Hi,
I am trying to produce scenarios of past land cover, before hydropower
reservoirs were built. To do so, I need to fill empty pixels from a raster in
the locations where the reservoirs are currently present, using as input the
actual land cover map. I tried doing that with r.neighbors (taking method=mode)
with neighborhoods of increasing size, to replace null pixels with the most
common land cover class in the neighborhood. I also tried that with
r.fill.stats which is basically the same thing.However, the results gets very
homogeneous, since the interpolated null cells always get the value of the most
common land cover class.
Do anyway know of a method in GRASS to perform a "probabilistic" neirighborhood
analysis, where cells in a neighborhood are given weights (possibly related to
the distance to the central cell and to their frequency) and these weights are
used to stocastically sample a value to fill the central cell?If not in GRASS,
does anyway know of such a method in a different platform, i.e. R?
Thanks!BestBernardo
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