Spatial Models and Modeling

1. Spatial Models and Modeling June 7, 2013 Institute of Space Technology, Karachi

2. Chapter 13: Spatial Models and Modeling

3. Model • Description of reality • Static reproduction that represents basic shape and form of an object • A conceptual description of key elements and processes in a system • Sophisticated replica of objects, events, or processes • For this class • Restricted to computer-based models of spatial features

4. Computer Based Spatial Models • Combination of • GIS • Computer programming languages • Spatial and non-spatial analytical tools

5. Two Broad Classes • Spatio-temporal Models • Dynamic in both space and time • Example: analysis of oil after spill • Cartographic Models • Static models • Involve application of spatial operations • Example: buffer, interpolation, reclassification, overly • Combine data from multiple data layers

6. Cartographic Models • Represent spatial features at a fixed point or points of time • Most GIS models are cartographic models that are temporally static • Provides information through a combination of spatial data sets, functions and operations • Reclassification • Overlay • Interpolation • Terrain analysis • Buffering, • Map algebra, etc.

7. Example: Suitability Analysis • Suitable park sites based on the proximity to Roads and Lakesand the absence of Wetlands

8. Flow Chart • A graphic representation of the spatial data, operations and their sequence of use in a cartographic model

9. Application • Land use planning • Transportation route and corridor studies • Design and development of water distribution systems • Human disease spread • Site selection • Pollution response planning • Endangered species preservation

10. Designing a Cartographic Model • Spatial functions and operations are mixed and matched in cartographic models • Variation in sequence of same operations will result in entirely different outputs • With a small set of data layers and tools, a huge number of models can be created • Usually produces a large number of ‘intermediate’ or temporary data layers that are not needed in final output or decision making

11. Designing the BEST Cartographic Model • Selection of appropriate spatial tools and specification of their sequence

12. Conti.. Designing a Cartographic Model • Based on a set of criteria • These criteria are usually defined in qualitative terms • The slope must not be too steep • Interpretation /translation of criteria into selection and sequence of spatial operations • What is meant by “too steep” • Need to be converted to specific, quantitative measures

13. Example: Home Site Selection • Problem: Ranking sites by suitability for home construction • Criteria: • Slopes should not be too steep • Southern aspect is preferred to enhance solar warming • Soils suitable for on-site septic systems • Sites should be far enough from a main road to offer some privacy but not so far as to be isolated

14. First convert these criteria into more specific quantitative terms • Check availability and quality of data • Do the required data layers exist for the study area? • Are spatial accuracies, spatial resolution and attributes appropriate for analysis • What level of map generalization? • If required data is not available • Obtain or develop the required data OR • Modify the goals • Explicit ranking of the relative importance of different classes or types of criteria

16. Ranking and Weighting • Ranking: Assignment of relative values within the same layer • How we rank a sandy soil vs. a silty soil in a soil layer • ‘Weighting’ – assigning the relative values of different layers • How we weight the values in an elevation layer vs. the values in a land use layer

17. Ranking Within Criteria • Each Criterion in cartographic model is usually expressed by a data layer or ‘criterion layer’ • Each criterion layer is a spatial representation of some constraint or selection condition • Select site outside floodplain: Floodplain sites = 0, Upland sites = 1

18. Discrete vs. Continuous Ranking • Discrete: when input data are interpreted such that criterion data layer is a map of discrete value • Soil = Good, Bad • Slope = steep or acceptable • Continuous: ranks vary along a scale • Soils: Rated from 1 to 100 for construction suitability

19. Discrete and Continuous ranking

21. Criterion: desirable sites are greater than 300 but less than 2000 meters from road

23. Weighting Among Criteria • Criteria combined in spatial analysis – in overlay or addition process • How to weigh one layer over another? • How important is slope relative to aspect? • Will an optimum aspect offset a moderately steep site? • The relative weightings given to each criterion will influence the result • Different weights are likely to result in different suitability rankings • Easy to define when importance of the various criteria expressed on a common scale – money • Reducing all criteria to a common scale removes differential weighting among criteria

24. Assigning Weights based on Importance Ranking

31. Spatio-temporal Models • Includes time driven processes within the framework of model • Feature boundaries, point feature locations, and attribute variables may change within model run • Complicated models