Dear all,
I have datasets associated with different polygon feature classes (as attributes) that I have to "project" onto other polygon feature classes. An example of such polygon FCs is attached, with a grid and countries. I am currently using the following algorithm that is working moderately well; I am assuming the data to be an attribute of the grid, but it should work both ways.
For intensive data:
1. Convert grid to "high resolution" raster using the attribute as the value. As raster pixels are known by their centers, I use a high enough resolution, so I am ensured that a significant amount of pixels/centers are present in each polygon of the destination FC (countries in this case).
2. Perform a Zonal Stat. to obtain MEAN values per destination polygon (country).
For extensive data:
1. Compute source polygons surface areas, and then a surface density (intensive) of the data for each polygon.
2. Process the densities as above for intensive data.
3. Compute destination polygons surface areas and multiply by MEANs obtained in 2. for going back to the original extensive data.
Is there a better or more direct way to do it?
Thank you and best regards,
Cedric
