| Summary: | Probability maps are useful to analyze ores or contaminants in soils and they are helpful to make a decision duringexploration work. These probability maps are usually derived from the indicator kriging approach. Ordinary krigingweights can be used to derive probability maps as well. For testing these two approaches a sample data base was randomlydrawn from an exhaustive data set. From the exhaustive data set actual cumulative distribution functions were determined.Thus, estimated and actual conditional cumulative distribution functions were compared. The vast majority of correlationcoeffi cients between estimated and actual probability maps is greater than 0.75. Not only does the ordinary kriging approachwork, but it also gives slightly better results than median indicator kriging. Moreover, probability maps from ordinary krigingweights are much easier than the traditional approach based on either indicator kriging or median indicator kriging.
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