Abstract
Landslide susceptibility is one of the main topics of geomorphological risk studies. Unfortunately, many of these studies applied an exclusively statistical approach with little coherence with the geomorphodynamic models, resulting in susceptibility maps that are difficult to read. Even if many different models have been developed, those based on statistical techniques applied to slope units (SUs) are among the most promising. SU segmentation divides terrain into homogenous domains and approximates the morphodynamic response of the slope to landslides. This paper presents a landslide susceptibility (LS) analysis at the catchment scale for a key area based on the comparison of two GIS-based bivariate statistical methods using the landslide index (LI) approach. A new simple and reproducible method for delineating SUs is defined with an original GIS-based terrain segmentation based on hydrography. For the first time, the morphometric slope index (MSI) was tested as a predisposing factor for landslides. Beyond the purely statistic values, the susceptibility maps obtained have strong geomorphological significance and highlight the areas with the greatest propensity to landslides. We demonstrate the efficiency of the SU segmentation method and the potential of the proposed statistical methods to perform landslide susceptibility mapping (LSM).
Highlights
Many of the landslides occurred on cultivated sites, and their morphological evidence was modified or removed by farming practices
More recent landslides were mapped during the field activity and the air-photo analysis
The majority of the landslides were of the flow type (223 out of 265)
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Landslide susceptibility (LS) can be defined as the probability that a landslide will occur in a given area based on terrain conditions without any temporal consideration [1]. It follows the principle that future slope failures are more likely to occur under the same conditions that have triggered past and present slope failures [2]. Certain terrain conditions can be considered as predisposing factors for the development of landslides. Triggering factors are temporary conditions that can directly cause landslides (e.g., earthquakes, rapid snow melt, and heavy rain). Landslide susceptibility maps are produced by considering conditioning factors only, whereas landslide hazard maps consider both predisposing and triggering factors [2]
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