Wednesday, 25 May 2016

interpolation - Open source methods for kriging?


I have a point dataset which I'd like to Krige, ideally using an open-source software package. If possible, I'd also like to choose the semi-variogram model during the process to improve the estimation.



Answer



Depending on which Kriging type you want to apply, there are different packages to choose from:


Ordinary Kriging


The most common version is implemented for example in:



Simple Kriging


Simple Kriging uses the average of the entire data set while Ordinary Kriging uses a local average. Therefore, Simple Kriging can be less accurate, but it generally produces "smoother" results. It's implemented in:




Universal Kriging


Universal Kriging allows for consideration of drift in data. Implementations are included in:



Other Kriging Types


GRASS v.krige also supports Block Kriging.


HPGL implements a big number of less known Kriging methods (check the manual for more information on those):



  • Indicator Kriging (IK)

  • Local Varying Mean Kriging (LVM Kriging)

  • Simple CoKriging (Markov Models 1 & 2)


  • Sequential Indicator Simulation (SIS)

  • Corellogram Local Varying Mean SIS (CLVM SIS)

  • Local Varying Mean SIS (LVM SIS)

  • Sequential Gaussian Simulation (SGS)

  • Truncated Gaussian Simulation (GTSIM) [in Python scripts collection]


SAGA offers different versions of both Ordinary and Universal Kriging.


Gstat krige additionally supports Block and Point Kriging.


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