How Moving Window Kriging works

A geostatistical layer is created using the complete input dataset. The kriging parameters can be adjusted or left as the initial default values that are automatically determined by the Geostatistical Wizard. The rationale behind Moving Window Kriging is to recalculate the Range, Nugget, and Partial Sill semivariogram parameters based on a smaller neighborhood.

When the data is nonstationary, you must estimate a heterogeneous semivariogram. In other words, use a moving window centered on the location to be predicted and create a semivariogram for each local neighborhood.

The prediction at each point s in the study area can be mapped sequentially as the window moves through the study area (figure 1). In this example, the data is isotropic or invariant under rotations. To exhaustively map every location in the study area, semivariograms are calculated for each location to be predicted. Within each neighborhood, the data is assumed to be locally stationary so the assumptions of the kriging algorithm are not violated.

As the window moves through the study area, new semivariogram parameters are calculated using neighboring points. For location s₁, the blue and green points are spatially correlated or within the range distance as indicated by the radius of the circle centered at that point. For location s₂, the green and red points are spatially correlated, and for location s_n, the yellow points are spatially correlated.

Heterogeneous semivariogram predictions