Comparison of GIS-based methodologies for the landslide susceptibility assessment Paolo Magliulo & Antonio Di Lisio & Filippo Russo Received: 2 July 2007 / Revised: 11 February 2008 / Accepted: 23 October 2008 # Springer Science + Business Media, LLC 2008 Abstract In this paper, two simple GIS-based methodologies have been used to assess the landslide susceptibility in a basin located in Southern Italy. The methodologies at issue, based on the spatial distribution of landslides and/or of causal factors, are bivariate statistics-based and expert-based, respectively. The spatial distribution of both the landslides and the causal factors has been investigated by integrating pre-existing and original data, which have been processed using ArcView GIS 3.2 software. The obtained results, consisting of landslide susceptibility maps have been compared and discussed. The bivariate statistics-based method has provided the most satisfying results. On the contrary, the expert-based method has provided a classification of the study area in terms of landslide susceptibility which does not completely fit with the surveyed spatial distribution of the landslides. Keywords Landslide susceptibility . GIS . Geomorphology . Southern Italy 1 Introduction Landslide susceptibility is the possibility that a landslide will occur in a particular area on the basis of the local environmental conditions [2]. Most of the approaches currently used in assessing and mapping landslide susceptibility are based on an accurate evaluation of the spatial distribution of both the “causal factors”, i.e. geoenvironmental factors determining all the pre-conditions for failure, and/or of the landslides. This involves the handling, the interpretation and the graphical representation of a large amount of territorial data. Thus, GIS represent a powerful tool in landslide susceptibility assessment. To assess landslide susceptibility, in most cases numerical weighting values are assigned to each class of the considered causal factors. In assigning weighting values, different approaches can be used. A first approach is the so-called qualitative or expert-evaluation approach [15]. In this Geoinformatica DOI 10.1007/s10707-008-0063-2 P. Magliulo (*) : A. Di Lisio : F. Russo Dipartimento di Studi Geologici e Ambientali, Università degli Studi del Sannio, via dei Mulini 59/A, 82100 Benevento, Italy e-mail: magliulo@unisannio.it