Site Suitability Analysis
Let's look at an example.
The Tim Hortons Foundation is looking for an ideal educational location where K-12 students can visit and conduct research to learn more about environmental sustainability. Research shows that children are more likely to be environmentally aware if they have exposure to these types of experiences at a young age. In determining the ideal location, the Tim Hortons Foundation would like to build on a lot that is close to water and that is near forest for water sampling/testing and tree-species identification.
You can obtain raster data (i.e., data composed of equally spaced and sized cells) containing land-cover information and assign all cells that have water a value of “1” and all cells that do not contain water a value of “0”. For the forest raster data, you would assign all cells that have forest present a value of “1” and all cells that do not contain forest a value of “0”.
When we overlay (i.e., combine the two layers together), we can determine which cells meet the two criteria that have been identified. There are two ways to combine the layers: multiplication and addition (see figure below). In the multiplication example, you obtain a final grid with values of either 0 or 1, where 1 indicates both criteria were met.
In comparison, the addition example results in values of 0, 1, or 2. In this method, a gradient of choices is provided. Although 2 is the most ideal choice, 1 is an alternative choice, and 0 represents an unacceptable location.
