Abstract:

There is a wide range of alternative approaches to study erosion processes. In this paper the construction of a model based in the interaction of Geographical Information System (GIS) and Artificial Neural Networks (ANN) is described. The
neural model uses supervised competitive learning process. The whole procedure starts with the digitization of collected data and the definition of the input variables, such as slope form and gradient, susceptibility to erosion and protective cover. The input variables are transformed into the erosion risk output variable using the neural model. The last stage concerns the development of an erosion risk zones map.