I want to perform an
Inverse distance weighted (IDW) interpolation to a series of points. However my data set can be
binary and just like the
IDW I want to interpolate the new values (categorical or binary) based on the highest frequency of closest points values surrounding the prediction location:
A if the majority of the closest points are A
C if the majority of the closest points are C
In addition I want to avoid using close points that are behind a barrier, that can be a wall or just an elevation.
This is how the problem/dataset looks like:
The grey points is the point I want to interpolate and the points behind the barriers can't be used in the process. The output of the interpolation process would be A or B, in this case probably A, since the closest points are all A.
What I am looking for is some kind of work-flow that would allow me to do this in ArcGIS, if possible I would prefer R (if anyone has any experience in doing this kind of processes in R). This is just the example how my problem looks like, I still have to implement it to a bigger extent and to many layers of points. Bear in mind that I have little experience with interpolation and that this might be a easy/dumb question. Any help/guidelines are deeply appreciated.