Prof. Dr. Reinhard Zölitz-Möller

University of Greifswald

Institute of Geography and Geology

Chair of Cartography and GIS

Germany / Greifswald and Vietnam / HaNoi

Greifswald

HaNoi

Cologne Dresden

Bremen

Hamburg

Frankfurt

BERLIN

Greifswald

Munich

RostockWhere is Greifswaldin Germany?

Institute of Geography and Geology

Ernst- Moritz- Arndt University Greifswald

Departments of Geography

Human Geography• Geography of Tourism• Regional Geography• Applied Human Geography, Regional Planning

Physical Geography• Applied Physical Geography / Hydrology • Physical Geography, Coastal Management• Soil Science and Geo-Ecology

Cartography and GIS

Education of teachers

Projects and research in the department of Cartography/GIS:

Digital Historical Maps (DHM), maps on the internet, web mapping

Protection of water and soil resources using GIS

GIS as decision support systems

Introducing GIS in governmental authorities and companies

Regional Economic Atlas (produced using ArcGIS)

Sea level changes in the baltic sea region and possible response of regional planning to rising sea level in the future

Internet atlas and herbarium of Mongolian flora

.

GIS Summer School in Hanoi, Sept / Oct 2007:

Module: GIS applications (AP1)

A. Introduction, Examples (morning)

B. Exercises (afternoon)

A. Introduction

1. Introduction, Principles

2. Examples of GIS application:

a) Soil erosion modelling with GIS

b) Modelling the effects of sea level rise for reg. planning

c) Looking for best location of new wind power stations in a region of SW-Germany

Introduction, Principles

Disciplines of „GIS science“:Disciplines that have traditionally studied the Earth,

particularly its surface and near-surface, in either physical or human aspect, e.g.: Geography Geology Geophysics Oceanography Agriculture Biology, particularly Ecology, Biogeography Environmental science,Landscape ecology Sociology Political science Anthropology and many more

GIS Applications: Natural Resources

Agriculture – land conservation, farm planning, precision farming

Forestry – timber assessment and management, harvest scheduling and planning, forest planning, environmental impact assessment, pest management

Wildlife – habitat assessment and management, rare species studies

Catchment management – runoffs and erosion modeling, sedimentation and water quality studies, integrated catchment management

Geology and mining – geologic hazard mapping, oil, gas and mineral studies, open pit mine design

Watershed management - guidelines for regulation

GIS Applications: Urban Resources

Spatial distribution of Utilities Hospitals Schools Fire Stations

Management of water discharge Crime analysis Waste collection routing Hazardous waste transportation Disease outbreak patterns

Typical field of GIS application is “Decision Making”

Decision making is driven by applications GIS helps in the decision making process, it´s the most important

component in spatial decision support systems GIS application examples for decision making:

Urban planning: Where should we build new hospitals? Schools? Fire stations?

Agriculture: Should we apply pesticides? Where and how much per acre?

Forestry: Where and when should we cut trees? How many? Wildlife: What should we do to help endangered species? Watershed/Catchment management: Would we have a surface erosion

problem after cutting trees? Archeology: Where should we excavate to find prehistoric sites? Geology and mining: Is it safe to build houses in the location (lat/long)?

Decision Making: Motivation / Process / Goal

Motivation: Seek optimal solutions How?

Evaluate multiple solutions Assess quality and significance of input variables Predict output variables Impose application specific constraints Construct optimality metric

Goal: To make the optimal decision Planning decision Management decision

Model

is a representation of a part of the real world that has certain characteristics in common with the real world.

Advantages: This allows to study the real world processes

indirectly, using the model as best fit to the real world

Scenarios are possible by changing the data of the model (what if …)

Important GIS- functionalityfor steps of analysis in GIS applications:

• Select (by attribute)

• Data export (of selected objects as shape file)

• Dissolve

• Buffer

• Clip

• Union

• Table work (add field, calculate area)

Analysing: Buffers Around points, lines and polygons

Processing of line buffers

Quelle: Chrisman 1997

Buffer processing is generated in several steps (behind the user interface):

1. Build distance zones for each line segment

2. Construct two semi-circle polygons around the end nodes of the line segment, and one rectangle polygon

3. Overlay all generated polygons (union)4. Dissolve polygons, eliminate duplicate

areas

Demo: Buffers Select objects to be buffered Generate buffers

Demo Hanoi

Result: 3 buffer rings of 30 km around HaNoi

Demo Hanoi

Clip

Demo: ClipInput map theme: Districts in SE Asia

Clip map theme: Vietnam

Result map theme: districts of Vietnam

Demo: eco regions + country92

Dissolve

Demo: Dissolve

Districts in SE Asia

Attrib. table contains country names

Country name used for classification: borderlines inside countries still exist

Result after dissolve by country name

Demo: admin by country name

Map overlay • Overlay mapping is not really a modern and new

technique, it is well known from the analogue (not digital) world of map use.

• Aim of overlay is combining of information from 2 or more different maps (map layers) for the same investigation area.

• In analogue manner (paper maps) it is done by the overlay of paper maps and / or transparent plastic film (foil) on a light-desk; this is troublesome and long-lasting, and the spatial resolution of such an analogue analysis is restricted to the mapscale of the paper maps.

• Digital map overlay today is a very important and useful function in GIS software.

Map overlay• Aim: to produce a new map (layer) from 2 input maps• It is done by geometric overlay and re-calculation of

geometry and topology• … and appending all (or all wanted) attribute data from all

input objects to the new generated geo-objects of the result map

• It is one of the most important operations in GIS analysis• For the programmer it is simple to realize in Raster-GIS:

linear combination of raster cells; for the GIS user: fast working

• For the programmer it is more complex in Vector-GIS; for the user: overlay processing takes much more time when dealing with complex maps with many objects (e.g. polygons)

Map overlay in Raster GIS

Source: Chrisman 1997

Overlay of 3 Layers with „map algebra“:

Map overlay of 2 layers

Source: Ashdown & Schaller 1990

Map 1:

Vegetation

Map 2:

Soil

Result map:

Composite

Map algebra with help of map overlay

• generating new information by combining attributes of different map layers

• types of combination:- dominance

- summarize / multiplication

- decision tree

source: Chrisman

Map overlay in Vector GIS • For computation more

complex• Computation of all

crossing points between borderlines of 2 maps is necessary

• … then set new nodes at these crossing points

• … then build new topology of all new polygon objects

• … then produce new attribute table, which contains all (or all wanted) attributes of the 2 input map layers

Source: Streit 2000

Soils Forests

Soils in forests

Types of map overlay Points with polygons

Lines with polygons

x

Polygons with polygons

Source: Streit 2000

Polygon with polygon overlay: “Union”

Source: Scholles 2000

“Union” produces the union set of 2 input geometries: in this example out of 4 + 1 polygons 12 polygons are generated.

Polygon with polygon overlay: union in ArcGIS

UnionMap 1: eco regions Map 2: countries

union

Map 3:

Result of union with full information on ecoregions and countries in one map layer

Demo: eco regions + country92

Source: Scholles 2000

“Intersect” produces the intersection set of 2 input geometries.

Demo: CountryVN + admin

Polygon with polygon overlay: “Intersect”

Problem: sliver polygons

source: Chrisman 1997

• map overlay may produce artefacts:

• very small “sliver polygons”• causes:

• 2 layers independently digitized

• 2 layers with different original mapscale

• this problem occurs particularly, where the content of the maps are correlated somehow

• e.g.: borderlines of a wetlands map and a land cover map

• Demo: Country + admin

Problem: multipart polygons

source: Chrisman 1997

• Result of buffer, union, intersect may be multipart polygons• = 1 object, consisting of several geometrically distinct parts

(areas)• = only 1 geo-object (row) in the attribute table • single geometric parts (areas) of a multipart polygon cannot be

selected singularly• If you want so select every single area unit of the multipart

polygon, first you have to run the multipart-to-singlepart tool in the toolbox

• Demo:

• buffer HaNoi and HCM-City each with 8 rings of 100km without dissolve

• Look at the result• Run the multipart-to-singlepart tool and look again at the result

Examples of

GIS applications

1.Soil erosion

modelling

Combination by multiplicationUSLE: Universal Soil Loss Equation

(Wischmeier & Smith 1965)

A = R * K * L * S * C * P

A = mean annual soil erosion

R = rain factor (constant for a small and flat investigation area)

K = erodibility (estimated from soil map , f (soil texture)

L = factor of slope length (derived from DEM and landuse map, f(length of arable fields in slope direction))

S = factor of slope (derived from DEM)

C = crop factor (derived from landuse map, f(crop sequence))

P = protection factor

Rainfall erosivity in Hoa Binh province

Landuse map

source: ÖZK 1998

needed for:

L = factor of slope length (derived from DEM and landuse map, f(length of arable fields in slope direction))

C = crop factor (derived from landuse map, f(crop sequence))

Calculated crop factor

source: ÖZK 1998

C = Crop-Factor

derived from landuse map, f(crop, crop- sequence)

Calculated factor of erodibility

source: ÖZK 1998

K = erodibility (estimated from soil map,

f (soil texture)

Factor of erodibility in Hoa Binh province

Result map

source: ÖZK 1998

A = mean annual potential soil erosion by runoff water

2. GIS for location planning:

Areas suitable

for new wind power stations

• Wind is free of charge, it´s a renewable energy source from nature

• Environmentally positive energy source

• Hence, producing electric power from wind is funded and privileged by the government in Germany since 1990ies

• Result was: very many wind power stations in several regions

Use of wind power in Gemany

Wind power stations

• Disadvantages in certain regions:

• Disturbance of (protected) birds

• Possible disturbance of nature reserves etc.

• Disturbance of people living very close to the wind power stations (shadow, noise)

Disadvantages of wind power stations

Conclusion:

New tasks for planning authorities (regional planning): Identify areas which are suitable for new wind power stations!

Criteria in planning of areas for new wind power stations• mean wind speed (10 m above ground surface) at least 3.5 m / sec

• not in settlements, housing areas (villages, towns)

• minimum distance of 500 meters apart from settlements places

• not in forests

• not in nature protected areas (nature protection, landscape protection, nature parks)

• outside of nature-2000-areas (flora-fauna-habitat guideline and birds protection guideline of EU)

• not in areas of regional nature protection interest (protection and development of biotope networks)

• minimum size of 100 hectares

How to implement this task in GIS?

• Now: look through data of „wind-long“ and talk about all GIS (analysis) functions, which are needed

• Exercise in the afternoon: work with data of „wind-short“ by yourself (with my help), produce the right result

Possible workflow for this application:

1. <select> forest areas from landuse, <export data> as shape-file forest

2. <select> areas with wind speed < 3.5 m/sec from wind, <export data> as shape-file wind35

3. <select> areas with preservation aim or development aim from biotopenetwork, <export data> as shape file biodevelpreser

4. <select> housing areas from landuse; <buffer> selected housing areas with 500 m distance (include housing areas, dissolve overlaps), result map = housingbuffer; <clip> this map with investigatianarea, result map = housingbuffclip

5. housingbuffclip <Union> investigationarea = exclude1

• <functions> in sharp brackets

• Input maps and result maps in Italics

Possible workflow for this application:6. exclude 1 <union> biodevelpreser = exclude2

7. exclude 2 <union> wind35 = exclude3

8. exclude 3 <union> forest = exclude4

9. exclude 4 <union> ffh-areas = exclude5

10. exclude 5 <union> landscapeprot = exclude6

11. exclude 6 <union> naturalpark = exclude7

12. exclude 7 <union> naturereserves = exclude8

13. Run the <multipart-to-singlepart> tool on exclude8, result map = exclude81

14. <select> from exclude81 all polygons, which fulfill the criteria for wind power stations: Define in the <select by attribute> function a complex statement, use therefore „and“ in order to combine multiple criteria, all of which have to be fulfilled

Possible workflow for this application:15. <calculate> the areas of all suitable (now selected) polygons using - when

the tables window is open - first the <add field> function (new field with double precision) and then the <field calculator> loading the script area.cal. The result units are square meters, because the map units are meters. Then recalculate the area in square meters into hectars, dividing it by ___?

16. <select> now polygons >=100 ha, these are the result polygons; <export> this selection as resultmap

17. sum up the area in ha, write it as text into your map in the map layout window

18. Add your full name to the map, make up the map a little bit using your cartographic expertise, then export your map as an image file (*.bmp).