Hi
Well, some time you have the impression that kriging is not an exact
interpolator because of
you have a high nugget effect and the interpolation grid nodes have
not the same location
of available data. The variability represented by the nugget effect
is filtered every time
an interpolation location doesn't coincide with known data.
So the apparent smoothing effect is related to the raster
representation of reality.
Sebastiano T.
At 09.56 19/02/2008, you wrote:
Dear list,
I'm graduate student in hydrogeology, I've to spatialize data of
reservoir thickness, and I need to achieve a map having exactly the
sampled value in the sampled localization (piezometers). I've little
experience in geostatatistics.
I had a look at kriging algorithms, but I did understand that kriging
does not preserve the sampled value at sampled locations but it tends
to smooth results, even if estimates correctly the unsampled space. So
I wonder why should I use Kriging instead IDW (which it should
preserve my sampled values): kriging respects the spatial variability
but do not respect data
As I told you before, I've very small knowledge in geostatistics
stuff, but I'm interesting in kriging.
Could anyone help me?
Thanks a lot,
Andrea Peruzzi
PS: I apologize for writing you again but it's the first time I'm
writing you, then I'm not sure how the mailing list works. Thanks :-)
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