A GIS-Based Multivariate Statistical Analysis for Shallow Landslide Susceptibility Mapping in La Pobla de Lillet Area (Eastern Pyrenees, Spain)

This paper presents a GIS-aided procedure for shallow landslide susceptibility mapping at a regional scale. Most of the input data for the susceptibility assessment have been captured automatically. A total of 13 parameters, related to the slope geometry, have been derived from the digital elevation model (DEM) while vegetation cover and thickness of superficial formations have been obtained from photointerpretation and field work. The susceptibility assessment is based on multivariate statistical techniques (discriminant analysis), which hasbeen tested in a pilot area in La Pobla de Lillet (Eastern Pyreenes, Spain). Theresults obtained using a random sample show that 82% of all the cells, and 90% of cells including slope failures, have been properly classified. A susceptibility map based on the discriminant function has given consistent results. The susceptibilityassessment is very sensitive to the parameters selected. Compared to thetraditional methods, the main advantage of the GIS-aided procedure is the rapidityprovided by the automatic capture of parameters. It also has the capability of coveringlarge areas, and the objectivity and reproducibility of the results. The main drawbackis that, at present, not all regions have DEM accurate enough to cope with small landslides.