MATEC Web Conf.
Volume 149, 20182nd International Congress on Materials & Structural Stability (CMSS-2017)
|Number of page(s)||7|
|Section||Session 2 : Structures & Stability|
|Published online||14 February 2018|
Mass movement susceptibility mapping - A comparison of logistic regression and Weight of evidence methods in Taounate-Ain Aicha region (Central Rif, Morocco)
Université Mohammed V, Faculté des sciences Département sciences de la terre, Unité de recherche GEORISK et LGRN, 4 Avenue Ibn Battouta Rabat-Agdal, BP 1014, Rabat, Maroc
Taounate region is known by a high density of mass movements which cause several human and economic losses. The goal of this paper is to assess the landslide susceptibility of Taounate using the Weight of Evidence method (WofE) and the Logistic Regression method (LR). Seven conditioning factors were used in this study: lithology, fault, drainage, slope, elevation, exposure and land use. Over the years, this site and its surroundings have experienced repeated landslides. For this reason, landslide susceptibility mapping is mandatory for risk prevention and land-use management. In this study, we have focused on recent large-scale mass movements. Finally, the ROC curves were established to evaluate the degree of fit of the model and to choose the best landslide susceptibility zonation. A total mass movements location were detected; 50% were randomly selected as input data for the entire process using the Spatial Data Model (SDM) and the remaining locations were used for validation purposes. The obtained WofE’s landslide susceptibility map shows that high to very high susceptibility zones contain 62% of the total of inventoried landslides, while the same zones contain only 47% of landslides in the map obtained by the LR method. This landslide susceptibility map obtained is a major contribution to various urban and regional development plans under the Taounate Region National Development Program.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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