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(NR) International Symposium on Land Cover
Mapping for the African Continent
TMEN
T ( Mapping for the African Continent
June 25-27, 2013
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FAO Land Cover Mapping methodology
UNEP HQ & RCMRD, Nairobi, Kenya
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FAO Land Cover Mapping methodology,
tools and standards
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&
GLC SHARE d b
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URA GLC–SHARE database
R C i & J h L hRenato Cumani & John LathamLand and Water Division (NRL)
(NR)
Content FAO Global Land Cover Network
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Standards for Land Cover mapping
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African land cover databases Global Land Cover SHARE
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Global Land Cover SHARE database Conclusions
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Main activities of the organization Putting information within reach
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Sharing policy expertiseP idi g ti g l f ti
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Bringing knowledge to the field
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FAO Global Land Cover Network (GLCN)Main Objectives:
T i li k b t l b l i l d
TMEN
T ( To improve linkages between global, regional and
national studies on land cover and the environment To improve standardization, homogenization,
compatibility and efficiency of information provided
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p y y pby different applications To provide information that improves design and
efficiency of sampling for validation of land cover products at global regional and national levels
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products at global, regional and national levels. To increase use and sharing of remote sensing data
and its derived datasets To provide comparable products at global, regional,
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To undertake capacity development and institution strengthening to maximize benefits for developing countries
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countries To support operational development and use by
national stakeholders of products emanating from the programme
multi-date landsat imagery
Sudan(N
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FAO GLCN Core activities Establish global network Develop Land cover mapping methodology
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Standards development (LCCS/LCML) Land Cover Mapping Toolbox
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Technical assistance to national experts for land cover mapping activities
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pp g Preparation of guidelines, manuals,
templates, workshops, technical papers, metadata
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Awareness raising workshops, training resources and sessions
•Nepal
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Dissemination and outreach (FAO GeoNetwork and FAO GLCN website) E bl f th l d i f ti Enable use of the land cover information
multi-date landsat imagery
St d d d Cl ifi ti S t
Standards and Tools (N
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Standards and Classification SystemLCCS / LCML / ISO 19144-2:2012
LCCS C h i th d l f d i ti
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characterization, classification and comparison of most land cover features identified anywhere in the
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comparative classification. (6 UN official languages)
Created in response to a need for a harmonized
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Created in response to a need for a harmonized and standardized collection and reporting on the status and trends of land cover
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Standards and Tools (N
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LCCS databasesGlobal Land Cover
(GLC) 2000
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1 km resolution
The dataset was
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members of the VEGETATION programme
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programme, including JRC.
Each partner used the Land Cover
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System (LCCS) produced by FAO and UNEP which
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ensured that a standard legend was used across
the globe
Standards and Tools (N
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LCCS databasesGlobCover ~2006
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300 m resolution
The GlobCover Land Cover
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Land Cover product is based
on ENVISAT MERIS data at f ll l ti
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full resolution from January 2005 to June
2006. The
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006. e GlobCover Land Cover product is
labelled di t th
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UN Land Cover Classification
Systemy
Standards and Tools (N
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FAO Land Cover Mapping ToolboxACCURACY MULTI USERTHEMATIC INTERPRETATION
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ANALISYSMULTI USER DATA BASEBROWSER
THEMATIC& CART. ASPECT
INTERPRETATIONEFFICIENCY
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Land
cover
Map
Acc.
Advanc.
Database
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Syst
Prog. GATEW.
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Syst.
DATA PRODUCERS DATA USERS
LCCS 2: 2001 LCCS 3: 2013
Standards and Tools (N
R)LCCS 2: 2001 (use LCCS)
LCCS 3: 2013 (use LCML/UML)
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ADG 2: 2003 ADG 3: 2013
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ADG 3 for ArcGIS 10.x: 2013
Mapping Device Change Analysis Tools Standards and Tools
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Mapping Device – Change Analysis Tools (MADCAT)
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Application designed by FAO Uses object‐base classification
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Wizard driven installation
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Implemented using .Net Framework Coding with LCCS2 and LCCS3 R i Wi d XP / Vi t / 7 /8 (32 d 64
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bit) Free to use for FAO programmes
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f p g One time activation needed:
Institution, User Name, Address, PC CODE
send request by email
Africa Land Cover products(N
R) Country scale (30m or better resolution) i ECONET
FAO’s Land Cover Mapping in AfricaTM
ENT
( •on going ECONETEthiopia
•2012 Fouta Djallon
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Malawi•2011 Sudan
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•2010 South SudanTunisiaKenya Update
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Kenya Update•2007 Somalia•2006 Kenya LCC •2005 Senegal
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•2004 Libya•1998- 2002 AFRICOVER
Africa Land Cover products(N
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GLCN/AFRICOVER: East Africa ModuleDevelopment of a regional database and regional aggregation
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Project facts: Mapped area: 8.5 million
Km2
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Landsat Scenes used: more than 400P i d f i i 998
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Period of activity: 1998-2004
Result: Multipurpose Africover Database for
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Africover Database for the Environmental Resources produced at a 1:200,000 scale
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countries and specific areas)
Burundi DR Congo Egypt EritreaBurundi, DR Congo, Egypt, Eritrea, Kenya, Rwanda, Somalia, Sudan,
Tanzania and Uganda.
Africa Land Cover products(N
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Fouta Djallon AOI: ca 400 000 Km2
Fouta Djallon Highlands land cover changeTM
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( Fouta Djallon AOI: ca. 400,000 Km 5 Countries within the AOI:
Guinea, Guinea-Bissau, Mali, Senegal, Sierra Leone
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LANDSAT coverage (30m res) 1990-2005ASTER coverage (17 m res) 2008-2011
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RapidEye coverage (5 m res) ~2005
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14000 1990Fouta Djallon Highlands land cover changes
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20003000400050006000700080009000
1000011000120001300014000 1990
2008
010002000
AG NVH NVS NVT URB WAT
Africa Land Cover products(N
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Malawi Land Cover change database (1990’s-2010’s)
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From other to cropland (square blue) and vice versa (square blue) and vice versa (circle orange)
Africa Land Cover products(N
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Primary datasets:
Sudan Land Cover
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Landsat 30m (~2000, ~2005-2007 ) Spot4 imagery
2009-2010, 2.5-5m, 10-20 m res
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2009 2010, 2.5 5m, 10 20 m res
IRS 2007, 15-22m res Aster 2005-2010,15 m res.
Ancillary:
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Ancillary: Googe Earth high resolution imagery Africover dataset (dated 1999-2000)
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Digital ATLAS (DVD) Posters
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Implemented in Sudan Capacity to undertake land cover p y
assessments
Africa Land Cover products(N
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Primary:
Land Cover Map of South SudanTM
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( Primary: Landsat ETM imagery (GLS),
30m res., false color. 2000 circa
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• 2005-2007 Spot4 imagery
2006 2008 10 20
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• 2006-2008, 10-20 m res., true color.
ill
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Google Earth high resolution imagery
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Africa Land Cover products(N
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55 land cover classes
Senegal Land Cover Change: 2005TM
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( 55 land cover classes Landsat 1990’s and
2005’s Completed in Senegal
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with involvement of national exerts
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Africa Land Cover products(N
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Libya Land Cover databaseTM
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Landsat ETM+ imagery 2001’s and 2002’s 88 landsat scenes in total
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88 landsat scenes in total
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Africa Land Cover products(N
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ECO–NET Africa Earth Cover Network Africa Sample tiles at 10 by 10 Km
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at half degree Very high resolution
imagery (targeted 5m or b )
BASIC OBJECTS PROPRERTIES CHARACTERISTICS
Herbaceous Cover 30 – 50 % CultivatedRainfedFi ld i 1 h
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Detailed land cover mapping using LCML enriched with vegetation
Field size 1 ha
Tree Cover 1 -3 % NaturalEight 5 -8 m. Disposition: irregular
Leaf type: BroadleafLeaf type % 100
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enriched with vegetation index(es) from remote sensing About 9,000 sampling sites
C di t d d i d
Scrub Cover 2 – 4 % NaturalEight 1 – 3 m. Disposition: irregularLeaf type: BroadleafLeaf type % 100
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by FAO GLCN with engagement of national experts 0 24
0.30
0 08
0.10
on
AverageTotal St. Deviation
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experts
0.06
0.12
0.18
0.24
ND
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vera
ge
0.02
0.04
0.06
0.08
ND
VI S
tand
ard
Dev
iatio
0.00
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35Dekad
0.00
Africa Land Cover products(N
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ECONET Outcomes Create a database with extremely
detailed information global or regional
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comparable and continually updated in support of a wide range of activities.
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information at any level of detail or complexity. Using specific software on the
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Web, any end users worldwide will be able to define a geographical area and the categories for which area statistics
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Provide the most consistent, detailed and dynamic test site for calibration and/or
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yaccuracy assessment of any future wall-to-wall global, regional or national Land Cover mapping programmespp g p g
GLC-SHARE database(N
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GLC-SHARE approach FAO System of Environmental Economic
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Accounts (SEEA) London Group process
Global Consultations, interviews,
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A significant step in improving the information accuracy of global land cover
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information accuracy of global land cover database
It integrates the best land cover data
Recommendation 19b.1: That the Land Cover Classification System (LCCS 3) developed by FAO should b d t d th l d
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It integrates the best land cover data available (at sub-national, national, regional and global level) into one single harmonized
be adopted as the land cover classification system in the revised SEEA and that the LCML (ISO 19144-2) should be adopted at the
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database
It uses international standards: ISO TC
19144 2) should be adopted at the methodology for linking to external sources of land cover data described in other land cover
211 – 19144-2:2013 LMCL systems.
GLC-SHARE database(N
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GLC-SHARE design principlesTM
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Use existing available land cover databases at national, regional and global level;
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Use the land cover legend prepared by SEEA and FAO based on the Land Cover Meta Language;
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Land Cover Meta-Language;
Make use of the harmonization of the land cover elements addressing semantic requirements;
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addressing semantic requirements;
Use data fusion technology;
Progressively update the database getting input from the community
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of users and include additional datasets as they become available.
GLC-SHARE database(N
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GLC-SHARE: fact-sheet Uses the FAO SEEA LCML(*) legend
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30 arc-second pixel resolution 11+1 layers indicating the % share of
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y geach class Dominant land cover layer and quality
score
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score Overall class accuracy ~80% Designed as a platform to facilitate
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Designed as a platform to facilitate crowd-sourcing Compatible with FAOSTAT classification
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update
Methodology and datasets will be published in 2013Methodology and datasets will be published in 2013
GLC-SHARE database(N
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GLC-SHARE SEEA Legend
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GLC-SHARE SEEA LCML Legend
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GLC-SHARE database(N
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Coverage of land cover databases
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GLC-SHARE database(N
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Processing ChainTM
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(
Multi-source and multi-resolution data fusion through use of the land cover class elements and the LCML
l f d l l d h h
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to use the optimal spatio-temporal information at pixel level
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Per product and per class rating assigned by technical experts (experts opinion)
O t t i l d 11 t t 30 d 1
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dominant land cover dataset, 1 quality indicator dataset including source date, resolution, sensor and confidence level per pixel metadata and technical
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paper
GLC-SHARE database(N
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GLC-Share DatabaseTM
ENT
( D
EPA
RTO
URC
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Distribution of the validation points
GLC-SHARE database(N
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Quality AssessmentUsed ~1 000 points (ArcGIS and Google Earth validation)
Distribution of the validation points
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Overall dominant class accuracy ~80%
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GLC-SHARE database(N
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( D
EPA
RTO
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GLC-SHARE database(N
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GLC-SHARE Summary GCL-SHARE is the first global database created using the
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ISO standard for land cover classification ISO TC 211 –19144-2 LMCL (Land Cover Meta Language) and is designed to be improved over time
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GLC-SHARE will be used to update Land Use Systems 2010 (FAO)
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2010 (FAO)
Planned to be made publicly available for comments and feedback by end of 2013
F ll d t d i l di t d t LCML/LCCS3
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legend
Update of the beta release with new available datasets
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new national land cover datasets
Maintained by FAO and community of practice partners y y p psuch as GEO, CGIAR, JRC, IIASA
Th k (N
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Thank youContacts:
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Links:
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Links:www.fao.org
www.fao.org/nr/gaez
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www.fao.org/nr/gaezwww.fao.org/geonetwork
www.glcn.orgwww.glcn.org
