Probabilistic Temporal GIS Modelling Involving More Than Two Map Classes

Abstract The development of probability-based spatial-temporal models for more than two classes is demonstrated using discriminant function analysis. This represents a significant departure from other probabilistic approaches which have largely been confined to modelling the outcome of a single binary event. It also represents a significant departure from conventional deterministic overlay analysis. Procedures for calibrating and validating such models are presented and discussed. The validation procedures discussed implicate both aspatial consideration, i.e., the amount of each cover type estimated, and spatial factors, i.e., the location of each cover type and the spatial dependence of model residuals (spatial autocorrelation).

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