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Sorry for not providing a code. I am asking a question that do not need a written chunk of code.
I am performing climate interpolation using the automatic semivariogram fitting offered by Automap R package. I have been trying to understand the arguments inside the autoKrige(), but could not understand the block argument.
Can anyone help me to understand that argument in GIS or spatial statistics manner?
These are the parameters for doing "Block Kriging". automap uses gstat, so the help pages for gstat::krige tell you what the parameters mean in slightly more detail that autoKrige does:
block: block size; a vector with 1, 2 or 3 values containing the
size of a rectangular in x-, y- and z-dimension respectively
(0 if not set), or a data frame with 1, 2 or 3 columns,
containing the points that discretize the block in the x-, y-
and z-dimension to define irregular blocks relative to (0,0)
or (0,0,0)-see also the details section of predict. By
default, predictions or simulations refer to the support of
the data values.
According to: https://www.publichealth.columbia.edu/research/population-health-methods/kriging-interpolation
"Block kriging, which estimates averaged values over gridded “blocks” rather than single points. These blocks often have smaller prediction errors than are seen for individual points."
but I'm struggling to find a reference on how you'd justify block kriging against simple point kriging, or how you'd choose the block size (except maybe by some cross-validation technique).
