An Approach to Removing Uncertainties in Nominal Environmental Covariates and Soil Class Maps

In this chapter we present an automated approach to correct the delineation of nominal soil and environmental datasets based on auxiliary metric attributes, aiming to enhance positional accuracy. The detection of uncertainties is based on different spatial and non-spatial approaches. The methodological framework mainly consists of nearest neighbour approaches and comprises supervised feature selection, different ensemble classification techniques, as well as spatial and non-spatial smoothing and generalization approaches. The method is described and applied to an artificial dataset as well as a 1:50 000 German soil map and a 1: 1 000 000 geological map of the Republic of Niger.