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839AI-GEOSTATS: Experimental variograms.

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  • Digby Millikan
    Jan 13, 2003
    • 0 Attachment
      Hello,

      Further information regarding my previous email, I illustrate by means
      of an example.

      e.g a variogram may be computed from data;

      Lag(m) SemiVariogram Number of values Coefficient of Variation
      2 20 100
      5%
      4 40 200
      3%
      6 60 200
      5%
      8 60 200
      7%

      Another variogram may be calculated within a different region;

      Lag(m) SemiVariogram Number of values Coefficient of Variation
      2 20 100
      25%
      4 40 200
      30%
      6 60 200
      28%
      8 60 200
      30%


      In both cases a well shaped variogram has been computed to which a
      spherical model could be fitted.
      However the coefficient of variation is much different for the variogram
      points for the two cases.
      In the first case the coefficient of variation for each sample point is
      fairly low, so we could assume that the variogram is a good
      representation of the underlying dataset considering that we have taken
      a few random samples from an underlying large population.
      In the second case however the Coefficient of Variation is considerably
      higher so we would wonder how much any spatial model produced from
      this variogram is smoothed using a model fitted to such a variogram.
      My question was I was wondering if anyone has comments or can
      suggest any research or literature on the effects of the C.V., S.D. or
      variance of variogram values, and their effect on producing smoothed
      models.

      Regards Digby Millikan B.Eng

      Geolite Mining Systems
      U4/16 First Ave.,
      Payneham South SA 5070
      Australia.
      Ph: +61 8 84312974

      digbym@...
      http://www.users.on.net/digbym


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