Hello Bernardo, although a solution with r.mapcalc random could be made to work, I'd say creating a new dedicated module is the way to go. Just an idea – create neighbour count raster (how many cells with centre class are in a sliding window), in second pass unroll classes based on their count and then choose random class from obtained list.
I don't think it is so common to infill (inpaint) categorical values in classification results of remote sensing. Māris. pirmd., 2023. g. 9. janv., plkst. 13:18 — lietotājs Bernardo Santos via grass-user (<[email protected]>) rakstīja: > > Hi Ken, > > The fuzzy logic tools seem interesting! But I am new to the concept so I did > not really think about how could I set functions/rules that increase with the > frequency of a land cover class... > Do you know any example in this context? > > I thought that people working with satellite imagery classification and cloud > cover would have experience with that, since sometimes it is necessary to > somehow interpolate and fill values cover by clouds... > > Best > B > > Em segunda-feira, 26 de dezembro de 2022 16:50:42 GMT+1, Ken Mankoff > <[email protected]> escreveu: > > > What about using the fuzzy logic modules? > > -k. > > Please excuse brevity. Sent from tiny pocket computer with non-haptic > feedback keyboard. > > On Wed, Dec 14, 2022, 13:38 Bernardo Santos via grass-user > <[email protected]> wrote: > > 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! > Best > Bernardo > _______________________________________________ > grass-user mailing list > [email protected] > https://lists.osgeo.org/mailman/listinfo/grass-user > > _______________________________________________ > grass-user mailing list > [email protected] > https://lists.osgeo.org/mailman/listinfo/grass-user _______________________________________________ grass-user mailing list [email protected] https://lists.osgeo.org/mailman/listinfo/grass-user
