Developing and testing a data-driven methodology for shallow landslide susceptibility assessment: preliminary results

Massimiliano Bordoni (a), Maria Giuseppina Persichillo (a), Claudia Meisina (a), Andrea Cevasco (b), Roberto Giannecchini (c), Giacomo D'Amato Avanzi (c), Yuri Galanti (c), Carlotta Bartelletti (c), Pierluigi Brandolini (b) & Davide Zizioli (a)
(a) Department of Earth and Environmental Sciences , University of Pavia, Via Ferrata, 1, 27100, Pavia, Italy. E-mail: massimiliano.bordoni01@universitadipavia.it (b) Department of Earth, Environmental and Life Sciences, University of Genoa, Corso Europa, 26, 16132, Genoa, Italy (c) Earth Sciences Department, University of Pisa, Via S. Maria, 53, 56126, Pisa, Italy.

In this work a data-driven methodology for shallow landslide susceptibility assessment is presented. The procedure is based on the Generalized Additive Model (Hastie and Tibshirani, 1990) and it is developed to be applied in different contexts, using terrain attributes, land use and lithological data. The application of the method in three different contexts in Italy shows the good forecasting capability of the model. The implementation of this method allows for building landslide susceptibility maps, which are a fundamental basis in hazard and risk assessment.

data-driven methods, Generalized Additive Model, landslides susceptibility, Oltrepo Pavese, Eastern Liguria.