Decision Making: Suitability Determination - Completely GIS, GPS, and Remote Sensing Tutorial -
Decision Making: Suitability Determination

We embark now to further explore what GIS does, how it works, what software systems are available, and what typical end products and applications look like. Before moving on, you may wish to gain further insights into GIS by visiting sites on the Internet. One way is to work through some of the entries found through a Web Search Engine. We have picked out a few of the better ones whose links are given here. Geographers at the U.S. Geological Survey prepared a site which they call the GIS Poster page. Another useful summary is found at the GIS Development site. The leading U.S. software providers are Leica Geosystems and ESRI, which also offers training courses.

Perhaps the best way to appreciate the power of GIS, even before examining the design and function of the data handling system, is to introduce a typical case study * and the thinking behind the steps in a site-suitability analysis. The following diagram summarizes the rationale behind such an analysis:

Site Suitability Analysis diagram.

Suppose that three factors or variables, among the attributes that describe a geographic area under consideration, are essential in determining best sites for, say, a land development venture: Vegetation, Topography, and Soils. A data element on a map represents each variable. In this case each map shows the characteristics and distribution of the members or classes within the element theme, e.g., different types of soils and their properties.

The most obvious manipulation performed on each map was to assign numbers to parts of the map that are the weighted estimates of suitability, ranging from 0 (least suitable) to N (highest number for most suitable).

We usually designate one map, often a cartographic map, as the base, over which we lay the others, (each then constitutes a data layer) either manually or digitally. Now, some soils, vegetation cover types, and elevations are more favorable than others in specifying their role in the site-selection process. Thus, for a certain intended use, we prefer high areas over low areas. So, we assign relative heights numerical ratings, say from 1 to 5. We can mark soils with optimum drainage by higher numbers in a scale of 1 to 8. We then subdivide a data element map into cells in a grid. We assign each cell a value based on its thematic rating. We can incorporate other kinds of data, e.g., tables representing some condition in the cells, provided there is some spatial connection. When we combine the maps sharing the same cells, each comprising a data layer, the values sum for each cell (ranging from lowest numbers = worst suited to highest = best suited). In a modern GIS, we do this digitally. The outcome is a map, in which we judge areas with the highest resultant scores the most favorably suited.