In this paper, a bivariate-heuristic model (modified Stevenson's method) and two multivariate statistical procedures (discriminant analysis and logistic regression) were used in order to assess and map landslide susceptibility in the north-western side of Daunia region (Apulia, Southern Italy). The whole Daunia region is characterized by complex and composite landslides, which are located on clayey slopes, near urban centers, affecting structures and infrastructures. The high predisposition to landsliding of the Daunia hillslopes is related to the very poor strength properties of clayey formations. The comparative analysis of landslide susceptibility using different methods, on the same test site and with the same inventory map allowed understanding the dependence of the results from the dataset and the capability of models under different levels of use, from expert to simple operator. By comparing the performance of the three models through the success rate curves, it emerges that the simple modified Stevenson's method produces reliable outcomes, comparable with those deriving from more complex multivariate statistical models. This result is related to the characteristics of clayey slopes, in which the landslide occurrence is so much controlled by the poor strength properties of the clayey formations that the multivariate analysis of a large set of morphometric, geological and land-use variables results to be somehow superfluous. This suggests that, for clayey slopes, a simple, easy-to-manage bivariate-heuristic model based on expert opinion can be used with reliable results. © 2013 Springer-Verlag Berlin Heidelberg

Pellicani, R., Frattini, P., Spilotro, G. (2014). Landslide susceptibility assessment in Apulian Southern Apennine: Heuristic vs. statistical methods. ENVIRONMENTAL EARTH SCIENCES, 72(4), 1097-1108 [10.1007/s12665-013-3026-3].

Landslide susceptibility assessment in Apulian Southern Apennine: Heuristic vs. statistical methods

FRATTINI, PAOLO
Secondo
;
2014

Abstract

In this paper, a bivariate-heuristic model (modified Stevenson's method) and two multivariate statistical procedures (discriminant analysis and logistic regression) were used in order to assess and map landslide susceptibility in the north-western side of Daunia region (Apulia, Southern Italy). The whole Daunia region is characterized by complex and composite landslides, which are located on clayey slopes, near urban centers, affecting structures and infrastructures. The high predisposition to landsliding of the Daunia hillslopes is related to the very poor strength properties of clayey formations. The comparative analysis of landslide susceptibility using different methods, on the same test site and with the same inventory map allowed understanding the dependence of the results from the dataset and the capability of models under different levels of use, from expert to simple operator. By comparing the performance of the three models through the success rate curves, it emerges that the simple modified Stevenson's method produces reliable outcomes, comparable with those deriving from more complex multivariate statistical models. This result is related to the characteristics of clayey slopes, in which the landslide occurrence is so much controlled by the poor strength properties of the clayey formations that the multivariate analysis of a large set of morphometric, geological and land-use variables results to be somehow superfluous. This suggests that, for clayey slopes, a simple, easy-to-manage bivariate-heuristic model based on expert opinion can be used with reliable results. © 2013 Springer-Verlag Berlin Heidelberg
Articolo in rivista - Articolo scientifico
Discriminant analysis; Heuristic model; Landslide; Logistic regression; Susceptibility; Soil Science; Environmental Chemistry; Water Science and Technology; Pollution; Global and Planetary Change; Geology; Earth-Surface Processes
English
2014
72
4
1097
1108
none
Pellicani, R., Frattini, P., Spilotro, G. (2014). Landslide susceptibility assessment in Apulian Southern Apennine: Heuristic vs. statistical methods. ENVIRONMENTAL EARTH SCIENCES, 72(4), 1097-1108 [10.1007/s12665-013-3026-3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/107973
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