Spatial correlation between the predictor variables and the weighting values calculated during the mapping of the environmental factors of mass movements in the Beni Idder region (northern Rif)

The Tleta of Beni Ider region located in the SW of Tetouan (Rif Septentrional) knows many mass instabilities. The diagnostic via the inventory, the mapping and the characterization of mass movements was made by using satellite imagery, aerial photography and field data coupled with existing documents (geological, geomorphological,…). The understanding of both their spatial distribution and the mechanism generating them, is very complex because of the existence of an important number of natural factors (geological, geomorphological, hydrological) in a relative mountainous landscape with deep valleys, steep slopes and significant elevation changes. Thus, a multidisciplinary approach was adopted to elaborate the landslide susceptibility map of the region taking into account interactions and causal relationships between the various natural parameters that tend to accentuate and aggravate the setting of landslides. The multidisciplinary database allowed us to evaluate the susceptibility thanks to a bivariate probabiliste model (Weight of Evidence). The obtained landslide susceptibility map is a major contribution to the development of urban development plans in the region.

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Mass movement susceptibility mapping - A comparison of logistic regression and Weight of evidence methods in Taounate-Ain Aicha region (Central Rif, Morocco)

MATEC Web of Conferences ◽

10.1051/matecconf/201814902094 ◽

2018 ◽

Vol 149 ◽

pp. 02094

Author(s):

A I JEMMAH ◽

L AIT BRAHIM

Keyword(s):

Land Use ◽

Logistic Regression ◽

Landslide Susceptibility ◽

National Development ◽

Susceptibility Mapping ◽

Weight Of Evidence ◽

Economic Losses ◽

Susceptibility Map ◽

Mass Movements ◽

Landslide Susceptibility Map

Taounate region is known by a high density of mass movements which cause several human and economic losses. The goal of this paper is to assess the landslide susceptibility of Taounate using the Weight of Evidence method (WofE) and the Logistic Regression method (LR). Seven conditioning factors were used in this study: lithology, fault, drainage, slope, elevation, exposure and land use. Over the years, this site and its surroundings have experienced repeated landslides. For this reason, landslide susceptibility mapping is mandatory for risk prevention and land-use management. In this study, we have focused on recent large-scale mass movements. Finally, the ROC curves were established to evaluate the degree of fit of the model and to choose the best landslide susceptibility zonation. A total mass movements location were detected; 50% were randomly selected as input data for the entire process using the Spatial Data Model (SDM) and the remaining locations were used for validation purposes. The obtained WofE’s landslide susceptibility map shows that high to very high susceptibility zones contain 62% of the total of inventoried landslides, while the same zones contain only 47% of landslides in the map obtained by the LR method. This landslide susceptibility map obtained is a major contribution to various urban and regional development plans under the Taounate Region National Development Program.

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Implementing Landslide Susceptibility Map at Watershed Scale of Lompobattang Mountain South Sulawesi, Indonesia

Indonesian Journal of Geography ◽

10.22146/ijg.16632 ◽

2018 ◽

Vol 50 (2) ◽

pp. 197

Author(s):

Abdul Rachman Rasyid ◽

Netra Prakash Bhandary ◽

Ryuichi Yatabe

Keyword(s):

Land Use ◽

Landslide Susceptibility ◽

Disaster Mitigation ◽

Weight Of Evidence ◽

Slope Aspect ◽

Susceptibility Map ◽

Watershed Scale ◽

Landslide Susceptibility Map ◽

Landslide Occurrence ◽

Predictive Rate

This study attempts to predict future landslide occurrence at watershed scale and calculate the potency of landslide for each sub-watershed at Lompobatang Mountain. In order to produce landslide susceptibility map (LSM) using the statistical model on the watershed scale, we identified the landslide with landslide inventories that occurred in the past, and predict the prospective future landslide occurrence by correlating it with landslide causal factors. In this study, six parameters were used namely, distance from fault, slope, aspect, curvature, distance from river and land use. This research proposed the weight of evidence (WoE) model to produce a landslide susceptibility map. Success and predictive rate were also used to evaluate the accuracy by using Area under curve (AUC) of Receiver operating characteristic (ROC). The result is useful for land use planner and decision makers, in order to devise a strategy for disaster mitigation.

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Applying weight of evidence method and sensitivity analysis to produce a landslide susceptibility map

Landslides ◽

10.1007/s10346-015-0576-3 ◽

2015 ◽

Vol 13 (2) ◽

pp. 379-397 ◽

Cited By ~ 63

Author(s):

Ioanna Ilia ◽

Paraskevas Tsangaratos

Keyword(s):

Sensitivity Analysis ◽

Landslide Susceptibility ◽

Weight Of Evidence ◽

Susceptibility Map ◽

Landslide Susceptibility Map

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Weights of evidence method for landslide susceptibility mapping in Tangier, Morocco

MATEC Web of Conferences ◽

10.1051/matecconf/201814902042 ◽

2018 ◽

Vol 149 ◽

pp. 02042

Author(s):

Mahfoud Bousta ◽

Lahsen Ait Brahim

Keyword(s):

Landslide Susceptibility ◽

Forest Cover ◽

Agricultural Land ◽

Weight Of Evidence ◽

Landslide Susceptibility Mapping ◽

Economic Losses ◽

Susceptibility Map ◽

Mass Movements ◽

Ground Truth Data ◽

Adopted Model

Tangier region is known by a high density of mass movements which cause several human and economic losses. The goal of this paper is to assess the landslide susceptibility of Tangier using the Weight of Evidence method (WofE). The method is founded on the principle that an event (landslide) is more likely to occur based on the relationship between the presence or absence of a predictive variable (predisposing factors) and the occurrence of this event. The inventory, description and analysis of mass movements were prepared. Then the main factors governing their occurrence (lithology, fault, slope, elevation, exposure, drainage and land use) were mapped before applying WofE. Finally, the ROC curves were established and the areas under curves (AUC) were calculated to evaluate the degree of fit of the model and to choose the best landslide susceptibility zonation. The prediction accuracy was found to be 70%. Obtained susceptibility map shows that 60% of inventoried landslides are in the high to very high susceptibility zones, which is very satisfactory for the validation of the adopted model and the obtained results. These zones are mainly located in the N-E and E part of the Tangier region in the soft and fragile facies of the marls and clays of the Tangier unit, where landuse is characterized by dominance of arable and agricultural land (lack of forest cover). From a purely spatial point of view, the localization of these two classes of susceptibility is completely corresponding to the ground truth data, that is to say that all the environmental and anthropogenic conditions are in place for making this area prone to landslide hazards. The obtained map is a decision-making tool for presenting, comparing and discussing development and urban scenarios in Tangier. These results fall within the context of sustainable development and will help to mitigate the socio-economic impacts usually observed when landslides are triggered.

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