Abstract.A procedure to select the controlling factors connected to the slope instability has been defined. It allowed us to assess the landslide susceptibility in the Rio Beiro basin (about 10 km 2 ) over the northeastern area of the city of Granada (Spain). Field and remote (Google EarthTM) recognition techniques allowed us to generate a landslide inventory consisting in 127 phenomena. To discriminate between stable and unstable conditions, a diagnostic area had been chosen as the one limited to the crown and the toe of the scarp of the landslide. 15 controlling or determining factors have been defined considering topographic, geologic, geomorphologic and pedologic available data. Univariate tests, using both association coefficients and validation results of singlevariable susceptibility models, allowed us to select the best predictors, which were combined for the unique conditions analysis. For each of the five recognised landslide typologies, susceptibility maps for the best models were prepared. In order to verify both the goodness of fit and the prediction skill of the susceptibility models, two different validation procedures were applied and compared. Both procedures are based on a random partition of the landslide archive for producing a test and a training subset. The first method is based on the analysis of the shape of the success and prediction rate curves, which are quantitatively analysed exploiting two morphometric indexes. The second method is based on the analysis of the degree of fit, by considering the relative error between the intersected target landslides by each of the different susceptibility classes in which the study area was partitioned. Both the validation procedures confirmed a very good predictive performance of the susceptibility models and of the actual procedure followed to select the controlling factors.

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In this paper, ModelBuilder TM in ArcGIS (ESRI) has been applied to landslidesusceptibility analysis, mapping and validation. The models (scripts), available for direct downloading as an ArcGIS tool, allow landslide susceptibility to be computed in a given region, providing a landslide-susceptibility map, with the GIS matrix method, and ensuring a quality validation. The paper details the steps needed for the model-building process, enabling users to build their own models and to become more familiar with the tool. The susceptibility model leads the user first through a Digital Elevation Model (DEM), depicting the morphological and morphometric features of the study area, and then through a Digital Terrain Model (DTM), useful as a source of landslide-determinant factors, such as slope elevation, slope angle and slope aspect. In addition, another determinant factor is the lithological unit, independent of the DEM. Once the determinant landslide factors are reclassified and in a vectorial format, all the combinations between the classes of these factors are determined using the geoprocessing abilities of ArcGIS. The next step for the development of the landslide-susceptibility model consists of identifying the areas affected by a given surface of rupture (i.e. source area) in every combination of the determinantfactor classes. This step leads to the landslide matrix based on a previously georeferenced landslide database of the region, in which the slopes are distinguished into two simple classes: with or without landslides. In the last stage, to build a landslide-susceptibility model, the user computes the percentages of area affected by landslides in every combination of determinant factors. In the resulting landslide-susceptibility map a progressive zonation of areas or slopes increasingly prone to landslides is performed.

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