On Sat, Apr 15, 2017 at 8:32 AM, Benjamin Ducke <bendu...@fastmail.fm> wrote:
> The thing is: I originally developed this module for > gradiometer data. That data is very noisy and has > high local variation. Interpolating that type of > data while preserving original measurements will > usually result in unsatisfactory output. Also note > that the smoothing increases with the interpolation > radius. For tiny holes in LiDAR data, try "distance=1" > or "2". Of course, LiDAR data probably has different > properties and does not need low-pass filtering > like gradiometer data. So try "-p" to preserve the > original values. > > An alternative would be to invert the behaviour of > the module and assume "-p" by default. > > I don't work with LiDAR data myself, but I would very > interested to know your results! > I've added a figure which shows the r.slope.aspect products from the surface without and with -p. You can see that the smoothing gives significantly different results and probably better ones. I had the same experience in past when trying to patch result of r.neighbors with the original raster. Perhaps using smaller distance as you say or greater power would help, but I haven't tested that yet. I managed to commit just the figure its caption. If somebody gets to it, please extent the section.
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