The indicator approach to categorical soil data

In this paper, the first of two, we present the indicator approach to describe the spatial variability of categorical soil data. Indicator kriging is used to obtain conditional probabilities of soil data classes at unsampled locations. A new concept of map purity is defined. Using Sequential Indicator Simulation (SIS), equiprobable realizations of classified maps can be drawn which reflect the probability of occurrence of each class and honour the observed spatial connectivity patterns of the classes and the classes found at the observation sites. When categorical data are used for land resources assessment, the uncertainties accruing from map impurities can be assessed by performing the analysis on each of the maps generated by SIS. In Part I1 of this series, the methods are demonstrated using a case study on the mapping of water table classes and a land use suitability analysis for pasture.