Hi Ulrich,
It's not an easy question. First note that the search strategy
includes not only the size of the search window but also the maximum
number of observations. In may occasions, I set the search radius
to a very large distance and use the number of observations as
the controling parameter. Using too many observations or too large
search windows may lead to oversmoothing, while estimates based on
low number of observations (say less than 8 in 2D) might not be
very reliable. Of course it depends also on the relative nugget effect.
If it is large, even further away observations will receive a
significant weight.
In practice, global search windows are seldom used because:
(1) no reliable semivariogram values are available
for so large distances, (2) the size of the kriging system is
likely very large, and (3) the stationarity assumption
within the search window might become questionable.
The best way to proceed would be to do some cross validation
using various search strategies and investigate their impact
on re-estimation scores.
Regards,
Pierre Goovaerts
Dr. Pierre Goovaerts
President of PGeostat, LLC
Chief Scientist with Biomedware Inc.
710 Ridgemont Lane
Ann Arbor, Michigan, 48103-1535, U.S.A.
E-mail: [EMAIL PROTECTED]
Phone: (734) 668-9900
Fax: (734) 668-7788
http://alumni.engin.umich.edu/~goovaert/
On 8 Jul 2003, Ulrich Leopold wrote:
Dear list,
What would you consider the most reliable ordinary kriging estimate? To
use a local search neighbourhood (slightly bigger than the effective
range) or set to global to include *all* data locations?
Ulrich
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Ulrich Leopold MSc.
Department of Physical Geography
Institute for Biodiversity and Ecosystem Dynamics
Faculty of Science
University of Amsterdam
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NL-1018WV Amsterdam
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Check us also out at:
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