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So i managed to solve the "problem" using cql. I am using a leaflet script, and by adding cql_filter: 'begin AFTER ' + begin + 'T00:00:00 AND end BEFORE ' + end + 'T00:00:00' to the getMap-Request, with begin and end containing the start and end of the period i am interested in (formatted like YYYY-MM-DD), i can now query exactly what i wanted before.


You could put more than one geometry onto each other. Then you can have your full set of rows with your history. And in case of the same geometry but different usage you have two times the same geometry "above" each other. That should be like a relate.


I'd say importing SA functions, setting workspace to fastest media possible using TableToNumpyArray might help as well: from import * from arcpy import env env.workspace='in_memory' If in_memory doesn't work set it to folder (not FGDB) on fastest disk. This is where ArcGIS stores temp rasters RasterInt=Int(raster) numberOfCells ...


I second that NumPy is fast for calculations on rasters (although converting back to a raster file can seemingly take a long time for the few times I've used it). You could also calculate your area using the Raster properties. Something like this without the need of Int_3d: Edited to correct calculation area = (my_raster.width * my_raster.height) * ...


The following might be more of a set of a partial suggestions for your situation rather than a direct and complete answer, but have you considered performing the arcpy.Int_3d() , numberOfCells and area work using numpy arrays? I've tested the function below on some small (6k x 2.5k pixels) single-band rasters and I hope it will reduce your running time. I ...


Yes, this can be done in ArcGIS. The following is the link to the top of the graph section on online ArcGIS 10.2 help. If you are using a different version of ArcGIS, you can simply replace the 10.2 in the URL with your version (that usually works).

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