I have a large approximately circular study area comprised of 5000+ polygons which represent forest parcels. For each of these polygons I have up to 4 different species. These species occur in an approximately random distribution (not much clumping of like species in tropical forests) E.g. one polygon may have 40% cover of Species 3 and 60% cover of species 4. For the purposes of creating an input for a separate computer model I need to create a raster that represents the unique distribution of tree canopy within each polygon. Each 10 X 10 meter cell will represent the canopy of one species. I can do this by assigning a random distribution of numbers between 0 and 1 to each polygon, and then reclassing the cells in each polygon to represent the percent cover of each species. e.g. if the cover of a given polygon is 40% species 3 and 60% species 4, then I would reclass 0-0.4 to be ‘3’ and 0.40001 to 1 to be ‘4’. My problem is that I can’t figure out how to do this on a large scale, other than manually (which would be impractical). Is there a way to do it with model builder or with python or by some other means?
أكثر...
أكثر...