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|
Susceptibility assessment of landslides: A comparison of two GIS-based methods in the region of Al Hoceima (Eastern Rif, Morocco).
Mohammed V University, faculty of science, department of earth sciences, GEORISK research unit: Geological risks, remote sensing and sustainable development. Ibn Battuta street, PO Box 1014, RABAT, MOROCCO.
3 Mohammed VI Polytechnic University, Geology & Sustainable Mining, BENGUERIR, MOROCCO.
The evaluation of the degree of susceptibility to landslides has become a major concern in mountainous areas, it is a key component of manager policies efforts in disaster prevention, mitigate risk and manage the consequences. The region of Al Hoceima is one of most mountain regions in Morocco, and is highly exposed landslides events. For this reason, the area was selected in order to determine its susceptibility to landslides using two methods. The purpose of this study is to evaluate and to compare the results of multivariate (logical regression) and bivariate (landslide susceptibility) methods in Geographical Information System (GIS) based landslide susceptibility assessment procedures. In order to achieve this goal, the selected methods were compared by the Seed Cell Area Indexes (SCAI) and by the spatial locations of the resultant susceptibility pixels. We found that both of the methods converge in 80% of the area; however, the weighting algorithm in the bivariate technique (landslide susceptibility method) had some severe deficiencies, as the resultant hazard classes in overweighed areas did not converge with the factual landslide inventory map. The result of the multivariate technique (logical regression) was more sensitive to the different local features of the test zone and it resulted in more accurate and homogeneous susceptibility maps. This information may have direct applications in landslides susceptibility research programs and can assist decision-makers in the implementation of preventive management strategies in the most sensitive areas.
Key words: Landslide susceptibility / Multivariate / Bivariate / Al Hoceima / Morocco
© 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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