Module 1, Part 1: Suitability Analysis
The purpose of this lab was to create a suitability model for a developer. The analysis included provided suitability ratings for land cover, soils, slopes, proximity to streams and proximity to roads. The flow chart of the analysis work flow is below:
I began by using the Reclassify tool to reclassify the landcover raster. I used the Euclidean Distance tool on the rivers and roads shapefiles, individually, and then reclassified each raster output using the Reclassify tool. I used the Slope tool on the elevation raster to convert the raster elevations to slope and then reclassified the output raster using the Reclassify tool. I converted the soils shapefile to a raster with the Polygon to Raster tool and reclassified the output raster using the Reclassify tool.
To create the final suitability model I added all the reclassified rasters to the Weighted Overlay tool and ran two analyses. The first analysis gave each variable the same weight, 20%. The second analysis used unequal weights for the variables as follows: slope 40%, land cover and soils 20% each and distance to streams and roads 10% each. The final suitability model for each result shows suitability ratings from 2 to 5, with the lower values being less suitable for development. Below is a comparison of the results of both analyses:
The results show a distinct difference in suitable areas for development, depending on the weight of the variable. In the unequal weights analysis, areas near the river are clearly more suitable for development (dark green), whereas in the equal weights analysis there are only a few areas near the river meeting all criteria and more suitable for development. This makes sense given that the areas near the river most likely have lower slopes, which is weighed heavier in the unequal weights analysis.
Given the results and experience in this lab, suitability analysis is a valuable tool for solving a variety of problems with many variable inputs.
I began by using the Reclassify tool to reclassify the landcover raster. I used the Euclidean Distance tool on the rivers and roads shapefiles, individually, and then reclassified each raster output using the Reclassify tool. I used the Slope tool on the elevation raster to convert the raster elevations to slope and then reclassified the output raster using the Reclassify tool. I converted the soils shapefile to a raster with the Polygon to Raster tool and reclassified the output raster using the Reclassify tool.
To create the final suitability model I added all the reclassified rasters to the Weighted Overlay tool and ran two analyses. The first analysis gave each variable the same weight, 20%. The second analysis used unequal weights for the variables as follows: slope 40%, land cover and soils 20% each and distance to streams and roads 10% each. The final suitability model for each result shows suitability ratings from 2 to 5, with the lower values being less suitable for development. Below is a comparison of the results of both analyses:
The results show a distinct difference in suitable areas for development, depending on the weight of the variable. In the unequal weights analysis, areas near the river are clearly more suitable for development (dark green), whereas in the equal weights analysis there are only a few areas near the river meeting all criteria and more suitable for development. This makes sense given that the areas near the river most likely have lower slopes, which is weighed heavier in the unequal weights analysis.
Given the results and experience in this lab, suitability analysis is a valuable tool for solving a variety of problems with many variable inputs.
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