Kriging is a multistep process; it includes exploratory statistical analysis of the data, variogram modeling, creating the surface, and (optionally) exploring a variance surface. Kriging is most appropriate when you know there is a spatially correlated distance or directional bias in the data. It is often used in soil science and geology. Jan 01, 2019 · Lecture Notes on Kriging kriging example the main result in kriging is concerned with estimation of the value (also referred to as z0 based on the observed. In Part One of this tutorial, we covered the basics of 3D Variability Analysis (3DVA) and showed how it can be used to solve for variability components (i.e., eigenvectors of the 3D covariance of images).

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