Lab 2 - Least-Cost Path and Corridor Analysis

In this week’s lab, we learned about least cost path analysis and corridor analysis using cost surfaces. The first part of the lab was an exercise in which we learned to create least-cost path analyses, using different weights on set criteria to determine the optimal path for a new pipeline. Then we were to perform a corridor analysis showing the potential movement of black bears between the two sections of Coronado National Forest, and to create a map of the latter corridor analysis.

In the first part, we were to create several least-cost path analyses using different settings. Our first criteria involved using the Slope tool on an elevation layer and reclassifying it, which we learned last week. We created cost distance and backlink rasters, both of which are needed to perform the least-cost analysis. In the second scenario, we added river crossings as an additional factor. Once the data was reclassified, we used the Raster Calculator to add the criteria together, and used this new cost surface to create a least-cost analysis. The third scenario expanded to cost to within a certain distance of a river, and we created a third least-cost analysis. To this point, we only created cost distances from the source; to create a corridor, we needed to create a cost distance from the destination as well, and use the Corridor tool to calculate an optimum corridor.

The second part of the lab was another corridor analysis. This time we were to show the potential movement of black bears between two sections of Coronado National Forest. I live not far up the road, so I know the geography, which was beneficial, as I could get a “feel” for the geographic region I was working with. The three criteria for the habitat corridor were the distance from roads, the elevation, and the type of land cover. We wanted our corridor to be a reasonable distance away from roads, black bears prefer mid-elevation areas, and they prefer specific types of forest and vegetation. I created a suitability model using those 3 criteria in a weighted overlay, the result of which was inverted to show that higher suitability describes lower travel cost. To obtain a meaningful corridor, I read the provided literature and tried a couple of different classifications to find a good threshold value. The map below shows three possible optimum corridors black bears could use to travel between the two sections of the Coronado National Forest.

Knowing a lot about the geography of the general area and where it’s sparsely populated also allowed me to find my corridor on a map and see that these do seem to be the optimum corridors based on the criteria. One note is that there were a lot of files created during the course of this lab, so I tried to make sure the names were as descriptive as possible to not get confused. This was sometimes difficult as we are often only allowed 13 characters for the file name lengths, but that usually wasn’t too bad. I had some trouble with the weighted overlay, and it took some time to find that it was weighting my classifications incorrectly, but troubleshooting problems is another way of learning. I really enjoyed learning about corridor analysis and I hope to get more practice using these techniques in the future.