Comparing predictive capability of statistic and deterministic methods for landslide susceptibility mapping: a case study in the Northern Apennines (Reggio Emilia Province, Italy)

Statistical and deterministic methods are widely used in GIS-based landslide susceptibility mapping. This paper compares the predictive capability of three different models, namely the Weight of Evidence, the Fuzzy Logic and SHALSTAB, for producing shallow earth slides susceptibility maps to be included, as informative layer, in land planning at local level. The test site is an area of about 450 km2 in the northern Apennines of Italy where, in April 2004, rainfall combined with snow melting triggered hundreds of shallow earth slides that damaged roads and other infrastructures. An inventory of the landslides triggered by the event was obtained from interpretation of aerial photos of May 2004. The pre-existence of mapped landslides was checked using earlier aerial photo coverage. All the predictive models were run on the same set of geo-environmental causal factors: soil type, soil thickness, land cover, possibility of deep drainage through the bedrock, slope angle and flow accumulation. Models’ performance Results was processed assessed using a threshold-independent approach (the ROC plot). Results show that global accuracy is as high as 0.77 for statistical models while it is only 0.56 for SHALSTAB. The bad performance of the deterministic model is mainly due to the simplified assumptions behind the hydrological component (steady-state slope parallel flow) which are unsuitable for describing the hydrologic behaviour of clay slopes, that are widespread in the study area.