Ok I will admit that I had a bit of fun with this lab. Like the previous lab it has lots of moving parts, so lots of places things might go wrong.
The intention of Scenario 2 is to leverage different data to determine suitability. The narrative for this particular part was to use GIS to identify the habitat where a conservation group would be most likely to "encounter" mountain lions to collar. The suitability criteria is:
- Slopes greater than 9 degrees
- Covered by forest
- Within 2,500 feet of a river
- More than 2,500 feet from highways
The data provide for this lab was a mix of vector and raster data and unlike a previous part the goal was to convert everything to raster but boolean raster to isolate the areas most suitable.
Largely other than the tools to convert vector data to raster, the lab leveraged the Reclassify. This tool is primarily used to change the value of the raster to another value, for example a single band image with a cell value of 5 might be reclassified to a value of 1 and values of 1 - 4 as 0 to effectively output a raster of 0 and 1 values (a.k.a. Boolean). Once this process was completed it was a simple matter of using the Raster Calculator and performing some bitwise operations. Well, Esri calls it Boolean Algebra or Boolean Math but its just good old low level binary math.
The next using much of the same data was to discover ares suitable for development based on a provide criteria. This exercise encompassed most of the lessons learn in the previous scenario but evolved generating the final results using the Weighted Overlay tool to rank certain condition more or less than others. Below is a mediocre which I create showing the outcome of that lab.
Yeah! mediocre!
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