This paper conducts a statistical analysis to determine shallow-landslide susceptibility in an approximately 7500-km2 region of the south-eastern Alps (South Tyrol, Italy). The study applies the weight of evidence (WofE) method, which is useful in determining landslide susceptibility in large areas with complex geological and geomorphological settings. The statistical analysis and landslide susceptibility mapping are based on 882 past landslides, three geometric/topographic factors and two anthropogenic factors, which are the most relevant landslide predisposing factors. The quality of the proposed model, particularly the fitting performance, was assessed; the landslide database was divided into a training set to obtain the model and a validation set to estimate the model quality. The results show that the developed susceptibility model predicts an acceptable percentage (75%) of landslides. Therefore, the model can be useful and reliable for land planners and decision makers also due to its cost-effectiveness ratio.

Statistical analysis for assessing shallow-landslide susceptibility in South Tyrol (south-eastern Alps, Italy.

TROIANI, FRANCESCO;SAVELLI, DANIELE;
2012-01-01

Abstract

This paper conducts a statistical analysis to determine shallow-landslide susceptibility in an approximately 7500-km2 region of the south-eastern Alps (South Tyrol, Italy). The study applies the weight of evidence (WofE) method, which is useful in determining landslide susceptibility in large areas with complex geological and geomorphological settings. The statistical analysis and landslide susceptibility mapping are based on 882 past landslides, three geometric/topographic factors and two anthropogenic factors, which are the most relevant landslide predisposing factors. The quality of the proposed model, particularly the fitting performance, was assessed; the landslide database was divided into a training set to obtain the model and a validation set to estimate the model quality. The results show that the developed susceptibility model predicts an acceptable percentage (75%) of landslides. Therefore, the model can be useful and reliable for land planners and decision makers also due to its cost-effectiveness ratio.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2506848
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 67
  • ???jsp.display-item.citation.isi??? 55
social impact