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Geosciences 2014, 4(3), 176-190;

GIS-Based Landslide Susceptibility Mapping on the Peloponnese Peninsula, Greece

Department of Geography, Harokopio University, El. Venizelou 70, 17671 Athens, Greece
Department of Geological Sciences, University of KwaZulu-Natal, Westville, Private Bag X54001, South Africa
Author to whom correspondence should be addressed.
Received: 16 May 2014 / Revised: 12 August 2014 / Accepted: 13 August 2014 / Published: 20 August 2014
(This article belongs to the Special Issue Geological Mapping and Modeling of Earth Architectures)
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: In this paper, bivariate statistical analysis modeling was applied and validated to derive a landslide susceptibility map of Peloponnese (Greece) at a regional scale. For this purpose, landslide-conditioning factors such as elevation, slope, aspect, lithology, land cover, mean annual precipitation (MAP) and peak ground acceleration (PGA), and a landslide inventory were analyzed within a GIS environment. A landslide dataset was realized using two main landslide inventories. The landslide statistical index method (LSI) produced a susceptibility map of the study area and the probability level of landslide occurrence was classified in five categories according to the best classification method from three different methods tested. Model performance was checked by an independent validation set of landslide events. The accuracy of the final result was evaluated by receiver operating characteristics (ROC) analysis. The prediction ability was found to be 75.2% indicating an acceptable susceptibility map obtained from the GIS-based bivariate statistical model. View Full-Text
Keywords: landslide susceptibility modeling; statistical index; GIS; Peloponnese; Greece landslide susceptibility modeling; statistical index; GIS; Peloponnese; Greece

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Chalkias, C.; Ferentinou, M.; Polykretis, C. GIS-Based Landslide Susceptibility Mapping on the Peloponnese Peninsula, Greece. Geosciences 2014, 4, 176-190.

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