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[ai-geostats] cokriging or not

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  • Törneman Niklas
    Hello list I have a soil parameter that exhibits clear spatial autocorrelation with a nice semivariogram. I have a secondary parameter which exhibits no
    Message 1 of 1 , Mar 24, 2006
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      Hello list
       
      I have a soil parameter that exhibits clear spatial autocorrelation with a nice semivariogram.
      I have a secondary parameter which exhibits no spatial autocorrelation and consequently I can not model any semivariogram parameters. The reason is most probably too few data.
      However, there exists an accepatble correlation between these two parameters (corr. coeff.=0.7, p<0.05).
       
      As I understand it, I have to define the semivariogram parameters (sill, nugget and range) for both parameters in order to use co-kriging for interpolation of the second parameter. This is not possible in my case. Are there any good methods to deal with this situation?
       
      Is it teoretically unsound to:
      1. Estimate my second parameter (using linear regression) at each point where the first parameter has been measured but not the second
      2.  Use kriging on estimated and measured values to interpolate the secondary parameter
       
      I understand that this approach is not optimal (Gerard and Pebesma 1999, Geoderma 89, 47-65) but is it wrong?
       
      cheers!
       
      /Niklas

       

       
       
       
       
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