AI-GEOSTATS: Ordinary Kriging question
- Friends of AI-GEOSTATS
I had a simple question regarding ordinary kriging. When dealing
with clustered data (either 2D or 3D) with various interpolation
techniques, is there an issue at all with redundant data? I've
never heard of this term before. Furthermore, with respect to
kriging, does this interpolation scheme handle clustered data any
differently than say any other type of interpolation (splines,
inverse distance weighted, natural neighbors)?
[Non-text portions of this message have been removed]
- Some would say that the whole advantage of kriging is
in the fact that it handles clustered data
automatically -- weighing each sample according to its
'actual' information content.
This, of course, relies on you having the correct
semi-variogram model. That being the other major
difference between a geostatistical estimation and
those which assume a standard or arbitrary spatial
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