If the Weighted Overlay tool was used for suitability modeling (to locate suitable areas), higher values generally indicate that a location is more suitable. The output rasters can be weighted by importance and added to produce an output raster. The cells in the raster will already be set according to suitability or preference, risk, or some similarly unifying scale. With the correct evaluation scale chosen, add the raster to Weighted Overlay. You can either leave the value assigned to each range (but note the range of values to which the new value corresponds) and assign weights to the cell values in the Weighted Overlay tool later, or you can assign weights at the time of reclassifying. The Reclassify tool allows for such rasters to be reclassified. Each range must be assigned a single value before it can be used in the Weighted Overlay tool. Generally, the values of continuous rasters are grouped into ranges, such as for slope, or Euclidean distance outputs. Continuous (floating-point) rasters must be reclassified to integer before they can be used. The tool only accepts integer rasters as input, such as a raster of land use or soil types. Adds the resulting cell values together to produce the output raster.Multiplies the cell values of each input raster by the raster's weight of importance.Reclassifies values in the input rasters into a common evaluation scale of suitability or preference, risk, or some similarly unifying scale.The Weighted Overlay tool lets you implement several of the steps in the general overlay analysis process within a single tool. Once the model is validated, a site is selected and the house is built. The final step of the overlay analysis process is to validate the model to make sure that what the model indicates is at a site is actually there. For example, in the housing suitability model, aspect is multiplied by 2 and the three criteria are added together, or represented another way, (2 * aspect) + slope + distance to roads. The input criteria are multiplied by the weights and then added together. Therefore, you may weight the aspect values as twice as important as the slope and distance to roads criteria. For instance, in our sample housing suitability model, you might decide that because of long-term conservation purposes, the better aspects are more important than the short-term costs associated with the slope and distance to roads criteria. You can weight the important criteria more than the other criteria. A location assigned a suitability of 5 on the reclassed slope layer will have the same cost as a 5 assigned on the reclassed distance to roads layer.Įach of the criteria in the weighted overlay analysis may not be equal in importance. A location assigned a suitability value of 5 on the reclassed slope layer will be twice as costly to build on as a slope assigned a value of 10. The locations closer to the roads are more favorable since they are less costly to build on, because they have easier access to power and require shorter driveways. The same reclassification process is applied to the distance to roads criterion. You do the same reclassification process to the 1-to-10 scale for aspect, with the more favorable aspects-in this case, the more southerly-being assigned the higher values. As the slopes become steeper, they are assigned decreasing values, with the steepest slopes being assigned a 1. The slopes are reclassed on a scale of 1 to 10, with the flatter being less costly therefore, they are the most favorable and are assigned the higher values. In a simple housing suitability model, you may have three input criteria: slope, aspect, and distance to roads. For example, if a location for one criterion is assigned a preference of 5, it will have the same influence on the phenomenon as a 5 in a second criterion. The preference values should not only be assigned relative to each other within the layer but also have the same meaning between the layers. That is, a preference value of 10 is twice as preferred as a preference value of 5. The preference values are on a relative scale. An assigned preference on the common scale implies the phenomenon's preference for the criterion. Since the input criteria layers will be in different numbering systems with different ranges, to combine them in a single analysis, each cell for each criterion must be reclassified into a common preference scale such as 1 to 10, with 10 being the most favorable. In a weighted overlay analysis, each of the general overlay analysis steps is followed.Īs with all overlay analysis, in weighted overlay analysis, you must define the problem, break the model into submodels, and identify the input layers. The Weighted Overlay tool applies one of the most used approaches for overlay analysis to solve multicriteria problems such as site selection and suitability models. Using Restricted and NoData for the scale value.
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