gis applications zm_1
TRANSCRIPT
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).