Abstract
During the past two decades (2000–2020) many studies have been conducted to build strategies as preventing landslides. Most of these approaches are focusing on different methods (statistical, mathematical, and machine learning…etc.) for the same study area. In the present research, we are benchmarking the results of our approach at two different geographical areas by using the Frequency Ratio (FR). First, we are comparing robustness between two susceptibility assessments for smaller areas such as Ceuta (257 Km2) and Tétouan-Ras-Mazari (590 Km2) to find out their similarities and their differences. Second, for both areas, we are utilizing the same controlling factors e.g., lithology, landuse, fault density, drainage density, slope degrees, slope aspects, and elevation. Third, we calculated the Prediction Rates (PR) of all factors. Fourth, our results show that three factors (Landuse, Elevation, Lithology for Area-1; in addition to, landuse, elevation, and fault density for Area-2 are sufficient for establishing acceptable LSAs for each area. Fifth, the evaluation process for the models is assessed by Areas Under the Curve (AUC). The accuracy of Models-I is 78.55% and Model- II is 79.25%. Last, our strategy could be an asset for our successors interested in Landslide Susceptibility Assessments (LSAs) in mountains MENA regions.
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Acknowledgments
The authors are extremely grateful and thankful to:
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Dr. Olivier DEBAUCHE, Senior Researcher at Department of Computer Science, Faculty of Engineering, University of Mons, Belgium; for his unconditional support on the computing and calculation processes of this research.
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Dr. Arnaud J TEMME, Associate Professor at Department of Geography and Geospatial Sciences, Kansas State University, USA; for his guidance and direction on the reasoning process, to tackle the current work, and find out an equilibrium between what is desired to be published and the availability of our data.
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Dr. Omar F. ALTHUWAYNEE, Post-doctoral Fellow at Department of Energy and Mineral Resources Engineering, Sejong University, South Korea; for granting free access to his online course to test our results.
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Elmoulat, M., Ait Brahim, L. (2022). A Selected Benchmark for Landslides Susceptibility Assessments in Northern Morocco. In: Al Saud, M.M. (eds) Applications of Space Techniques on the Natural Hazards in the MENA Region. Springer, Cham. https://doi.org/10.1007/978-3-030-88874-9_19
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DOI: https://doi.org/10.1007/978-3-030-88874-9_19
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