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How can I read grid data (3 or 5 sources of grids) like slope, soil, cover, etc?

My goal is to build a simulator based on multiple grid data for harvesting decisions.

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RasterToNumPyArray takes an input raster and returns you a numpy array that you could then work with.

myArray = arcpy.RasterToNumPyArray(out_curved_elev_raster)
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Given a set of point features, you can extract multiple raster datasets using ExtractMultiValuesToPoints:

Extracts cell values at locations specified in a point feature class from one or more rasters, and records the values to the attribute table of the point feature class.

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Could you explain why point features might be relevant to a grid-based calculation? – whuber Nov 17 '11 at 16:38
Lately I've done a lot of reading of grid values at specific locations (model nodes) to extract geologic data to build the geometry for groundwater models. I guess my initial read of the post was that the OP was trying to accomplish something similar. – Jason Nov 17 '11 at 16:42
Thank you for the clarification: now the potential relevance of your reply is evident (+1 for offering a different approach). (Modeling harvests, though, is not usually done with finite element, adaptive gridding, or analytical methods, unlike groundwater models. It usually comes down to operations on entire regular grids of squares, which are almost always best left in a logical grid format.) – whuber Nov 17 '11 at 16:46
Like I've always said, you learn something new about harvest modeling every day ;) – Jason Nov 17 '11 at 16:50

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