Applications in GIS - M6 Corridor Analysis

 

Final corridor analysis map from this lab determined with several habitat inputs.

In this lab students were asked to take on the role of park rangers and determine the corridors likely to be utilized by black bears moving between two sections of the Coronado National Forest. We were provided with layers for landcover and elevation, as well as shapefiles of the roads and forest boundaries. 

For my analysis I first checked that all raster datasets were in meters, then used the Euclidean Distance tool to convert the roads shapefile to a raster where cell values were distance to the road. From here I had three comparable rasters for analysis. 

I used the Reclassify tool on the roads, elevation, and landcover rasters to convert their values to ranks from 1-10 on how attractive the cell would be to black bears. Cells close to roads were ranked low, while in landcover any cell values that indicated forest and vegetation ranked high and human development ranked low. Since the assignment indicated black bears prefer mid-elevations, elevation values between 1200 and 2000 meters were ranked high and elevation values below and far above that ranked lower. 

With these three rasters all reclassified, I could now combine them with the Weighted Overlay tool. This tool combines raster values based on an optional weighting, and in this case landcover was weighted higher than elevation and road proximity. The resulting raster had cells containing values 1 to 9, with 1 being least suitable bear habitat and values closer to 10 being most suitable bear habitat.

Suitability raster, green values are those more suitable for black bears.

Unfortunately the Corridor tool uses a cost surface, not a suitability surface, so the sutability raster had to be "inverted" to a cost raster, using the Minus tool. By subtracting the raster from 10, all low ranking places became high cost cells, and previously suitable cells now displayed as low cost. 

Cost raster, inverted from the suitability rankings, darker red areas are higher cost, the forest shapefiles are drawn in light green. 

To conduct a corridor analysis between the two forest areas, I used the Cost Distance tool with this new cost surface raster, once with the northern Coronado section as the source, and once with the southern Coronado section as the source. This resulted in two rasters that displayed the cost over distance emanating from each forest section. Backlink was not important for this corridor analysis, so it was not included. I combined both of these cost distance rasters into one by running the Corridor tool, which automatically determines the least-cost corridor based on two cost rasters. 

Corridor raster displaying the least-cost corridors between the two forest shapefiles.

I explored the corridor raster and found the minimum cost value, then multiplied that value by 1.03, 1.05, and 1.10 and compared results before finally selecting the 5% corridor as my final wildlife corridor. This seemed the best balance between connectivity and space allocation, and I adjusted the symbology accordingly.