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RE: [ai-geostats] Understanding variograms

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  • Pierre Goovaerts
    Another explanation for this shape is that Jose is looking at the variogram for short distances. It is well known that for very continuous attributes, such as
    Message 1 of 4 , Nov 3, 2004
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      Another explanation for this shape is that Jose is looking at
      the variogram for short distances. It is well known that for
      very continuous attributes, such as elevation or depth to water table.
      the semivariogram is expected to display a parabolic behaviour at
      the origin, which can be modeled using a Gaussian or cubic model
      for example. If one computes the semivariogram before it reaches
      its sill, then one will look only at a power curve and conclude
      that a trend is present. As always, everything is a matter of scale,
      and what looks like as a trend at a local scale can be modeled as
      part of a stationary process at a more regional scale.

      Cheer,

      Pierre
      <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

      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: goovaert@...
      Phone: (734) 668-9900
      Fax: (734) 668-7788
      http://alumni.engin.umich.edu/~goovaert/

      <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

      On Wed, 3 Nov 2004, Dan Bebber wrote:

      > Detrending is a pretty basic practice in geostatistics. I think you should
      > do some more reading before you plunge into analyses.
      >
      > Dan Bebber
      >
      > > -----Original Message-----
      > > From: Jose Luis Gomez Dans [mailto:jgomezdans@...]
      > > Sent: 03 November 2004 17:01
      > > To: Dan Bebber
      > > Subject: Re: [ai-geostats] Understanding variograms
      > >
      > >
      > > Dan and Isobel,
      > > Many thanks for your prompt reply!
      > >
      > > On Wednesday 03 Nov 2004 16:39, you wrote:
      > > > It probably means that you have a spatial trend in
      > > your data.
      > > > Remove any trend, then try again.
      > >
      > > OK, my data are point heights above the geoid over a
      > > large area. While
      > > there could well be a trend, how would I go
      > > de-trending the data? I
      > > have a digital elevation model of this region, and I
      > > guess I could
      > > subtract the grid value for each point considered, and
      > > that should get
      > > rid of things like slope effects (in effect, a
      > > linear-ish trend).
      > >
      > > Does this make any sense?
      > >
      > > Many thanks
      > > Jose
      > >
      > > --
      > > Jose L Gomez-Dans, Research Assistant
      > > Bristol Glaciology Centre, Geographical Sciences/CPOM
      > > University of Bristol, Bristol, UK
      > >
      > >
      > >
      > >
      > >
      > >
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