Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/14852
Authors: Carabella, Cristiano* 
Cinosi, Jacopo* 
Piattelli, Valerio* 
Burrato, Pierfrancesco* 
Miccadei, Enrico* 
Title: Earthquake-induced landslides susceptibility evaluation: A case study from the Abruzzo region (Central Italy)
Journal: Catena 
Series/Report no.: /208 (2022)
Publisher: Elsevier
Issue Date: 9-Sep-2021
DOI: 10.1016/j.catena.2021.105729
URL: https://www.sciencedirect.com/science/article/pii/S0341816221005877
Subject Classification04.04. Geology 
Abstract: Landslides are widespread natural phenomena that play an important role in landscape evolution and are responsible for several casualties and damages. Slope instability is linked to the combination of geological, geomorphological, and climatic factors with various triggering mechanisms; among these, seismic shaking can induce relevant changes in the landscape, leading to coseismic and post-seismic phenomena such as landslide events. The Abruzzo Region (Central Italy) is severely affected by Earthquake-Induced Landslides (EILs), linked to the geomorphological dynamics and the severe seismicity of the area. The distribution, mechanisms, and typology of landslides are strictly related to the different physiographic and geological-structural settings. This paper focuses on the realisation of an EILs susceptibility map, following a heuristic approach combined with a statistical analysis, integrated using GIS technology. This approach led to the identification of nine instability factors. These factors were analysed for the construction of thematic maps. Hence, each factor was assigned proper expert-based ranks and weights based on the critical evaluation of literature data as well as on available landslide inventories and combined in a preliminary map wherein high/low numerical values correspond to a high/low propensity of the slope to fail; furthermore, a statistical analysis of these values was performed to derive suitable susceptibility classes. Results presented herein highlight the robustness of the approach; remarkably, the applied methodology is suitable even in areas where a detailed landslide catalogue is lacking, when the same classification and weighting of available parameters is performed. The statistical analyses and the adoption of an absolute scale ranging from minimum to maximum potential values, finally, ensures the comparability of results among different study areas. Finally, this work represents a scientific and multidisciplinary tool for better defining situations that could lead to hazards (such as landslides) following an earthquake to develop sustainable territorial planning, emergency management, and loss-reduction measures.
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