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...<br>
<br><div><span class="gmail_quote">2008/2/12, Paul Kelly <<a href="mailto:paul-grass@stjohnspoint.co.uk">paul-grass@stjohnspoint.co.uk</a>>:</span><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
On Tue, 12 Feb 2008, G. Allegri wrote:<br><br>> Hello everyone. In these days I was using IDW to make an easy interpolation<br>> of a point features layer, and I faced a strange behaviour.<br>> My dataset is composed of 122 points, and the attribute to be interpolated<br>
> is Z, in the sample I attach.<br>> I've interploated first in a narrow region around a peak. 5/122 points were<br>> used and the result is this:<a href="http://www.geospatial.it/allegri/IDW1.png">http://www.geospatial.it/allegri/IDW1.png</a>, 491<br>
> rows x 552 columns of 2 meters cells.<br>> Then I've widened the region in the same area:<br>> <a href="http://www.geospatial.it/allegri/IDW2.png">http://www.geospatial.it/allegri/IDW2.png</a>. Ok<br>> Then, when I've interpolated across the while area, the result is this<br>
> strange over-smoothed surface: <a href="http://www.geospatial.it/allegri/IDW3.png">http://www.geospatial.it/allegri/IDW3.png</a> ,<br>> where I put in evidence the first small region.<br><br>Are you sure they are really that different? If you could use the same<br>
colour table for all three images, it would be a lot easier to see. I<br>mean, are the values actually very different or are you just going by the<br>colours?<br><br>If you still notice anomalies after assigning the same colour table to all<br>
the maps, I will definitely look into it, as I wrote a lot of the code in<br>the current version of v.surf.idw.<br><br>> Another wierd surface I got is: <a href="http://www.geospatial.it/allegri/IDW4.png">http://www.geospatial.it/allegri/IDW4.png</a> ,<br>
> resulted from a lower resolution setting (50 meters) of the region.<br>><br>> About IDW3:<br>> Why the interpolation fails to detect local anomalies while it gets wider?<br>> It seems that the algorithm doesn't manage correctly the incresing number of<br>
> points vs search radius.<br><br>I'm not sure what you mean here. Can you explain further?<br><br>> I will try to take a look at the v.surv.idw code,<br>> and to understand what the nrowsxncols/npoints>400 threshold stands for...<br>
<br>It means, if the resolution is quite a lot larger than the number of<br>points, it simply searches through all the points for each cell of the<br>output raster to find the 12 closest, rather than using a search radius to<br>
only search those close by. It is just a bit faster. But if you can<br>improve the way it detects this it would be very interesting as I'm not<br>happy with the choice of such an arbitrary number.<br><br>Paul<br></blockquote>
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