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The approach I ended up using is the following: I buffer the forest stands, which are represented as centroids (green dots) in the image above. I create a fishnet grid over the entire area of interest. I determine for each fishnet grid cell, how many timber stands are within that grid cell. I determine the grid cell with the highest number of stands ...


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the input of cost distance should be a raster or a feature layer. You should create a feature layer using your feature class and your where clause, and use this layer as input in Cost distance. See the help on makeFeatureLayer here in you example, the SQL statement should look like this (for shapefiles and file gdb) : sql = '"' + fieldname + """" = '""" + ...



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