Hi Paul. The anomalies are in the raster values, indipendently by the color table. If you do an r.what around the peak in IDW1 you get raster values corresponding to the point Z value (about 22000), while if you do r.what on IDW3 you get values arounf 2000...
2008/2/12, Paul Kelly <[EMAIL PROTECTED]>: > > On Tue, 12 Feb 2008, G. Allegri wrote: > > > Hello everyone. In these days I was using IDW to make an easy > interpolation > > of a point features layer, and I faced a strange behaviour. > > My dataset is composed of 122 points, and the attribute to be > interpolated > > is Z, in the sample I attach. > > I've interploated first in a narrow region around a peak. 5/122 points > were > > used and the result is this:http://www.geospatial.it/allegri/IDW1.png, > 491 > > rows x 552 columns of 2 meters cells. > > Then I've widened the region in the same area: > > http://www.geospatial.it/allegri/IDW2.png. Ok > > Then, when I've interpolated across the while area, the result is this > > strange over-smoothed surface: http://www.geospatial.it/allegri/IDW3.png, > > where I put in evidence the first small region. > > Are you sure they are really that different? If you could use the same > colour table for all three images, it would be a lot easier to see. I > mean, are the values actually very different or are you just going by the > colours? > > If you still notice anomalies after assigning the same colour table to all > the maps, I will definitely look into it, as I wrote a lot of the code in > the current version of v.surf.idw. > > > Another wierd surface I got is: > http://www.geospatial.it/allegri/IDW4.png , > > resulted from a lower resolution setting (50 meters) of the region. > > > > About IDW3: > > Why the interpolation fails to detect local anomalies while it gets > wider? > > It seems that the algorithm doesn't manage correctly the incresing > number of > > points vs search radius. > > I'm not sure what you mean here. Can you explain further? > > > I will try to take a look at the v.surv.idw code, > > and to understand what the nrowsxncols/npoints>400 threshold stands > for... > > It means, if the resolution is quite a lot larger than the number of > points, it simply searches through all the points for each cell of the > output raster to find the 12 closest, rather than using a search radius to > only search those close by. It is just a bit faster. But if you can > improve the way it detects this it would be very interesting as I'm not > happy with the choice of such an arbitrary number. > > Paul >
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