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Grid-based Map Analysis Techniques and Modeling Workshop Part 1 – Maps as Data Part 2– Surface Modeling Part 3 – Spatial Data Mining Part 4 – Spatial.

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Presentation on theme: "Grid-based Map Analysis Techniques and Modeling Workshop Part 1 – Maps as Data Part 2– Surface Modeling Part 3 – Spatial Data Mining Part 4 – Spatial."— Presentation transcript:

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2 Grid-based Map Analysis Techniques and Modeling Workshop Part 1 – Maps as Data Part 2– Surface Modeling Part 3 – Spatial Data Mining Part 4 – Spatial Analysis Part 5 – GIS Modeling Modeling structure Processing hierarchy and analysis levels Calibrating and weighting model criteria Simulating alternative scenarios and perspectives

3 Campground Suitability Model (Demo) …evaluate a GIS model for Campground Suitability with the following criteria—  Prefer gentle slopes  Prefer near roads  Prefer near water  Prefer good views of water  Prefer westerly aspect …can’t be too close to water or too steep (legal constraints) (Berry)

4 Communicating Model Logic (suitability) (Berry)

5 Decision Support Systems Framework (Berry) (See MapCalc Applications, “Identifying Campground Suitability” for more information)MapCalc Applications An Interactive Map links a map’s logic (flowchart) to its processing script (commands) and base data. A user can query the logic (click on boxes and maps) and modify calibrations/weights for alternate scenarios— What if …thinking with maps

6 Transmission Line Routing Model Criteria – the transmission line route should… Avoid areas of high housing density Avoid areas of high housing density Avoid areas that are far from roads Avoid areas that are far from roads Avoid areas within or near sensitive areas Avoid areas within or near sensitive areas Avoid areas of high visual exposure to houses Avoid areas of high visual exposure to housesHousesRoads Sensitive Areas Houses Elevation Goal – identify the best route for an electric transmission line that considers various criteria for minimizing adverse impacts. Existing Powerline ProposedSubstation (Berry)

7 Routing Model Flowchart (Model Logic—components) Model logic is captured in a flowchart where the boxes represent maps and lines identify processing steps leading to a spatial solution High Housing Density Far from Roads In or Near Sensitive Areas High Visual Exposure Avoid areas of… (Berry)

8 Step 1 Identify overall Discrete Preference (1-9 rating) Step 1 Step 2 Generate an Accumulated Preference surface from the starting location to everywhere Step 2 Step 3 Identify the Most Preferred Route from the end location Step 3 Routing Model Flowchart (Model Logic—maps) (Berry) Model logic is captured in a flowchart where the boxes represent maps and lines identify processing steps leading to a spatial solution

9 … identifies the relative preference of locating a transmission line at any location throughout a project area considering multiple criteria Step 1 Discrete Preference Map (Berry) AVOID Least Preferred Most ATTRACT …average of the four individual preference maps for overall preference at each cell EXCLUDE (0)

10 … identifies the preference to construct the preferred transmission line from a starting location to everywhere in a project area Step 2 Accumulated Preference Map Splash Algorithm – like tossing a stick into a pond with waves emanating out and accumulating costs as the wave front moves (Berry)

11 … the steepest downhill path over the accumulated preference surface identifies the most preferred route — minimizes areas to avoid Step 3 Most Preferred Route (Berry) PreferredRoute Preferred Route

12 Generating Optimal Path Corridors Pinch Point The alternative corridors are derived by considering the top 5 percent of the best routes within the project area …technique combines the Start and End preference surfaces to identify the overall preference for “forcing” routes off the optimal path (Berry)

13 Siting Model Flowchart (Calibrating and Weighting) Model logic is captured in a flowchart where the boxes represent maps and lines identify processing steps leading to a spatial solution Avoid areas of… High Housing Density Far from Roads In or Near Sensitive Areas High Visual Exposure RankingsWeights …but what is high housing density and how important is it? …etc? (Berry)

14 Calibrating Map Layers (Relative Preferences) Model calibration refers to establishing a consistent scale from 1 (most preferred) to 9 (least preferred) for rating each map layer 1 for 0 to 5 houses …group consensus is that low housing density is most preferred The Delphi Process is used to achieve consensus among group participants. It is a structured method involving iterative use of anonymous questionnaires and controlled feedback with statistical aggregation of group response. (See select Column Supplements, Beyond Mapping, September 03, Delphi) (Berry)

15 Weighting Map Layers (Relative Importance) Model weighting establishes the relative importance among map layers (model criteria) on a multiplicative scale The Analytical Hierarchy Process (AHP) establishes relative importance among by mathematically summarizing paired comparisons of map layers’ importance. HD * R * 3.23 SA * 1.00 VE * …group consensus is that housing density is very important (10.38 times more important than sensitive areas) (See select Column Supplements, Beyond Mapping, September 03, AHP) (Berry)

16 Generating Alternate Routes (changing weights) The model is run using three different sets of weights for the map layers— …to generate three alternative routes (draped over Elevation) (Berry)

17 Grid-based Map Analysis Techniques and Modeling Workshop Part 1 – Maps as Data Part 2– Surface Modeling Part 3 – Spatial Data Mining Part 4 – Spatial Analysis Part 5 – GIS Modeling

18 More on Spatial Analysis and Modeling Software Books Online (Berry)


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