Most overlay problems are complex and it is recommended that you break them down into submodels for clarity, to organize your thoughts, and to more effectively solve the overlay problem.įor example, a suitability model for identifying the best location for a ski resort can be broken into a series of submodels that should help the ski area be profitable. All factors that are identified in the model should help the ski area be profitable. In the problem definition, specific measures should be established to identify the success of the outcome from the model.įor example, when identifying the best location for a ski resort, the overall goal may be to make money. Not only is it important to identify what the problem is, a clear understanding needs to be developed to define when the problem is solved, or when the phenomenon is satisfied. However, a clear definition of each component and how they interact must be established. Some of the components may be complementary and others competitive. The components relating to the objective must be defined. All aspects of the remaining steps of the overlay modeling process must contribute to this overall objective. The overall objective must be identified. Define the problemĭefining the problem is one of the most difficult aspects of the modeling process. Steps 1 through 3 are common steps for nearly all spatial problem solving and are particularly important in overlay analysis. Reclassify or transform the data within a layer.The following lists the general steps to perform overlay analysis: Some values in a particular raster may be ideal for your purposes (for example, slopes of 0 to 5 degrees), while others may be good, others bad, and still others unacceptable. How much more important is for you to decide.Įven within a single raster, you must prioritize values.
It may be that the cost of land is more important in choosing a site than the distance to utility lines.
You cannot add a raster of land cost (dollars) to a raster of distance to utilities (meters) and obtain a meaningful result.Īdditionally, the factors in your analysis may not be equally important. This information exists in different rasters with different value scales: dollars, distances, degrees, and so on. For instance, choosing the site for a new housing development means assessing such things as land cost, proximity to existing services, slope, and flood frequency. Overlay analysis often requires the analysis of many different factors.
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