Suitability Overlay analyses the relative importance of various data to identify areas that produce the most positive result. For example, analysing data in a project to identify the best location for a school or the most likely location for a forest fire.
To perform the analysis, you must build a project containing layers of data that you want to use in the calculation. Each layer should contain one type of data representing a factor in the calculation. For example, if you are trying to determine the best location for a winery, your project could contain a layer with rainfall levels for an area, a layer of soil types found in the area, a layer containing the road network, and so on.
To calculate a combination that produces the best result, you must decide on a scale to rank the importance the layers and a scale to rank the data in the layers. The scales measure the relative importance of each input into the equation; the most important factors affect the results the most. The value from the scale that you assign to the layer and to the data is called a weight.
For example, you have a scale of 1 to 100 for the layers. Because the soil type layer is more important than the road network layer, you can assign a weight of 75 to the soil type layer and a weight of 25 to the road network layer; the soil type layer is three times more influential in the calculation than the road network layer.
You do not need to use the same scale for the layers and the data in the layers, but you should use one scale for the layers themselves and one scale for the data in the layers. Weighting the data in one layer according to a vastly different scale from the data in the other layers can skew the results.
To add weights to data, add a field in the Attribute Manager for each layer and enter the numeric value expressing the weight for the data in each record. A negative weight for a record will force an unfavorable result in the output for that record.
For example, you have a scale of 1 to 10 for the data in the layers. In the soil type layer, you assign the well-drained soils an 8, the poor and shallow soils a 2, and the polluted soils a -1. Any sites containing polluted soils will automatically receive a negative result.
You must also assign a weight to the 'No Data' value in the layers. The 'No Data' value represents the null values or the pixels without data. The 'No Data' value is usually set in the metadata of the layer so it may not appear in the Attribute Manager. When you assign a weight to the 'No Data' value in step 7, you should use the same scale as the rest of the data in the layers.
When setting up a Suitability Overlay, you must determine the weight of each layer, the weight of the NoData value, and select the field that contains the weights for the data in each layer. The result is displayed in a layer indicating the most positive correlation between all the factors in the equation.
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