Multisource evidential classification of surface cover and frozen ground

Abstract An evidential reasoning classification system (MERCURY©) has been developed to address some of the methodological limitations or conventional image analysis strategies applied to larger, multisource data sets. The software can process any number of variables at different levels of measurement without restrictions of underlying statistical models, and it can also incorporate measures of uncertainty into the analysis. A new frequency-based technique to compute evidence from training data has been implemented, and a modified decision rule is introduced for use with Dcmpstcr-Shafer orthogonal combination of evidence. These ideas were tested for a complex environment in northern Canada where the occurrence of permafrost (perennially frozen ground) was classified using field and remotely-sensed measures of landcover, equivalent latitude (potential insolation), and terrain aspect. Evidential classification of permafrost from field observations was 85 per cent in agreement with soil probe field determina...