I've been trying to figure out a way to pre-process a single-band thematic raster dataset (e.g., land cover) to produce a multi-band raster of proportional cover.
For example, consider a land cover dataset with two land cover types: water and land.
What I would like is to calculate for each cell the proportional coverage by a given land cover type within some distance from the center of that cell.
The final product would be a 2-band raster where band 1 is proportional cover by water, and band 2 is proportional cover by land.
You can conceptualize this as a raster representing the output of a moving window exercise.
The window is a buffer of a given radius, and the centroid of the buffer is the center of the target cell.
The target cell is assigned the proportional cover by the land cover type, then the window moves to the next cell and repeats the process.
The full process would calculate a raster band for each land cover type in the dataset.
I've yet to figure out an efficient workflow for this; my solutions have all involved iteration (for loops) in R, which takes an absolute eternity for large raster datasets.
Is there a more efficient approach, preferably using ArcGIS or R?