%0 Journal Article
%T Modelling shallow landslide susceptibility: a new approach in logistic regression by using favourability assessment
%J International journal of earth sciences
%D 2010
%A Domínguez-Cuesta, María José
%A Jiménez-Sánchez, Montserrat
%A Colubi, Ana
%A González-Rodríguez, Gil
%V 99
%N 3
%P 661-674
%X A new method for estimating shallow landslide susceptibility by combining Geographical Information System (GIS), nonparametric kernel density estimation and logistic regression is described. Specifically, a logistic regression is applied to predict the spatial distribution by estimating the probability of occurrence of a landslide in a 16 km 2 area. For this purpose, a GIS is employed to gather the relevant sample information connected with the landslides. The advantages of pre-processing the explanatory variables by nonparametric density estimation (for continuous variables) and a reclassification (for categorical/discrete ones) are discussed. The pre-processing leads to new explanatory variables, namely, some functions which measure the favourability of occurrence of a landslide. The resulting model correctly classifies 98.55% of the inventaried landslides and 89.80% of the landscape surface without instabilities. New data about recent shallow landslides were collected in order to validate the model, and 92.20% of them are also correctly classified. The results support the methodology and the extrapolation of the model to the whole study area (278 km 2 ) in order to obtain susceptibility maps.<p />
%G 
%I Holtzbrinck Springer Nature Publishing Group
%@ 1437-3254
%U http://dx.doi.org/10.1007/s00531-008-0414-0