The aim of this paper is to present a spatial decision model based on logistic regression, fuzzy classification
and GIS-based techniques, applied to erosion risk mapping. The spatial database was composed by following
maps: NDVI vegetation index (1); terrain slope calculated from ASTER-GDEM2 (2); structural lineaments
density (3); road density (4) and a map of 729 gullies sites surveyed in the study area (5), obtained by Google
images visual analysis and field trip. The values of maps 1 to 4 were classified in 10 classes using the quantil
method. Total of gullies occurring in each class was calculated using overlay between one each of the maps
1 to 4, and the map 5. Odd ratios (OR) values indicating the chances in favor of a gully event in relation to
the chances against it, in each class map, were estimated using logistic regression. Then, OR curves were
converted in fuzzy values using membership functions (Mf). The erosion risk in each pixel was estimated using
the weighted sum of the following fuzzified variables: vegetation index, terrain slope, road density and
structural lineaments density.