GIS 5100 Module 6 - Part I: Suitability Mapping

Module 6 of Applications in GIS was very extensive and loaded with information; the Module was divided into two parts, with two scenarios for each part. This first portion of the module focused on Suitability Mapping; a suitability map identifies areas [within a study area] that meet some, or all, criteria for a given problem. For example, in the map below, regions within the study area are highlighted that are optimal for cougars to live in; these areas were determined by meeting four criteria: distance from roadways, proximity to rivers, areas with increased slope [mountainous or canyon], and forested areas. To determine which areas meet all [or none] of these criteria, a reclassification process had to be run on the provided datasets. For instance, the Digital Elevation Model was processed using the Slope Calculator function and reclassified into two distinct classes: areas with < 9° slope and areas with > 9° slope. Next, a reclassification was employed on the landcover dataset, distinguishing forested areas from every other landcover type. The same process was completed for proximity to roadways and rivers [a Euclidian Distance raster dataset was created prior to the reclassification process.]

After all datasets had been reclassified, the values for each cell could be added together using the Raster Calculator too, and the analysis could begin. Referencing the map above, three variations on the analysis are displayed. The two bottom maps illustrate regions within the study area that meet ALL four requirements, thus being determined as the likeliest places for cougars to dwell; the only difference between the two bottom maps is one is vector-based [comprised of polygonal geometries], while the bottom-right is raster-based [a grid array of pixel values]. The top map, however, displays the study area using a graduated symbology; this tells the map viewer how many criteria are met for the entire study area. A visual comparison of the top map with the bottom two clearly illustrates all three maps highlight the same optimal areas for a cougar to live.

The second scenario of Part 1 was a similar analysis, only determining which areas within the study area would be best for a future development. The criteria used in this analysis were: proximity to roadways, proximity to water, current land classification / land use, and the slope of the land. While there were some variations within the criteria, and what was determined to be optimal for development, the workflow for Scenario 2 was the same. As displayed in the map below, a graduated symbology was utilized to show how many criteria were met for each pixel within the study area.

The difference between the two maps in Scenario 2 is weighted value. The map on the left gives an equal weighted value for each criterion, while the map on the right does not. This is significant because some factors are going to affect the suitability of potential sites more than others. For instance, while proximity to water will have some effect on the location of a future development, it will not be the same effect as not having any available roadways to access the potential site. 

As outlined in this post, the applications of Suitability Mapping are endless, and can be used in a wide variety of ways. Although this lab was very time-consuming and covered a tremendous wealth of information, it was a great experience continuing to learn about the potential applications of Geographic Information Systems.