This week we worked on least-cost path and corridor analysis. For the first portion, we looked at a few different least-cost paths for a pipeline by creating cost surfaces for slope and proximity to rivers. We created three different scenarios by changing the cost of being close to rivers. For the first path, we only looked at a slope, which was reclassified so that the lowest cost was for low slopes (<2°) and highest for steep slopes (>30°). A cost surface raster was created, followed by a cost distance raster, with accumulative costs as you move away from the source. The source is at the top of the image, indicated in light blue, and the destination is represented with a dark blue asterisk. With this analysis, there are 4 river crossings, which were determined using the Intersect tool. A backlink raster was also created, so that a least-cost could be created using the Cost Path tool.
Figure 2. Scenario 1, showing least-cost path with slope as the cost surface. |
For the second scenario, we created a cost surface with a high cost for rivers, which resulted in fewer pipeline intersections. In order to combine the two cost surfaces, the Raster Calculator was used. For the third scenario, we used a high cost for rivers, and a slightly lower cost for the area close to a river (within 500 m). We again had two intersections, but they were at different areas. The following image compares the two:
Additionally, we created a corridor for the same pipeline. Some layers could be reused, but we had to perform cost distance again, this time with the destination as a "source" since the Corridor tool requires two source inputs. After using the Corridor tool to create a range of possible paths, symbology was adjusted to represent 105, 110 and 115% of the minimum value. My image is slightly off from the example in the lab, I believe that this is due to differences in rounding when calculating the path values. I tried several different sets of numbers, to no avail. The following image is the result:
Corridor analysis was then performed, using both fragments of the national forest as sources. The same values were used in order to determine a suitable corridor (105, 110, 115% minimum value). All values above 115% were reclassified as NoData in order to create a raster with only the corridor and source areas. A final map was created in order to showcase the results:
Figure 5. Final output map for the black bear corridor. Map shows corridor areas ranked by suitability (1-3). |
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