One of the assumptions made in kriging is that the data being estimated
are stationary. That is, as you move from one region to the next in the
scatter point set, the average value of the scatter points is relatively
constant. Whenever there is a significant spatial trend in the data values
such as a sloping surface or a localized flat region, this assumption
is violated. In such cases, the stationary condition can be temporarily
imposed on the data by use of a drift
term. The drift is a simple polynomial function that models the average
value of the scatter points. The residual is the difference between the
drift and the actual values of the scatter points. Since the residuals
should be stationary, kriging is performed on the residuals and the interpolated
residuals are added to the drift to compute the estimated values. Using
a drift in this fashion is often called "__universal
kriging__."

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Kriging