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

Content Provider	Springer Nature Link
Author	Cervi, Federico Berti, Matteo Borgatti, Lisa Ronchetti, Francesco Manenti, Federica Corsini, Alessandro
Copyright Year	2010
Abstract	Statistical and deterministic methods are widely used in geographic information system 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 slide susceptibility maps, to be included as informative layers in land use planning at a 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 snowmelt triggered hundreds of shallow earth slides that damaged roads and other infrastructure. An inventory of the landslides triggered by the event was obtained from interpretation of aerial photos dating back to May 2004. The pre-existence of mapped landslides was then 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 upslope contributing area. Model performance was assessed using a threshold-independent approach (the ROC plot). Results show that global accuracy is as high as 0.77 for both statistical models, while it is only 0.56 for SHALSTAB. Besides the limited quality of input data over large areas, the relatively poorer performance of the deterministic model maybe also due to the simplified assumptions behind the hydrological component (steady-state slope parallel flow), which can be considered unsuitable for describing the hydrologic behavior of clay slopes, that are widespread in the study area.
Starting Page	433
Ending Page	444
Page Count	12
File Format	PDF
ISSN	1612510X
Journal	Landslides
Volume Number	7
Issue Number	4
e-ISSN	16125118
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-04-10
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Shallow landslide Susceptibility Spatial analyses northern Apennines Italy Geography (general) Civil Engineering Agriculture Natural Hazards
Content Type	Text
Resource Type	Article
Subject	Geotechnical Engineering and Engineering Geology

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