Spatial prediction of landslide susceptibility using Frequency Ration (FR) and Shannon Entropy (SE) models: a case study from northern Rif, Morocco.

Résumé

Abstract In this study, a methodology for mapping and identifying the areas prone to landslides as well as to predict and reduce their impacts has been develop in the coastline between Tetouan-BouAhmed and its hinterlands, North Morocco. The area in the context of geological, morphological, climatic, seismic, and anthropogenic conditions is extremely favoring landslide occurrences. The trend of this phenomenon is expected to be growing over a course of time due to exceptional increasing rain events in response to climate change. A booming development of infrastructure and large quarrying activity, at the cost of forests on mountainous areas are strongly predisposed to mass movements. Their consequences are extremely large on various components such as on road network, habitat, hydraulic and electrical lines, protective structures, forest and vegetation systems, agricultural lands, littoral coast etc. For evaluating the susceptibility of landslide occurrences, the approach consists integrating a set of multisource data in GIS platform using Frequency Ration (FR) and Shannon Entropy (SE) models. For building these models, a total of 905 unstable slopes and eleven landslides causative factors were utilized based on multicollinearity test. Results of validation showed good prediction ability (> 76%) for both the models. However, the accuracy prediction indicated that the FR is about 3% more precise than SE model. More than 60% of the area is classified as dangerous that is prone to high landslide activities. The study may be of great importance to the managers and regulatory bodies for devising the guidelines for prevention, assessment, management and sustainable development in this region.

Citer ce document

Accès au document

Ce document est hébergé sur son dépôt institutionnel d'origine.

Auteur(s)

Statistiques

Consultations : 1

Téléchargements : 0