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Reminder

Learn about different types of spatial models and their applications in decision-making. Explore multicriteria evaluation and weighted overlay techniques for suitability analysis.

jfraley
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Reminder

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  1. Reminder • Data Dictionary is due Thursday (Nov. 9th) Lecture 13B

  2. Spatial Models & Modeling Ch. 13 Part 2 Lecture 13B

  3. Types of Spatial Models • Cartographic Models (Automated Mapping Analysis & Processing) • Often applied to ranking areas in support of decision making. • Nominal or ordinal output • Uses processes such as overlay, buffers, reclassification etc. • Simple Spatial Models –focus on applying mathematical relationships • Subject of SIE 512 • Output is often interval or ratio • Spatio-Temporal Models (Process Models) Lecture 13B

  4. An Example of a Simple Cartographic Model Lecture 13B

  5. MulticriteriaEvaluation • Rankings – The assignment of relative values within a layer. • Weighting – the assignment of different values to each layer. Lecture 13B

  6. Weighted Overlay • Boolean operators are appropriate when each factor is equally important. • We can take relative importance into account by using weights. wi*pik where w is the weight assigned to each layer and p is 0 or 1 depending upon whether the factor was present or absent at a given location k. The weights should sum to 1. Lecture 13B

  7. Weighted Overlay • If each layer in the overlay operation itself consists of various types within the layer, then each type may have a different score according to its perceived importance within the layer. • Score each type on a score of 0 to 9 for suitability, and assign a weight to each score. Lecture 13B

  8. Assignment of Weights • The weights may reflect the preferences of the decision maker. • These may be based on some cost; money, time, etc. • Another approach – Saaty’s Analytical Hierarchy Process (AHP) which builds a matrix of pairwise comparisons between the factors. Lecture 13B

  9. The Analytical Hierarchy Process https://en.wikipedia.org/wiki/Analytic_hierarchy_process Lecture 13B

  10. Suitability Analysis Using Spatial Analyst Lecture 13B

  11. The Problem • The Wildcat Boat Company is planning to construct a small testing facility and office building to evaluate new designs. • They’ve narrowed the proposed site to a farming area near a large lake, and several small towns. The company now needs to select a specific site that meets the following requirements: • The site should not have trees to reduce the cost of clearing the land. The town does not allow the conversion of farmland, and other land used (urban, barren and wetlands are also out. That leave brush land. • The building must reside on soil suitable for construction. • A local ordinance designed to prevent rampant development allows new construction only within 300 meters of existing sewer lines. • Water quality legislation requires that no construction occur within 20 meters of streams. • The site must be at least 4,000 sq. m in size to provide space for building and grounds. Lecture 13B

  12. The original data are all vectors, but we can convert from vector to raster. Lecture 13B

  13. Since we are working with rasters, we need the Spatial Analyst Extnsion. Lecture 13B

  14. The Raster Environment The raster is a rectangle, and when you combine rasters, you want them to represent the same area, so we will set the output extent to and projection to one of the features. I’ll use the soils feature and round the values to the nearest tenth of a meter. They must also be the same cell size. Lecture 13B

  15. Set the Cell Size to 10.0 Lecture 13B

  16. Setting the General and Raster Environment Set the environment and scratch variables as usual, then set the Processing extent. Lecture 13B

  17. Converting Features to Rasters SUIT is suitability: 0,1, 2 or 3. Where 0 indicates “no data”. NOTE: This is NOT stored in the Geodatabase. Lecture 13B

  18. Geometry Lecture 13B

  19. Attribute Tables Feature Class Raster Lecture 13B

  20. Create another soils grid with a 5 m resolution. 5 m Resolution 10 m Resolution NOTE: The change in resolution produces a change in precision. Lecture 13B

  21. Since this is a small dataset, we are going to increase the resolution to 2 m. The resolution has gone from 10 m to 2 m (5 fold), thus increasing storage 52, or 25 fold. Lecture 13B

  22. Lecture 13B

  23. Landcover Code Lecture 13B

  24. Lecture 13B

  25. Lecture 13B

  26. Lecture 13B

  27. The process was repeated with streams, using stream code as the field. Lecture 13B

  28. And with roads, using road_code. Lecture 13B

  29. It is difficult to create a good buffer with Spatial Analyst. We will buffer the vector files and convert to rasters. Lecture 13B

  30. Sewer_Buff as a raster Lecture 13B

  31. The same was done with a 20 m buffer around the streams. Lecture 13B

  32. Reclassifying the Data Lecture 13B

  33. Change all values to 0 except 300 (brush). Lecture 13B

  34. Soils: 0 & 1 are unsuitable, change to 0, 2 and 3 change to 1. Lecture 13B

  35. Sewer_Buff becomes 1. Lecture 13B

  36. Stream_Buff: Replace value with no data, and nodata becomes 1. Lecture 13B

  37. Overlay using the Raster Calculator Lecture 13B

  38. Results Lecture 13B

  39. Adding Weights and Ranks to the Problem • We could have decided that the 300 meter sewer restriction could be avoided by constructing a septic system, which would be more costly. • We could favor the 300 m buffer by the cost factor, but the rest of the area would be acceptable. Instead of simply adding the layers in the raster calculator would could have weighed the layers differently: Sewer2+Stream2+(2*Landcover2)+(2.5*Soils2) Lecture 13B

  40. Modeling Human Processes • It is difficult to model humans spatial behavior. • How do people move through space when constrained by roads, buildings, fences, etc.? • How do people choose where to live, shop, vacation? Lecture 13B

  41. Spatial Interaction Models An abstract, idealized, representation of any and all kinds of spatial interaction phenomenon. It is the flow of products, people, services, or information among places, in response to localized supply and demand. These models describe the flows between a set of origin and destination zones on a map. These are commercial models outside of most GIS packages. Lecture 13B

  42. Three interdependent conditions are necessary for a spatial interaction to occur: • Complementarity. There must be a supply and a demand between the interacting locations; e.g., a store and its customers. • Intervening opportunity. There must not be another location that may offer a better alternative as a point of origin or as a point of destination. For instance, in order to have an interaction of a customer to a store, there must not be a closer store that offers a similar array of goods. • Transferability. Freight, persons or information being transferred must be supported by transport infrastructures, implying that the origin and the destination must be linked. Lecture 13B

  43. Lecture 13B

  44. Inputs and Outputs Beta Deterrence Parameter Destination Totals Origin Totals Interzonal Costs Spatial Interaction Model (an equation) Predicted Trips Lecture 13B

  45. Origin/Destination Matrix Lecture 13B

  46. The Relationship between Distance and Interaction The above figure portrays a classic non-linear relationship between distance and the level of interactions of location A with other locations (B, C and D). It assumes that each location has the same complementarity level and that no intervening opportunities are present. The closest location, B, has the highest level of interaction with location A, while locations C and D have lower levels of interaction since they are located further away. Lecture 13B

  47. Three Basic Interaction Models Lecture 13B

  48. Three Basic Interaction Models 1. Gravity model. The level of interaction between two locations is measured by multiplying their attributes, which is then pondered by their level of separation. Separation is often squared to reflect the growing friction of distance. On the above figure, two locations (i and j) have a respective "weight" (importance) of 35 and 20 and are at a distance (degree of separation) of 8. The resulting interaction is 10.9, which is reciprocal. Lecture 13B

  49. Three Basic Interaction Models 2. Potential model. The level of interaction between one location and all the others is measured by the summation of the attributes of each other location pondered by their level of separation (again squared to reflect the friction of distance). On the above figure, the potential interaction of location i (Ti) is measured by adding the ratio "weight" / squared distance for each other locations (j, k and l). The potential interaction is 3.8, which is not reciprocal. Lecture 13B

  50. Three Basic Interaction Models 3. Retail model. This model deals with boundaries, instead of interactions. It assumes that the market boundary between two locations is a function of their separation pondered by the ratio of their respective weights. If two locations have the same importance, their market boundary would be halfway between. On the above figure, the market boundary between locations i and j (Bij) is at a distance of 4.9 from i (and consequently at a distance of 2.1 from j). Lecture 13B

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