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<div dir="ltr" data-setdir="false">Hi Ken,</div><div dir="ltr" data-setdir="false"><br></div><div dir="ltr" data-setdir="false">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...</div><div dir="ltr" data-setdir="false">Do you know any example in this context?</div><div dir="ltr" data-setdir="false"><br></div><div dir="ltr" data-setdir="false">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...</div><div dir="ltr" data-setdir="false"><br></div><div dir="ltr" data-setdir="false">Best</div><div dir="ltr" data-setdir="false">B </div><div><br></div>
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Em segunda-feira, 26 de dezembro de 2022 16:50:42 GMT+1, Ken Mankoff <mankoff@gmail.com> escreveu:
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<div><div id="yiv3890026284"><div><div>What about using the fuzzy logic modules? <br clear="none"><br clear="none"><div> -k.<br clear="none"><br clear="none">Please excuse brevity. Sent from tiny pocket computer with non-haptic feedback keyboard.</div></div><br clear="none"><div class="yiv3890026284gmail_quote"><div id="yiv3890026284yqt26295" class="yiv3890026284yqt0047918665"><div dir="ltr" class="yiv3890026284gmail_attr">On Wed, Dec 14, 2022, 13:38 Bernardo Santos via grass-user <<a rel="nofollow noopener noreferrer" shape="rect" ymailto="mailto:grass-user@lists.osgeo.org" target="_blank" href="mailto:grass-user@lists.osgeo.org">grass-user@lists.osgeo.org</a>> wrote:<br clear="none"></div><blockquote style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;" class="yiv3890026284gmail_quote"><div><div style="font-family:Helvetica Neue, Helvetica, Arial, sans-serif;font-size:16px;"><div dir="ltr">Hi,</div><div dir="ltr"><br clear="none"></div><div dir="ltr">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 <font face="courier new, courier, monaco, monospace, sans-serif">r.neighbors</font> (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 <font face="courier new, courier, monaco, monospace, sans-serif">r.fill.stats</font> which is basically the same thing.</div><div dir="ltr">However, the results gets very homogeneous, since the interpolated null cells always get the value of the most common land cover class.</div><div dir="ltr"><br clear="none"></div><div dir="ltr">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?</div><div dir="ltr">If not in GRASS, does anyway know of such a method in a different platform, i.e. R?</div><div dir="ltr"><br clear="none"></div><div dir="ltr">Thanks!</div><div dir="ltr">Best</div><div dir="ltr">Bernardo</div></div></div>_______________________________________________<br clear="none">
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