Application of a Bayesian Network in a GIS Based Decision Making System

In this paper we show how a Pearl Bayes network of inference can be used with a GIS in order to combine information from different sources of data for the purpose of classification. Data may include satellite images, topographic maps, geological maps etc, each one with its own resolution and accuracy. We show how this uncertainty in the input data is incorporated in the network and develop also a method to construct the conditional probability matrices used by the network. We demonstrate our approach within the framework of the problem of assessing the risk of desertification of some burned forests in the Mediterranean region.