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

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