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:
The most common version is implemented for example in:
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 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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