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[ai-geostats] A question on lag class and lag distance

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  • xhy
    Dear all, I have a question on the selection of the lag classes and lag distance when computing experimental semi-variogram. It has been suggested that the
    Message 1 of 2 , Oct 1, 2004
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      Dear all,

       

      I have a question on the selection of the lag classes and lag distance when computing experimental semi-variogram. It has been suggested that the average semivariance can be done in an increment with an arbitrary distance tolerance (e.g. 300 m ± 150 m) taking into consideration of the number of data pairs per lag class. However, the lag class and lag distance are set a bit arbitrarily, and can influence the resulting variogram. My question is:

       

      1. How to select the lag class and lag distance in order to obtain a more reasonable experimental variogram?

       

      2. Is it reasonable to use an uneven set of lag (e.g. the lag increments are: 0-2.5m, 2.5-5.0m, 5.0-12.0m, 12.0-19.5m, 19.5-27.0m, 27.0-30.0m, 30.0-40m, 40-50m etc.) if a more stable variogram can be obtained?

       

      I should really appreciate anyone’s reply!

       

      Thanks a lot ahead!

       

      Xiuh



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    • Isobel Clark
      xhy your questions are long-standing and as yet unanswered in general. ... I always think of it as focussing a camera. Believe there is a pattern in your data
      Message 2 of 2 , Oct 1, 2004
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        xhy

        your questions are long-standing and as yet unanswered
        in general.

        > 1. How to select the lag class and lag distance in
        > order to obtain a more reasonable experimental
        > variogram?
        I always think of it as focussing a camera. Believe
        there is a pattern in your data and our task is to
        balance 'width of interval' versus 'number of pairs in
        interval' to get the clearest picture.

        One of the things I have found most useful with
        irregularly spaced data is a 'nearest neighbour'
        analysis. Take each sample and find the closest one to
        it. Record the distance. Repeat for all samples. This
        process takes twice as long as calculating the
        semi-variogram but gives you an idea of the 'natural'
        or model spacing between your samples. This can be
        used to guide your choice of interval.

        Check out our free tutorial downloads at
        http://geoecosse.bizland.com/softwares

        > 2. Is it reasonable to use an uneven set of lag
        > (e.g. the lag increments are: 0-2.5m, 2.5-5.0m,
        > 5.0-12.0m, 12.0-19.5m, 19.5-27.0m, 27.0-30.0m,
        > 30.0-40m, 40-50m etc.) if a more stable variogram
        > can be obtained?
        I am not sure I have ever seen this done, but don't
        see why not if you plot the point at the centre of
        gravity of your interval (i.e. average distance of
        pairs found).

        Hope this helps
        Isobel
        http://geoecosse.bizland.com/books.htm





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