I've created an average kernel density map by running KDEs on points stacked within the same spatial extent. For example, say we have three point shapefiles representing seedlings in three different forest gaps of the same shape and size. I ran a KDE for each point shapefile. The output from the KDE were then stacked based on spatial extent in order to calculate the average in Arc's raster calculator, for example: Float(("KDE1"+"KDE2"+"KDE3")/3). Here is the final product:
Now I'm interested in creating a map depicting the error associated with the averaged KDEs. I hope to use the error map to visually depict how much error is associated with the hotspots (e.g. is the SW hotspot due entirely to the points in one gap?). How should I go about creating a map of the error associated with the averaged KDEs? Would MSE be the most appropriate measure of error in this case?
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Now I'm interested in creating a map depicting the error associated with the averaged KDEs. I hope to use the error map to visually depict how much error is associated with the hotspots (e.g. is the SW hotspot due entirely to the points in one gap?). How should I go about creating a map of the error associated with the averaged KDEs? Would MSE be the most appropriate measure of error in this case?
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