In this work, the role of different landslide inventories in susceptibility assessment was evaluated using a non linear regression technique, namely the generalized additive model (GAM).The investigation was carried out in three study areas: the Versa catchment (Oltrepò Pavese, Southern Lombardy, Italy), the Vernazza catchment (Cinque Terre, Eastern Liguria, Italy) and the Pogliaschina catchment (Vara Valley, Eastern Liguria, Italy). Two landslide inventories related to the 2009 and 2013 rainfall events were taken into account in the Versa catchment, whereas two landslide inventories (referred to the same 2011 rainfall event) which differ for methods of detection and criteria adopted for the landslide mapping were considered in the Vernazza and Pogliaschina catchments. The predictive performance of GAM for each landslide inventory was evaluated. The results related to different inventories were compared. The results show that the predictive capability of the model and the landslide susceptibility are significantly influenced by the type of landslide inventory. Thus, the work highlights that a standard criterion for preparing inventories should be adopted in order to produce landslide susceptibility assessment as reliable as possible.
GIS-Based Deterministic and Statistical Modelling of Rainfall-Induced Landslides: A Comparative Study
BARTELLETTI, CARLOTTA;BARSANTI, MICHELE;GIANNECCHINI, ROBERTO;D'AMATO AVANZI, GIACOMO ALFREDO;GALANTI, YURI;
2017-01-01
Abstract
In this work, the role of different landslide inventories in susceptibility assessment was evaluated using a non linear regression technique, namely the generalized additive model (GAM).The investigation was carried out in three study areas: the Versa catchment (Oltrepò Pavese, Southern Lombardy, Italy), the Vernazza catchment (Cinque Terre, Eastern Liguria, Italy) and the Pogliaschina catchment (Vara Valley, Eastern Liguria, Italy). Two landslide inventories related to the 2009 and 2013 rainfall events were taken into account in the Versa catchment, whereas two landslide inventories (referred to the same 2011 rainfall event) which differ for methods of detection and criteria adopted for the landslide mapping were considered in the Vernazza and Pogliaschina catchments. The predictive performance of GAM for each landslide inventory was evaluated. The results related to different inventories were compared. The results show that the predictive capability of the model and the landslide susceptibility are significantly influenced by the type of landslide inventory. Thus, the work highlights that a standard criterion for preparing inventories should be adopted in order to produce landslide susceptibility assessment as reliable as possible.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
