MATEC Web Conf.
Volume 149, 20182nd International Congress on Materials & Structural Stability (CMSS-2017)
|Number of page(s)||6|
|Section||Session 2 : Structures & Stability|
|Published online||14 February 2018|
Extraction of the predisposition parameters for mapping the susceptibility of slides lands, in the region of EL Quola, province of Larache (Nothern Rif)
Université Mohammed V, Faculté des Sciences de Rabat, Département des Sciences de la Terre, Laboratoire GEORISK : Risques Géologiques, Télédétection et Environnement. Avenue Ibn Battouta Rabat – Agdal, Boîte Postale 1014, Rabat, Maroc
Slide lands (Lands mass movements) are among the natural risks that Morocco faces in the Rifaines regions in particular. They generally constitute small-scale, punctual phenomena. But their diversity and frequency are nevertheless responsible for significant and costly damages and injuries. To deal with this problem, the study of field instabilities must take into account that: ithe ground movements must be taken in a context of the overall dynamics of the watershed, ii-the choice of more objective methods, which is not based on the very subjective opinion of the expert; iii-the choice of an adapted approach to the scale of work. In this article, we used the evidence theory "WofE" to evaluate the sensibility of landslide in the El Quola area. This method is based on the analysis of the relationships between landslides that occurred in the past (the so-called modelable variable Vm) and the spatial distribution of some predictive parameters of instability (Vp). The result obtained is a landslide susceptibility map that is the result of multi-disciplinary and multi-temporal data. This method has been described as one of the most performing by several authors; however, it requires a conditional independence between the different predictive factors. The quality of the performances was evaluated with success curves.
© 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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