The mean value of samples from a geographical space can be estimated, either using the arithmetic mean or by constructing a weighted average integrating the knowledge of the spatial correlation of the samples. The two approaches are developped and it turns out that the solution of kriging the mean reduces to the arithmetic mean when there is no spatial correlation between data locations.
KeywordsEstimation Error Spatial Correlation Covariance Function Estimation Variance Geographical Space
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