Landslide susceptibility assessment using analytic hierarchy process and weight of evidence methods in parts of the Rif chain (northernmost Morocco)

Es-smairi, Abderrazzak; Moutchou, Brahim El; Touhami, Abdelouahed El Ouazani

doi:10.1007/s12517-021-07660-9

Cited by 13 publications

(3 citation statements)

References 63 publications

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“…In the bivariate statistical analysis, the weighting values for each factor class are obtained by combining the landslide inventory map with each data layer of conditioning factors. The frequency ratio (Lee and Sambath 2006;Lee and Pradhan 2007;Aditian et al 2018;Sharma and Mahajan 2018;Shano et al 2021;Bourenane et al 2021b), information value (Van Westen 1997, the weight of evidence (Pourghasemi et al 2012b;Ilia and Tsangaratos 2016;Es-smairi et al 2021), and evidential belief function (Althuwaynee et al 2012;Pourghasemi et al 2016;Feby et al 2020) models are the most important bivariate statistical methods used in LSM. While, in multivariate statistical approaches, the weights of landslide conditioning factors are based on the relative contribution of each factor in the presence or absence of the landslide events within a defined pixel unit (Ayalew and Yamagishi 2005;Nandi and Shakoor 2009).…”

Section: Introductionmentioning

confidence: 99%

Integration of multi-criteria decision analysis and statistical models for landslide susceptibility mapping in the western Algiers province (Algeria) using GIS techniques and remote sensing data

MOKADEM

Lounis

Machane³

et al. 2023

Preprint

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Landslide susceptibility assessment and prediction are among the main processing for disaster management and land use planning activities. Therefore, the general purpose of this research was to evaluate GIS-based spatial modeling of landslides in the western Algiers province using five models, namely: frequency ratio (FR), weights of evidence (WoE), evidential belief function (EBF), logistic regression (LR) and analytical hierarchy process (AHP), then, compare their performances. At first, a landslide inventory map was prepared according to Google Earth satellite images, historical records, and extensive field surveys. The recorded landslides were divided into two groups (70% and 30%) to establish the training and validation models. In the next step, GIS techniques and remote sensing data were used, to prepare a spatial database containing thirteen landslide conditioning factors; lithology, distance to lithological boundaries, permeability, slope, exposure, altitude, profile curvature, plan curvature, precipitation, distance to rivers, TWI, NDVI, and distance to roads. Finally, the landslide susceptibility maps were produced using the five models and validated by the areas under the relative operative characteristic curve (AUC). The AUC results showed a significant improvement in susceptibility map accuracy, the FR model has the best performance in the training and prediction process (90%), followed by LR (88%, 89%), WoE (88%, 87%), EBF (86%,86%), and AHP (76%,75%), respectively. The produced maps in the current study could be useful for land use planning and hazard mitigation purposes in western Algiers province.

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Section: Introductionmentioning

confidence: 99%

Integration of multi-criteria decision analysis and statistical models for landslide susceptibility mapping in the western Algiers province (Algeria) using GIS techniques and remote sensing data

MOKADEM

Lounis

Machane³

et al. 2023

Preprint

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“…The combination effect of geological composition, landscapes complexity, abundant rainfall, seismic activity and the increasing magnitude of anthropogenic activities are considered the known framework of landslide conditioning factors at Rif scale (Millies-Lacroix1965; El Gharboui1980; Fares 1994;Es-smairi et al2021). Similar factors are active at the coastline between Tetouan and Bou-Ahmed and its hinterlands in addition to the action of Mediterranean sea that continuously undermines in downstream mountains extending into the sea resulting in instabilityand slope failure (Es-smairi et al 2021). The attracting geographical position of the coastlines and the hinterlands of the Rif domain, generally and more precisely covering our study area makes it more exposed to strong anthropogenic activitieslike the increasing housing and infrastructure development.…”

Section: Introductionmentioning

confidence: 99%

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

Es-smairi

Elmoutchou

Mir

et al. 2022

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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.

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“…Few studies have covered the study area (EL Fellah, 1994;El Fellah et al, 1996;Es-Smairi et al, 2021;Harmouzi et al, 2019;Mastere et al, 2017). The rst one is a preliminary reconnaissance site-speci c study and the last three works are landslide susceptibility assessing by ANN, AHP and Weight of evidence methods.…”

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confidence: 99%

Coastal rocky slopes instability analysis and landslide frequency-area distribution alongside the road network in west Mediterranean context (Northern of Morocco)

Obda

Kharim

Obda

et al. 2022

Preprint

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The Mediterranean coasts are known for their tourist attractiveness due to its richness in fishing resources and beach resorts as well as landscapes at the level of different ecosystems (forests, rocky and sandy beaches). The construction of the Mediterranean coastal road (RN16), which aims to enhance the tourist value of these resources and to improve access to this coastal region, has triggered an almost radical modification in the development process of this area, where the risks are increasing because of the multiplication of the challenges and the hazards due to the instability of its slopes. These events are mainly the result of marine erosion, the involvement of geological, geomorphological, climatic factors and also anthropic parameters with a strong littoralisation. The study area is characterized by active tectonics translated by the presence of faulting sets affecting the rock mass. The aim of this study is to assess the characteristics of the rock mass and its stability, and to anticipate landslide occurrence frequency with a particular size in a specified region with a certain rock mass quality as well. The methodology followed in this work consists of the elaboration of a complete inventory of landslides, the fracturation analysis and the rock mass engineering conducted to evaluate the stability of the slopes and the statistical analysis of the landslide size distribution. The combination of these two approaches has allowed us to assess qualitatively and quantitatively the landslide hazard on coastal rocky fractured areas.

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Landslide susceptibility assessment using analytic hierarchy process and weight of evidence methods in parts of the Rif chain (northernmost Morocco)

Cited by 13 publications

References 63 publications

Integration of multi-criteria decision analysis and statistical models for landslide susceptibility mapping in the western Algiers province (Algeria) using GIS techniques and remote sensing data

Integration of multi-criteria decision analysis and statistical models for landslide susceptibility mapping in the western Algiers province (Algeria) using GIS techniques and remote sensing data

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

Coastal rocky slopes instability analysis and landslide frequency-area distribution alongside the road network in west Mediterranean context (Northern of Morocco)

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