Project SLOPE1
WP 2 ndash Forest information collection and analysis
SLOPE WP 2 ndash Task 21
Kick-off Meeting 8-9jan2014
Andrea Masini PhD
Remote sensing and multispectral analysis
Remote Sensing DepartmentFlyby Srl
Task 21 general description
Kick-off Meeting 8-9jan2014
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
Task 21 participants
Kick-off Meeting 8-9jan2014
bullFlyby Srl (Leader)
bull CNR
bull Coastway
bull TreeMetrics
Task 21 expected output
Kick-off Meeting 8-9jan2014
bull Deliverable D201 (month 8 ndash August 2014)
Report on remote sensing data collected on the
methodologies and the algorithm to extract needed
information and on the generated output
Use of satellite data for forestry
Kick-off Meeting 8-9jan2014
Satellite imagery can be extremely useful in the forestry sector in particular for
bull forest health near real-time monitoring
bull accurate and wide forest inventory
Kick-off Meeting 8-9jan2014
Use of satellite data for forestry Studies
Different type of analysis
Kick-off Meeting 8-9jan2014
LOW SPATIAL RESOLUTION
EO data used so far for forestry
Kick-off Meeting 8-9jan2014
EO data used in the past for
bull Cover Change Detection bull Mapping biophysical structure bull Mapping ecosystem services (carbon water) bull Modelling trends under change scenarios bull Generating management plans
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
SLOPE WP 2 ndash Task 21
Kick-off Meeting 8-9jan2014
Andrea Masini PhD
Remote sensing and multispectral analysis
Remote Sensing DepartmentFlyby Srl
Task 21 general description
Kick-off Meeting 8-9jan2014
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
Task 21 participants
Kick-off Meeting 8-9jan2014
bullFlyby Srl (Leader)
bull CNR
bull Coastway
bull TreeMetrics
Task 21 expected output
Kick-off Meeting 8-9jan2014
bull Deliverable D201 (month 8 ndash August 2014)
Report on remote sensing data collected on the
methodologies and the algorithm to extract needed
information and on the generated output
Use of satellite data for forestry
Kick-off Meeting 8-9jan2014
Satellite imagery can be extremely useful in the forestry sector in particular for
bull forest health near real-time monitoring
bull accurate and wide forest inventory
Kick-off Meeting 8-9jan2014
Use of satellite data for forestry Studies
Different type of analysis
Kick-off Meeting 8-9jan2014
LOW SPATIAL RESOLUTION
EO data used so far for forestry
Kick-off Meeting 8-9jan2014
EO data used in the past for
bull Cover Change Detection bull Mapping biophysical structure bull Mapping ecosystem services (carbon water) bull Modelling trends under change scenarios bull Generating management plans
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Task 21 general description
Kick-off Meeting 8-9jan2014
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
Task 21 participants
Kick-off Meeting 8-9jan2014
bullFlyby Srl (Leader)
bull CNR
bull Coastway
bull TreeMetrics
Task 21 expected output
Kick-off Meeting 8-9jan2014
bull Deliverable D201 (month 8 ndash August 2014)
Report on remote sensing data collected on the
methodologies and the algorithm to extract needed
information and on the generated output
Use of satellite data for forestry
Kick-off Meeting 8-9jan2014
Satellite imagery can be extremely useful in the forestry sector in particular for
bull forest health near real-time monitoring
bull accurate and wide forest inventory
Kick-off Meeting 8-9jan2014
Use of satellite data for forestry Studies
Different type of analysis
Kick-off Meeting 8-9jan2014
LOW SPATIAL RESOLUTION
EO data used so far for forestry
Kick-off Meeting 8-9jan2014
EO data used in the past for
bull Cover Change Detection bull Mapping biophysical structure bull Mapping ecosystem services (carbon water) bull Modelling trends under change scenarios bull Generating management plans
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Task 21 participants
Kick-off Meeting 8-9jan2014
bullFlyby Srl (Leader)
bull CNR
bull Coastway
bull TreeMetrics
Task 21 expected output
Kick-off Meeting 8-9jan2014
bull Deliverable D201 (month 8 ndash August 2014)
Report on remote sensing data collected on the
methodologies and the algorithm to extract needed
information and on the generated output
Use of satellite data for forestry
Kick-off Meeting 8-9jan2014
Satellite imagery can be extremely useful in the forestry sector in particular for
bull forest health near real-time monitoring
bull accurate and wide forest inventory
Kick-off Meeting 8-9jan2014
Use of satellite data for forestry Studies
Different type of analysis
Kick-off Meeting 8-9jan2014
LOW SPATIAL RESOLUTION
EO data used so far for forestry
Kick-off Meeting 8-9jan2014
EO data used in the past for
bull Cover Change Detection bull Mapping biophysical structure bull Mapping ecosystem services (carbon water) bull Modelling trends under change scenarios bull Generating management plans
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Task 21 expected output
Kick-off Meeting 8-9jan2014
bull Deliverable D201 (month 8 ndash August 2014)
Report on remote sensing data collected on the
methodologies and the algorithm to extract needed
information and on the generated output
Use of satellite data for forestry
Kick-off Meeting 8-9jan2014
Satellite imagery can be extremely useful in the forestry sector in particular for
bull forest health near real-time monitoring
bull accurate and wide forest inventory
Kick-off Meeting 8-9jan2014
Use of satellite data for forestry Studies
Different type of analysis
Kick-off Meeting 8-9jan2014
LOW SPATIAL RESOLUTION
EO data used so far for forestry
Kick-off Meeting 8-9jan2014
EO data used in the past for
bull Cover Change Detection bull Mapping biophysical structure bull Mapping ecosystem services (carbon water) bull Modelling trends under change scenarios bull Generating management plans
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Use of satellite data for forestry
Kick-off Meeting 8-9jan2014
Satellite imagery can be extremely useful in the forestry sector in particular for
bull forest health near real-time monitoring
bull accurate and wide forest inventory
Kick-off Meeting 8-9jan2014
Use of satellite data for forestry Studies
Different type of analysis
Kick-off Meeting 8-9jan2014
LOW SPATIAL RESOLUTION
EO data used so far for forestry
Kick-off Meeting 8-9jan2014
EO data used in the past for
bull Cover Change Detection bull Mapping biophysical structure bull Mapping ecosystem services (carbon water) bull Modelling trends under change scenarios bull Generating management plans
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
Use of satellite data for forestry Studies
Different type of analysis
Kick-off Meeting 8-9jan2014
LOW SPATIAL RESOLUTION
EO data used so far for forestry
Kick-off Meeting 8-9jan2014
EO data used in the past for
bull Cover Change Detection bull Mapping biophysical structure bull Mapping ecosystem services (carbon water) bull Modelling trends under change scenarios bull Generating management plans
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
LOW SPATIAL RESOLUTION
EO data used so far for forestry
Kick-off Meeting 8-9jan2014
EO data used in the past for
bull Cover Change Detection bull Mapping biophysical structure bull Mapping ecosystem services (carbon water) bull Modelling trends under change scenarios bull Generating management plans
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
EO data used in the past for
bull Cover Change Detection bull Mapping biophysical structure bull Mapping ecosystem services (carbon water) bull Modelling trends under change scenarios bull Generating management plans
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
The vegetation indexes
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
Forest classification
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
RapidEye satellite imagery
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
RapidEye satellite - Forestry
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
RapidEye satellite ndash Forestry Studies
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Other high resolution satellite data
Kick-off Meeting 8-9jan2014
We will investigate the following data
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Kick-off Meeting 8-9jan2014
Task 21 main objectives
bull design of an automatic chain that provides a first level forest inventory exploiting satellite imagery
bull calculation of NDVI (Normalised Difference Vegetation Indices) to monitor tree growth and biomass production also in mountainous environment
bull first level forest inventory used also to drive more accurate UAVin-situ measurements
bull satellite-based data fusion with other data to achieve more accurate results
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
TreeMetrics
ldquoPROVIDE MORE WOOD FROM LESS TREESrdquo
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
INVENTORY PLANNING AND MANAGEMENT
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
WP 23 On-Field Digital Surveys The Problems
bull Productive Area
bull Stratification
bull Stocking
bull Stem Taper Variation
bull Stem Quality Variation
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Terrestrial Laser Scanning Forest Measurement System(AutoStem Forest)
Automated 3D Forest Measurement System
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Trusted and Independent Data
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
Technology amp Services3 Greater Forest Product Knowledge
Product Volumes
30
9
7
77
8
23
9
61
58
55
52
49
46
43
37
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
61 | |
58 | |
55 | |
52 | |
49 | |
46 | |
43 | |
37 |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
6 | 7 | 11 | 15 | 16 | 17 | 18 | 19 | 20 | 265 | 29 | 30 | 90+ | |||||||||||||||||||||||||||
61m | 60 | 62 | 64 | 66 | 68 | 70 | 74 | 76 | 76 | 76 | 76 | 76 | |||||||||||||||||||||||||||
58m | 58 | 60 | 62 | 64 | 66 | 68 | 72 | 74 | 74 | 74 | 74 | 74 | |||||||||||||||||||||||||||
55m | 56 | 58 | 60 | 62 | 64 | 66 | 70 | 72 | 72 | 72 | 72 | 72 | |||||||||||||||||||||||||||
52m | 54 | 56 | 58 | 60 | 62 | 64 | 68 | 70 | 70 | 70 | 70 | 70 | |||||||||||||||||||||||||||
49m | 52 | 54 | 56 | 58 | 60 | 62 | 66 | 68 | 68 | 68 | 68 | 68 | |||||||||||||||||||||||||||
46m | 50 | 52 | 54 | 56 | 58 | 60 | 64 | 66 | 66 | 66 | 66 | 66 | |||||||||||||||||||||||||||
43m | 48 | 50 | 52 | 54 | 56 | 58 | 62 | 64 | 64 | 64 | 64 | 64 | |||||||||||||||||||||||||||
49 (6cm) | 36 | 38 | 40 | 40 | |||||||||||||||||||||||||||||||||||
46 (6cm) | 34 | 36 | 38 | 38 | |||||||||||||||||||||||||||||||||||
43 (6cm) | 32 | 34 | 36 | 36 | |||||||||||||||||||||||||||||||||||
40 (6cm) | 30 | 32 | 34 | 34 | |||||||||||||||||||||||||||||||||||
37 (6cm) | 28 | 30 | 32 | 32 | |||||||||||||||||||||||||||||||||||
34 (6cm) | 26 | 28 | 30 | 30 | |||||||||||||||||||||||||||||||||||
31 (6cm) | 24 | 26 | 28 | 28 | |||||||||||||||||||||||||||||||||||
27 (6cm) | 22 | 24 | 26 | 26 | |||||||||||||||||||||||||||||||||||
30m Pulp | 18 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | ||||||||||||||||||||||||||
MKT | |||||||||||||||||||||||||||||||||||||||
Nurmes | 76203 | 2198 | 1684 | 1811 | 598 | 14716 | 2068 | 981 | 1707 | 352 | 13 | 865 | 731 | 107 | 405 | 348 | 2448 | euro6043 | euro6487309 | ||||||||||||||||||||
Rumo | 61533 | 3766 | 4071 | 2608 | 2416 | 56035 | 2772 | 6418 | 3185 | 2097 | 1333 | 875 | 1841 | 1103 | 4121 | 1962 | 4796 | euro4876 | euro7847303 | ||||||||||||||||||||
Tiilikkajarvi | 37183 | 20 | 869 | 76 | 636 | 752 | 659 | 112 | 1305 | 42 | 156 | 159 | 148 | 141 | 1398 | 437 | 1499 | euro5859 | euro3304760 | ||||||||||||||||||||
Dec OPt1 | |||||||||||||||||||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | euro6048 | euro6492393 | ||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | euro4878 | euro7849578 | ||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | euro5861 | euro3306211 | ||||||||||||||||||||
Eql Wts | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | euro5700 | euro6118829 | ||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | euro4606 | euro7413256 | ||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | euro5484 | euro3093269 | ||||||||||||||||||||
Dec 1 Oct Style | |||||||||||||||||||||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | euro5759 | euro6182316 | ||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | euro4505 | euro7250523 | ||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | euro5522 | euro3115186 | ||||||||||||||||||||
61m | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | 58m | ||||||||||||||||||||||
Nurmes | 74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | 55m | |||||||||||||||||||||
Rumo | 60873 | 4414 | 3277 | 2277 | 2416 | 55829 | 3984 | 7166 | 2877 | 1829 | 1333 | 875 | 2009 | 1173 | 3853 | 1834 | 4913 | 52m | |||||||||||||||||||||
Tiilikkajarvi | 36262 | 2319 | 1308 | 79 | 87 | 7325 | 758 | 102 | 1189 | 717 | 178 | 124 | 153 | 145 | 1128 | 47 | 1651 | 49m | |||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | 46m | |||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | 43m | |||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | 49 (6cm) | |||||||||||||||||||||
Nurmes | 29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | 46 (6cm) | |||||||||||||||||||||
Rumo | 19267 | 7135 | 703 | 8282 | 7871 | 16114 | 6563 | 8631 | 3002 | 5067 | 2872 | 4032 | 497 | 10026 | 3347 | 16196 | 351 | 43 (6cm) | |||||||||||||||||||||
Tiilikkajarvi | 13816 | 3621 | 3456 | 3705 | 4801 | 1339 | 4706 | 61 | 11473 | 675 | 1052 | 833 | 458 | 1609 | 1168 | 1729 | 1357 | 40 (6cm) | |||||||||||||||||||||
37 (6cm) | |||||||||||||||||||||||||||||||||||||||
34 (6cm) | |||||||||||||||||||||||||||||||||||||||
31 (6cm) | |||||||||||||||||||||||||||||||||||||||
27 (6cm) | |||||||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
74834 | 3263 | 229 | 1194 | 1233 | 14618 | 179 | 1625 | 1226 | 311 | 13 | 778 | 664 | 154 | 405 | 418 | 242 | |||||||||||||||||||||||
29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | |||||||||||||||||||||||
29755 | 10641 | 6351 | 8491 | 8904 | 1688 | 7537 | 1607 | 18577 | 2003 | 2063 | 1068 | 1094 | 2599 | 405 | 2779 | 179 | |||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
Opt 1 | 4929 | 3966 | 4793 | Dec OPT1 | 6048 | 4878 | 5861 | |||||||||||||||||
Eq Wts | 4928 | 396 | 4785 | Eq WTS | 57 | 4606 | 5484 | |||||||||||||||||
348 | 272 | 377 | ||||||||||||||||||||||
58 | 56 | 64 | ||||||||||||||||||||||
64923 | 78495 | 33062 | ||||||||||||||||||||||
6048 | 4878 | 5861 | ||||||||||||||||||||||
5759 | 4505 | 5522 | ||||||||||||||||||||||
289 | 373 | 339 | ||||||||||||||||||||||
48 | 76 | 58 | ||||||||||||||||||||||
61823 | 72505 | 31151 | ||||||||||||||||||||||
61m (15cm) | ||||||||||||||||||||||||
58m (15cm) | ||||||||||||||||||||||||
55m (15cm) | ||||||||||||||||||||||||
52m (15cm) | 61 | 58 | 55 | 52 | 49 | 46 | 43 | 37 | ||||||||||||||||
49m (15cm) | 29321 | 8668 | 7123 | 7209 | 7363 | 8267 | 23361 | 945 | ||||||||||||||||
46m (15cm) | ||||||||||||||||||||||||
43m (15cm) | ||||||||||||||||||||||||
49 Poles (6cm) | ||||||||||||||||||||||||
46 Poles (6cm) | ||||||||||||||||||||||||
43 Poles (6cm) | ||||||||||||||||||||||||
40 Poles (6cm) | ||||||||||||||||||||||||
37 Poles (6cm) | ||||||||||||||||||||||||
34 Poles (6cm) | ||||||||||||||||||||||||
31 Poles (6cm) | ||||||||||||||||||||||||
27 Poles (6cm) | ||||||||||||||||||||||||
30m Pulp |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Rumo | |||||||||||||||||||||||||||||||||||
Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Productive Area | (ha) | 926 | |||||||||||||||||||||||||||||||||
Total Volume | (m3) | ||||||||||||||||||||||||||||||||||
Measurement Data | Productive Area | Species | Stocking | Avg Volume | Avg DBH | Total Volume | VolProd Area | NoStems | |||||||||||||||||||||||||||
Forest Name | (Ha) | (stemsha) | (m3) | (cm) | (m3) | (m3ha) | |||||||||||||||||||||||||||||
Nurmes | 537 | SP | 293 | 063 | 28 | 66407 | 12369 | 1056 | |||||||||||||||||||||||||||
Nurmes | BI | 923 | 034 | 213 | 8883 | 1655 | 258 | ||||||||||||||||||||||||||||
Nurmes | NS | 508 | 042 | 225 | 32062 | 5972 | 764 | ||||||||||||||||||||||||||||
Nurmes Totals | 107352 | ||||||||||||||||||||||||||||||||||
Rumo | 926 | SP | 803 | 023 | 186 | 142089 | 15344 | 6274 | |||||||||||||||||||||||||||
Rumo | NS | 235 | 024 | 18 | 18845 | 2035 | 799 | ||||||||||||||||||||||||||||
Rumo Totals | 160933 | ||||||||||||||||||||||||||||||||||
Tiilikkajarvi | 3 | SP | 521 | 052 | 25 | 52144 | 17376 | 996 | |||||||||||||||||||||||||||
Tiilikkajarvi | NS | 318 | 057 | 263 | 4265 | 1421 | 74 | ||||||||||||||||||||||||||||
Tiilikkajarvi Totals | 56409 | ||||||||||||||||||||||||||||||||||
610 1 | 580 1 | 550 1 | 520 1 | 490 1 | 490 P 1 | 460 1 | 460 P 1 | 430 1 | 430 P 1 | 400 P 1 | 370 P 1 | 340 P 1 | 310 P 1 | Pulp30 | 270 P 1 | Waste | |||||||||||||||||||
Nurmes | 29321 | 8668 | 7123 | 7209 | 7363 | 3006 | 8267 | 2981 | 23361 | 1474 | 3227 | 994 | 783 | 856 | 405 | 509 | 1805 | ||||||||||||||||||
Rumo | 26015 | 2901 | 8254 | 4866 | 6333 | 20469 | 5448 | 22966 | 33394 | 1416 | 755 | 2608 | 2883 | 4308 | 2765 | 461 | 4149 | ||||||||||||||||||
Tiilikkajarvi | 12469 | 4303 | 278 | 4423 | 3244 | 189 | 6132 | 2531 | 12814 | 474 | 1436 | 366 | 225 | 584 | 49 | 324 | 1924 | ||||||||||||||||||
Eql Wts | Price per M3 | ||||||||||||||||||||||||||||||||||
Nurmes | |||||||||||||||||||||||||||||||||||
Rumo | |||||||||||||||||||||||||||||||||||
Tiilikkajarvi |
WP 23 On Field Digital Survey Systems
1 Forest Mapper System (SatForm 3D Remote Sensing Aerial LIDAR amp Imagery)
2 Terrestrial Laser Scanning Forest Measurement System (AutoStem Forest)
3 Real Time Forest Intelligence
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
1st Phase = Plot Selection2nd Phase = Stratification
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Select the right plot locations =Better predict log product breakout
Product gt50
SawlogPalletPulp
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
New Web Based System Forest Mapper
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
New Stand Analytics ndash Log distribution
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Technology amp Services6 Forest Valuation
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Online Forest Valuation amp Harvest Planning System (The Forest Warehouse)
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Full Integration ndash lsquoClosed Loop Controlrsquo
Multisource data
Tree modeling Parameters relationsHarvest control
Forest pre-stratificationInitial area
Spatial generalization GeostatisticsArea correction
Spatial analysis for field plots locations
TLS recordingField survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINALSTRATIFICATION
WEB SERVICES
DATA ANALYTICS
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Some Example Trials International Validation amp Facts
SkogForsk Sweden 20092013
Coillte Results 2008 UCC Stats Department 20102011 Industrial Trial Results
Scotland 20082013 Forest Research Forest Enterprise Scotland James Jones
Other Results Greenwood Resources Oregon SkoglandScap Norway Forestry South Australia US Journal of Forestry Island Timberlands Canada
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Example Skogforsk Sweden
Stroumlmsjoumlliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Stroumlmsjoumlliden 586 7
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Manual control measurements of all logs-Diameter and length-Approximately one diameter per meter-Average from two diameter measurements per sampling point
At Remningstorp 34 trees were measured by the operator using a caliper
Control trees
Example Swedish Government Validation
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Harvester production data- Stem length and diameter measurements were used as reference- Sample trees were harvested and harvester data collected- Diameter measurements registered every 10 cm of stem- Diameter from approx 08 m height to last cut in tree
Stroumlmsjoumlliden
Remningstorp
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
- GIS software onboard harvester for linking tree measurements from harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp stand 343
Spruce 343-1-06Pine 343-3-12
Dia
met
er
HarvesterControlTLS
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Site SpeciesNumber of
treesMean trees size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 112 000 013 01313 116 117
Spruce 185 101 -001 011 011-09 92 92
Birch 16 044 -001 010 010-80 156 175
Stroumlmsjoumlliden Pine 275 047 002 004 00530 88 93
Spruce 339 027 001 004 00426 94 97
Birch 29 021 001 003 00326 129 132
Volume estimates on individual trees
1 Volume on bark excluding top
Sweden Final Results January 2013
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Position of in-vehicle device to driver preference
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
In-Vehicle Unit
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Shape File amp Machine Location Geo-fence Sound
Alarm Feature Sound Alarm (Rivers ESB Wires etc)
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Final On-Field Survey Tree GPS position and actual product breakout
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Task 24 - 3D Modelling for harvesting planning
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
bull Objectives
bull Scheduling
bull Participants and roles
bull Overview
Outlook
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Objectives
Task 24 Goal To generate and make accessible a detailedinteractive 3D model of the forest environment
The WPrsquos purpose is to develop methodologies and tools to fully describe terrain and stand characteristics in order to evaluate the accessibility for and efficiency of harvestingtechnologies in mountain forests
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Scheduling
Start Month 7End Month 15Deliverable Harvest simulation tool based on 3D forest modelTotal MM 20Task leader GRAPHITECHParticipants CNR KESLA COAST BOKU GRE FLY TRE
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Participants role
GRAPHITECH(10) Task Leader It has in charge the development of tool for representing the virtual 3D environment of the mountain forest as well as the of the virtual system on mobile and machine-mounted displays Finally it will be involved into the developmet of the solution for interactive cableway positioning
CNR(1) Definition of the ldquotechnology layersrdquo (ie harvest parameters) and methodologies to coordinate tree marking with the subsequent harvesting operations
KESLA(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
COAST(2) Provide the input model for the virtual system combining the information of task 21 22 and 23
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Participants role
BOKU(2) it will be involved into definition of the ldquotechnology layersrdquo (ie harvestparameters) then on the developmet of the solution for interactive cablewaypositioning
GRE(1) Acting as final user in order to simulate the behaivor of own machine into the virtual system
FLY(1) Provide the input model for the virtual system combining the information of task 21 22 and 23
TRE(2) Development of the Forest WarehouseTM for mountain forestry and support the deployment of the virtual system on the machine-mounted display
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Platform Core
Using the remote data (Satellite UAVs orthophotos and digital surface model) combinedwith on field information (TLS) each single tree feature will be segmented including itsdeducted geometric properties
Task 21
Task 22
Task 23
3D forest modelVirtual 3D
environment
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Functions
bull Forestry measurements estimationsThe platform will allow the combination of accurate tree profile information with up to date remote sensing data
bull Interactive system for cableway positioning simulation
bull Definition of the ldquotechnology layersrdquo (ie harvest parameters)Technological layers show technical limitations of machines and equipment on different forest areas
bull Deployment of the virtual system on mobile and machine-mounted displays
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Functions
bull Forest WarehouseTM (Treemetrics) for mountain forestry integration
The Forest Warehouse is a web-based forest planning system that performsbucking (log making) simulation through software developed by TRE
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
3D Visualization Technologies
Interfaces Scenariobull Desktopbull Mobile bull In-vehicle embedded
Systems
Approachesbull Desktop Visualization Platform
with Mobile Portingbull Web-Client Visualization
Platform
Desktop Platformbull Open-Source Library for 3d
visualization (OpenInventor Vtk Openscenegraph)
bull 3d Engine ( UdK IrrichlichtEngine Unity 3d)
Technologies
Web Client bull WebGL implementation of
OpenGL ES 20 for web programmable in JavaScript
bull Java Applet based on OpensourceGlobe Nasa World wind
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Kick-off Meeting 8-9jan2014
Thank you for your attention
DR FEDERICO PRANDI
Federicoprandigraphitechit
Fondazione GraphitechVia Alla Cascata 56C38123 Trento (ITALY)
Phone +39 0461283394Fax +39 0461283398
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Project SLOPE61
T 25 ndash Road and Logistic planning
Trento January 8th 2014
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
Index62
1 Task objectives
2 Approaches for sites location and flow allocation decisions
3 Approaches to estimate traffic in existing roads
4 Proposed work plan
5 Contact info
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
1 Task objectives63
Task objectives
Identify and analyze logistics elements within the forest and their characteristics for site locations and flow allocation decisions
Integration of the data with the global forest model Build and validate and Optimization model to allocate landings with the mills and
plants Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
To be developed from M8 to M13
Includes development of ldquoD205 Road and logistic simulation modulerdquo Due to Month 13
Partners involved all ITENE (leader) GRAPHITECH CNR BOKU FLY
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
64
The goal is to determine an optimal (minimum cost) forest logisticnetwork to respond future demands
The approach should determine Location of facilities (specially for new requirements) Size an capacity of facilities (storage areas and processing sites) Volume to harvest in every landing and stand area Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning) Volume of product to transport from facilities to demand sites
The model should consider inputs like location of landing aacutereas intermediate sites (storage buffers) processing sites demand sites demand volumes routes type of routes and distances between thesessites
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
65
Location of a single facility by center-of-gravity method Output XY coordinates for the facility Optimization based only on distances Binary model (source-sink) Useful for a first estimation of a facility location
to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
66
Location of selected number of facilities by the exact center-of-gravity method Output XY coordinates of a selected number
of facilities Optimization based only on distances Binary model (source-sink) Useful for a first estimation of 2 or more
facility locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
67
P-median multiple facility location Output selected facilities from a list of
candidate sites receiving flows from other sites Optimization based on transport costs and fix
costs but lack of capacity constrains and other inventory costs
Binary model (source-sink) Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
68
Mixed integer linear programming problem Output selected facilities and optimal flows
between nodes Optimization based on transport costs and fix
costs capacity constrains and inventory costs Three stages model More appropriate approach for a network with
more than 2 node types
lands in forest
storageand
facilities(saw mills biomass)
Demandsites
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
69
Dynamic linear programming Consider changing demand Output
Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
Minimize total costs for timber supply and transport investment and operational costs product transport cost to demand sites fixed cost for capacity expansion
- 200 400 600 800
1000 1200
1 2 3 4 5 6 7
Period Demand Volume
lands in forest
storageand
facilities(saw mills
biomass)
Demandsites
(normallycities)
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
70
Previous Work
Facilities Location Models An Application for the Forest Production and Logistics
JUAN TRONCOSO T 1 RODRIGO GARRIDO H 2 XIMENA IBACACHE J 3
July 2002
1 Departamento de Ciencias Forestales Pontificia Universidad Catoacutelica de Chile Casilla 305 Correo 22 Santiago Chile E-mail jtroncotpuccl
2 Departamento de Ingenieriacutea de Transporte Pontificia Universidad Catoacutelica de Chile3 Escuela de Ingenieriacutea Forestal Universidad Mayor
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
71
StandCable ways
forestlanes
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
72
minorroad
mainroad
land
land
land
stand
stand
stand
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
73
Solution flow
Possible flow
lands in forest storage and facilities (saw mills biomass)
Demand sites(normally cities)
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
74
INPUTS Demands of product per each period and type of quality from demand site
DATA COLLECTION FOR THE MODEL Positions of stands lands storage areas processing sites (saw paper mills and
biomass heating and power plants) demand sites Volume available to harvest in every stand per quality of timber and destination (saw
mill or energy) Position for stand respect existing roads Slope or grade of difficulty to access Capacity of ground to support specific machinery Size and availability of skyline deployment sites Capacity and location of storage areas and buffers and processing sites Characteristics of processing sites and conversion facilities Distances between different nodes
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
2 Approaches for sites location and flowallocation decisions
75
COST FACTORS supply and transport operational costs final product transport cost to demand sites fixed cost for capacity expansion during the planning horizon investment associated to construction of a new site
OUTPUT Selected facilities Size an capacity of facilities (storage and processing sites) Volume of harvest in every landing and stand aacuterea Volume to transport
Timber from landings to facilities
Product from facilities to demand sites
Decision to expand production capacity in a specific period in the planning horizon
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
3 Approaches to estimate traffic in existing roads
76
Once the different sites and locations have been selected and flows between sites have been determined for each future period
A Logistics Resource Planning Model will be used to determine the volume to harvest in every period in every land processing and transport means and a more precise estimation of traffic in every individual sections of road in terms of number of trip per vehicles type (size weight) in each period
This traffic estimation will allow to define plans for road maintenance and construction in the forest area taking into account the capability of roads to accept trucks and cranes of different weights and sizes
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
3 Approaches to estimate traffic in existing roads
77
Similarities to DRP method
Land 1
SITE Saw PlantX
City 1
Product demandHarvest orders
Land 2 City 2
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
3 Approaches to estimate traffic in existing roads
78
SITE Saw Plant X Minumum Batch (harvest) (m3period) 500 Lead time (number of periods) 1 Safety stock (m3) 200
Period 1 2 3 4 5 6 7 Demand Volume (m3) 400 500 600 1000 500 600 1000 Available Stock (m3) 700 300 300 200 200 200 100 100 Harvest recepcion (m3) - 500 500 1000 500 500 1000 Harvest order launch (m3) 500 500 1000 500 500 1000
Land 1 To harvest (m3) 500 500 1000 Available m3 in land 1 2000 1500 1000 -Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100
land 2 To harvest (m3) - - - 500 500 1000 -Available m3 in land 1 3000 2500 2000 1000 1000 Size of vehicle (m3) 10 Number of vehicle trips size 10m3 50 50 100 -
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
3 Proposed work plan79
Understand the forestry supply chain and logistic processes Choose a real scenario (ITENE BOKU)
Review literature and formulate an Optimization model for logistics site location and flow allocation decisions (BOKU)
Define a model to estimate traffic in existing roads (CNR)
Identify elements for the models
Relevant logistics locations within the forest (GRAPHITECH CNR FLY ITENE)
Gather info and contact with the different agents of the forest product processing (ITENE)
Define and analyze relevant characteristics of the logistics elements (ITENE)
Integration with the global forest model (ITENE)
Implement the Optimization model to allocate landings with the mills and plants and traffic calculation on individual sections (BOKU)
Validation of model with a real scenario (BOKU)
Implement the model for road planning based on the amount of timber to be transported and identification of traffic on existing forest infrastructure (CNR)
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom
4 Contact info80
Emilio Gonzalez egonzalezitenecom
Patricia Bellver pbellveritenecom