Raster Data and Site Selection
When you need to select a site based on certain requirements, what are the best tools to use for this? There are several ways to approach such problems, and with the "Using Raster Data for Site Selection" module from ESRI, working examples are provided. Here are definitions regarding suitability methods:
Binary suitability - When something is or is not suitable; no gray areas.
Fuzzy membership - This is determined by a value between 0 and 1, and the close to one, the more appropriate the result.
Reclassification - replacing old raster values with new ones to achieve a new classification.
Weighted Suitability - A number calculated that determines the best site based on weighted values.
Given specific requirements for a vineyard, how can we find the best site based on distance from the freeway, slope and sun exposure? Using the raster data we first need to use a spatial analyst tool that calculates slope from the elevation of the raster. From this we will know slope and rise. For calculating distance we use the euclidean distance tool. When you have all of the values, you then need to reclassify them and then assign a weighted value to them.
After values are reclassified and weighted, we have ideal locations for the vineyard.
Maps showing weighted site selections and suitable site selections.
Map of weighted values Ideal location sites in Green
Application and Reflection
This is certainly one of the most useful analyses in determining site selection. There are many uses for site suitability. Corporations use it to find the best sites to locate a new business. It's used in wildlife management and city service
You want to find a good place to observe the Eastern Screech Owl in eastern North Carolina. You know there have been sightings in Dare County. You are given a map of the Alligator River National Wildlife Refuge and told to find the best location based on pine tree stands that are located near fields.
Raster image of ARNWR, shapefile of Dare County.
The raster image needs to first have the land cover classes identified. The output from this will be used to extract raster attributes of evergreen and empty field land cover types. Since the best location to see the Eastern Screech owl is in a stand of pines near fields, so there will be three classes created with the following values: Pine stands near fields (1), Pine stands (2) and Fields (3). A weighted value favoring Pine stands near fields will be given highest percentage.
ESRI Training Certificate for Using Raster Data for Site Selection
One of the problems in this ESRI module was determining the best place to locate a new vineyard based on aspect, slope and distance to the freeway. This module teaches what tools to use to to extract those requirements from the data and them also which tools to use to select the proper location based on a weighted overlay, or in other cases binary site selection or fuzzy logic.
Final image showing ideal vineyard locations in green.