Factor Selection Procedures in a Google Earth^TM Aided Landslide Susceptibility Model: Application to the Beiro River Basin (Spain)

A procedure to select the controlling factors connected to the slope instability has been defined. It allowed to assess the landslide susceptibility in the Rio Beiro basin (about 10 km²) over the north-eastern area of the city of Granada (Spain). Field and remote (Google Earth^TM) recognition techniques allowed to generate a landslide inventory consisting in 127 phenomena. Univariate tests, using both association coefficients and validation results of single parameter susceptibility models, allowed to select among 15 controlling factors the ones that resulted as good predictor variables; these have been combined for unique conditions analysis and susceptibility maps were finally 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 splitting of the landslide archive for producing a test and a training subset. The relative error, considered between the intersected target landslides by the different susceptibility classes, was used to estimate the predictive skill of the maps.