Continuous classification in soil survey: spatial correlation, confusion and boundaries

Abstract

This article traces the development of conceptual paradigms of soil classification and mapping from the pre-1960's model of crisp classes in attribute space linked to crisply delineated mapping units in geographical space, to modern approaches using fuzzy classification and geostatistical interpolation for simultaneously handling continuous variation in both attributes and location. Continuous classification yields a separate map of class membership values for every class the dominance of any class at each location can be expressed by a confusion index, CI. If spatial correlation is strong, zones of high CI are concentrated in narrow geographical transition zones between locally dominant classes: these zones can be refined to delineate automatically classspecific boundaries. If spatial correlation in membership values is weak then broad zones of large values of CI occur all over the map. Simulation modelling and two case studies demonstrate that contiguity in geographical space is more important for successful mapping than attribute class compactness. The studies show that soil information systems must take the spatial aspects of soil variation into account; further improvements in identifying and mapping significant soil groupings should be possible using numerical models of soil processes together with the methods presented here.