I have a set (A) of geospatial raster data layers and a set (B) of point data. (B) includes numerical values that indicate the "suitability" of the specific site with a rising value. I know that (B) depends at least partly on geospatial information covered in (A).
Now my idea is to train an algorithm with my point data of (B) to find the patterns in (A) that contribute to the known suitability and then calculate for me in the areas which are not covered by point data a probability/possibility of suitability.
I thought either of a supervised neural network toolbox or fuzzy logic script to be applied in a GIS environment to do the operation.
Has anybody got an idea with which GIS-tool (either QGIS or ArcGIS) one could execute the analysis successfully and derive meaningful results?