RETRACTED: Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models

Shahabi, Himan; Khezri, Saeed; Ahmad, Baharin Bin; Hashim, Mazlan

doi:10.1016/j.catena.2013.11.014

Cited by 290 publications

(149 citation statements)

References 42 publications

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“…In the literature, the logistic regression method has been used widely to produce landslide susceptibility maps (i.e., Carrara et al 2008;Nefeslioglu et al 2008;Bai et al 2010;Pradhan 2010;Chauhan et al 2010;Atkinson and Massari 2011;Ramani et al 2011;Yalcın et al 2011;Akgun 2012;Choi et al 2012;Ozdemir and Altural 2013;Wang et al 2013;Althuwaynee et al 2014;Shahabi et al 2014). The first step of the logistic regression analyses was preparation of the data matrix.…”

Section: Landslide Susceptibility Mapping Of Two Sampling Strategiesmentioning

confidence: 99%

Modification of seed cell sampling strategy for landslide susceptibility mapping: an application from the Eastern part of the Gallipoli Peninsula (Canakkale, Turkey)

Dağdelenler

Nefeslioğlu

Gökçeoğlu

2015

Bull Eng Geol Environ

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In the literature, different sampling strategies (such as landslide area, seed cell, scarp, point) have been applied to landslide susceptibility mapping studies. Landslide sampling strategy should reflect the pre-failure conditions of failures. Hence, researchers tried to develop sampling methods to provide pre-failure conditions. The main purpose of this study was to modify the seed cell sampling strategy for landslide susceptibility evaluations. Furthermore, landslide susceptibility maps were produced using two different sampling strategies (seed cell and landslide area), and compared in terms of their results. In accordance with these purposes, the eastern part of the Gallipoli Peninsula (Canakkale, Turkey) was selected as the study area in which to apply these two sampling strategies. For the seed cell sampling strategy, different random samplings were prepared by considering different buffer distances and different spatial resolutions. Sensitivity analyses were carried out using the landslide area (with depletion and accumulation zones) and samples and seed cells were acquired from different buffer zones with respect to different resolutions. The spatial performance of the landslide susceptibility maps of both sampling strategies were evaluated using area under the ROC curve (AUC) values. The resulting AUC results obtained from different random samplings and different spatial resolutions indicated that the appropriate buffer distance used to produce seed cells for the evaluation of landslide susceptibility maps in medium scale should be approximately 50 m.

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Section: Landslide Susceptibility Mapping Of Two Sampling Strategiesmentioning

confidence: 99%

Modification of seed cell sampling strategy for landslide susceptibility mapping: an application from the Eastern part of the Gallipoli Peninsula (Canakkale, Turkey)

Dağdelenler

Nefeslioğlu

Gökçeoğlu

2015

Bull Eng Geol Environ

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“…Increasing trend of urbanization and overuse of natural resources has exacerbated this phenomenon (Ercanoglu and Gokceoglu, 2004). Landslides are known as one the most common geological disasters which cause damages and casualties worldwide (Bianchini et al, 2016;Shahabi et al, 2014;Wang et al, 2016). The unplanned urbanization especially in developing countries and wide climate changes through global warming increase the risk of natural hazards.…”

Section: Introductionmentioning

confidence: 99%

COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING

Mijani

Samani

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Landslide is one of the main geomorphic processes which effects on the development of prospect in mountainous areas and causes disastrous accidents. Landslide is an event which has different uncertain criteria such as altitude, slope, aspect, land use, vegetation density, precipitation, distance from the river and distance from the road network. This research aims to compare and evaluate different fuzzy-based models including Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), Fuzzy Gamma and Fuzzy-OR. The main contribution of this paper reveals to the comprehensive criteria causing landslide hazard considering their uncertainties and comparison of different fuzzy-based models. The quantify of evaluation process are calculated by Density Ratio (DR) and Quality Sum (QS). The proposed methodology implemented in Sari, one of the city of Iran which has faced multiple landslide accidents in recent years due to the particular environmental conditions. The achieved results of accuracy assessment based on the quantifier strated that Fuzzy-AHP model has higher accuracy compared to other two models in landslide hazard zonation. Accuracy of zoning obtained from Fuzzy-AHP model is respectively 0.92 and 0.45 based on method Precision (P) and QS indicators. Based on obtained landslide hazard maps, Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR respectively cover 13, 26 and 35 percent of the study area with a very high risk level. Based on these findings, fuzzy-AHP model has been selected as the most appropriate method of zoning landslide in the city of Sari and the Fuzzygamma method with a minor difference is in the second order.

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“…Assessing and mapping landslide susceptibility is an established practice, often aimed at comparing different predictive methods, which offers the possibility for a dynamic, integrated and on-going management of the territory and its sudden modifications (Devkota et al 2013;Kavzoglu et al 2014;Pellicani, Frattini & Spilotro 2014;Shahabi et al 2014;Pham et al 2016). On the contrary, quantifying, in mathematical terms, the landslide risk can be very complicated, due to several aspects, related to the complexity in assessing the temporal probability of a specific landslide event with given intensity (hazard) and the probability of damaging a given element at risk, i.e.…”

Section: Introductionmentioning

confidence: 99%

GIS-based predictive models for regional-scale landslide susceptibility assessment and risk mapping along road corridors

Pellicani

Argentiero

Spilotro

2017

Geomatics, Natural Hazards and Risk

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In this paper, a study aimed to assess the landslide susceptibility at a regional scale for the wide provincial territory of Matera (Basilicata region, southern Italy) and the relative risk along the main road corridors distributed in this area is presented. A heuristic-bivariate statistical predictive model was performed to assess and map the landslide susceptibility in the study area by using a polynomial function of eight predisposing factors, weighted according to their influence on the instability process. The resulting susceptibility map was successively used for assessing the landslide risk along the provincial road network. The importance of these roads, representing the main network connecting the urban centres, derives from the absence of an efficient integrated transportation system through the entire regional territory. The landslide risk was evaluated through a matricial approach, which has allowed to define the risk levels (low, medium and high) along road stretches by overlapping the consequences and hazard maps, by combining their corresponding classes in a matrix and by associating to each combination a risk level. The resulting landslide risk map provides support information for decision-making and for identifying the priorities for the design of appropriate mitigation plans.

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RETRACTED: Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models

Cited by 290 publications

References 42 publications

Modification of seed cell sampling strategy for landslide susceptibility mapping: an application from the Eastern part of the Gallipoli Peninsula (Canakkale, Turkey)

Modification of seed cell sampling strategy for landslide susceptibility mapping: an application from the Eastern part of the Gallipoli Peninsula (Canakkale, Turkey)

COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING

GIS-based predictive models for regional-scale landslide susceptibility assessment and risk mapping along road corridors

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