To do this I would create a python script that steps through the polygons, creates a temporary midpoint circle or buffer (or whatever shape you would like) with a desired radius. Then use this temporary shape to select the grid squares underneath (use a copy/clone as you already are stepping through the same dataset). Then summarize the desired attribute/attributes on that particular selection and store them either in a new dataset or preferably as new columns in the original grid dataset. Both sums and averages could be stored (the nominator area for the average can either come from the circular shape or be calculated as a sum of areas of the selected grids) Then the script moves on to the next grid until all is stepped through. Which selection type you use for selecting the grids must of course be desided (either "completely inside" or just plain intersect). The summarized values stored as the result for each grid must be thoroughly explained as they have really nothing to do with the original grid size except that the grid size, is the one used as the "moving steps" for the analysis. I'm not a python programmer myself so I can't help you with any actual coding. /Daniel Skickat från min Samsung-enhet
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