Probabilistic Landslide risk assessment - Application to Eastern Rif (Morocco)

The present study is consecrated to the probabilistic mapping of the landslide risk at the local scale of an area that belongs to Al Hoceima city in the western Rif of Morocco. The study focuses mainly on the spatial analysis of multi sources data by using an environment GIS (Geographic Information...

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Main Authors: Mohamed RFIFI, Lahsen AIT BRAHIM
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Subjects:
Online Access:https://doi.org/10.1051/matecconf/201814902081
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author Mohamed RFIFI
Lahsen AIT BRAHIM
author_facet Mohamed RFIFI
Lahsen AIT BRAHIM
author_sort Mohamed RFIFI
collection DOAJ
description The present study is consecrated to the probabilistic mapping of the landslide risk at the local scale of an area that belongs to Al Hoceima city in the western Rif of Morocco. The study focuses mainly on the spatial analysis of multi sources data by using an environment GIS (Geographic Information Systems), and the application of the bivariate probabilistic model to qualify the risk susceptibility. The employed methodology is based on three stages. First, the evaluation of landslide susceptibility (S) by the analysis model cited before. Second, the identification and the estimation of the potential consequences (C) for the existing issues. Finally, the landslide risk (R) is evaluated by combining the susceptibility and the potential consequences map. This study requires the use of spatial analysis techniques. It also refers to the risk maps scale, generally reduced and being inappropriate at the urban project area. The obtained risk map defines four risk intensities with a spatial resolution of two meters.
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spelling doaj.art-c58c774945fa481ebf7c433fd7578f1e2022-12-21T18:11:27ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-011490208110.1051/matecconf/201814902081matecconf_cmss2018_02081Probabilistic Landslide risk assessment - Application to Eastern Rif (Morocco)Mohamed RFIFILahsen AIT BRAHIMThe present study is consecrated to the probabilistic mapping of the landslide risk at the local scale of an area that belongs to Al Hoceima city in the western Rif of Morocco. The study focuses mainly on the spatial analysis of multi sources data by using an environment GIS (Geographic Information Systems), and the application of the bivariate probabilistic model to qualify the risk susceptibility. The employed methodology is based on three stages. First, the evaluation of landslide susceptibility (S) by the analysis model cited before. Second, the identification and the estimation of the potential consequences (C) for the existing issues. Finally, the landslide risk (R) is evaluated by combining the susceptibility and the potential consequences map. This study requires the use of spatial analysis techniques. It also refers to the risk maps scale, generally reduced and being inappropriate at the urban project area. The obtained risk map defines four risk intensities with a spatial resolution of two meters.https://doi.org/10.1051/matecconf/201814902081LandslideProbabilistic mappingSusceptibilityConsequencesRiskGIS
spellingShingle Mohamed RFIFI
Lahsen AIT BRAHIM
Probabilistic Landslide risk assessment - Application to Eastern Rif (Morocco)
MATEC Web of Conferences
Landslide
Probabilistic mapping
Susceptibility
Consequences
Risk
GIS
title Probabilistic Landslide risk assessment - Application to Eastern Rif (Morocco)
title_full Probabilistic Landslide risk assessment - Application to Eastern Rif (Morocco)
title_fullStr Probabilistic Landslide risk assessment - Application to Eastern Rif (Morocco)
title_full_unstemmed Probabilistic Landslide risk assessment - Application to Eastern Rif (Morocco)
title_short Probabilistic Landslide risk assessment - Application to Eastern Rif (Morocco)
title_sort probabilistic landslide risk assessment application to eastern rif morocco
topic Landslide
Probabilistic mapping
Susceptibility
Consequences
Risk
GIS
url https://doi.org/10.1051/matecconf/201814902081
work_keys_str_mv AT mohamedrfifi probabilisticlandslideriskassessmentapplicationtoeasternrifmorocco
AT lahsenaitbrahim probabilisticlandslideriskassessmentapplicationtoeasternrifmorocco