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Apart from “in-memory” space and physical geodatabase, is there any other method to process raster data?

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Using the centroid of the building footprints (tagged residential), I want a count of hydrants within 135m, and a count of hydrants within 270m of every residential footprint. This would be based on a defined exclusion zone (Private Property, Railway reserve etc), or the inverse.

To calculate the least cost distance from a footprint to a hydrant, the raster maps are used as the intermediate data. I can use either a physical geodatabase or the in-memory space to carry the process. With a physical geodatabase, the process will take a long time to run. Though the in-memory space makes the process running fast but is causing data missing.

Therefore I am looking for a workspace/method to make the raster process fast and reliable.

I’m using ArcGIS 10.2.2 for Desktop and Python 2.7.


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