Modelling uncertainty in categorical data for GIS quality assessment.

In geography people are using frequently categorical maps to mapp spatial continuing. Categorical maps however, don't succeed to give an accurate discription of transition zones and mixed zones, that results in doubt about the class which a location belongs to. Fault propagation allows us to quantify the effect of uncertainty of the results of an analysis and is an important instrument of quality monitoring with the use of GIS. The necessary information to execute a fault propagation is missing for the most of the categorical maps. In this research proposal we want to elaborate a methodology to model the incertainty in a categorical map based on secundary data-sets.