Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: A case study from the Tinau watershed, west Nepal

Kayastha, Prabin; Dhital, Megh Raj; Smedt, Florimond De

doi:10.1016/j.cageo.2012.11.003

Cited by 456 publications

(203 citation statements)

References 45 publications

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“…Using Bayes learning and logistic regression to predict debris flows in southwest Sichuan, China, Xu et al [22] pointed out that both methods have disadvantages: Bayes requires some variable assumptions that are difficult to be completely met in practice, whereas logistic regression needs large samples for the iterative calculation to obtain stable model parameters. Other methods such as weight of evidence [23,24] and analytic hierarchy process [25,26] have also been used for susceptibility analysis. The spatial results of these approaches are generally appealing, and they give rise to qualitative and quantitative mapping of the threatened areas [27].…”

Section: Study Areamentioning

confidence: 99%

Debris Flow Susceptibility Assessment in the Wudongde Dam Area, China Based on Rock Engineering System and Fuzzy C-Means Algorithm

Wang

Chen

et al. 2017

Water

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Debris flows in the Wudongde dam area, China could pose a huge threat to the running of the power station. Therefore, it is of great significance to carry out a susceptibility analysis for this area. This paper presents an application of the rock engineering system and fuzzy C-means algorithm (RES_FCM) for debris flow susceptibility assessment. The watershed of the Jinsha River close to the Wudongde dam site in southwest China was taken as the study area, where a total of 22 channelized debris flow gullies were mapped by field investigations. Eight environmental parameters were selected for debris flow susceptibility assessment, namely, lithology, watershed area, slope angle, stream density, length of the main stream, curvature of the main stream, distance from fault and vegetation cover ratio. The interactions among these parameters and their weightings were determined using the RES method. A debris flow susceptibility map was produced by dividing the gullies into three categories of debris flow susceptibility based on the susceptibility index (SI) using the FCM algorithm. The results show that the susceptibility levels for nine of the debris flow gullies are high, nine are moderate and four are low, respectively. The RES based K-means algorithm (RES_KM) was used for comparison. The results suggest that the RES_FCM method and the RES_KM method provide very close evaluation results for most of the debris flow gullies, which also agree well with field investigations. The prediction accuracy of the new method is 90.9%, larger than that obtained by the RES_KM method (86.4%). Therefore, the RES_FCM method performs better than the RES_KM method for assessing the susceptibility of debris flows.

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Section: Study Areamentioning

confidence: 99%

Debris Flow Susceptibility Assessment in the Wudongde Dam Area, China Based on Rock Engineering System and Fuzzy C-Means Algorithm

Wang

Chen

et al. 2017

Water

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“…Numerous landslide predictive factors have been used in producing spatial hazard maps in previous studies [8,9,14,19,20,30]. According to [31], these factors can be grouped into two types: (1) controlling factors that contribute to landslides potential, such as slope, lithology, topography, geology and hydrology; and (2) triggering factors, such as rainfall, earthquakes and human activities (e.g., excavation at the foot of slope, mining, etc.).…”

Section: Landslide Predictive Factormentioning

confidence: 99%

“…The qualitative approaches usually involve a high degree of subjectivity, because these approaches are built on the experts' knowledge and experience for ranking and weighting the landslide predictive factors. Typical examples of qualitative methods include inventory mapping, expert evaluation and the analytical hierarchy process (AHP) method [8][9][10][11]. Some semi-quantitative approaches also incorporate geomorphologic analysis and objectively ranked weights of predictive factors [8,12].…”

Section: Introductionmentioning

confidence: 99%

“…Two frequently used and already tested LSM methods, AHP and FR, are employed as the representative subjective and objective methods. The AHP is a multi-criteria methodology designed for hierarchical representation of a decision-making problem [24] and has gained wide application in LSM [9,11]. The AHP can be easily adopted in a GIS to facilitate the production of landslide susceptibility maps with powerful visualization and mapping capabilities [25].…”

Section: Introductionmentioning

confidence: 99%

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GIS-Based Integration of Subjective and Objective Weighting Methods for Regional Landslides Susceptibility Mapping

et al. 2016

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Abstract:The development of landslide susceptibility maps is of great importance due to rapid urbanization. The purpose of this study is to present a method to integrate the subjective weight with objective weight for regional landslide susceptibility mapping on the geographical information system (GIS) platform. The analytical hierarchy process (AHP), which is subjective, was employed to weight predictive factors' contribution to landslide occurrence. The frequency ratio (FR) method, which is objective, was used to derive subclasses' frequency ratio with respect to landslides that indicate the relative importance of a subclass within each predictive factor. A case study was carried out at Tsushima Island, Japan, using a historical inventory of 534 landslides and seven predictive factors: elevation, slope, aspect, terrain roughness index (TRI), lithology, land cover and mean annual precipitation (MAP). The landslide susceptibility index (LSI) was calculated using the weighted linear combination of factors' weights and subclasses' weights. The study area was classified into five susceptibility zones according to the LSI. In addition, the produced susceptibility map was compared with maps generated using the conventional FR and AHP method and validated using the relative landslide index (RLI). The validation result showed that the proposed method performed better than the conventional application of the FR method and AHP method. The obtained landslide susceptibility maps could serve as a scientific basis for urban planning and landslide hazard management.

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“…However, secondary-level weights are expert opinion-based weights (Ayalew et al 2004;Ahmed 2015). Among expert opinion methods for weights assignment, an analytic hierarchy process (AHP) is a technique which has been successfully applied to many decision maker systems (Kayastha et al 2013;. The AHP technique uses a pair-wise relative comparison between each LCF (Saaty 1980).…”

Section: Introductionmentioning

confidence: 99%

Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Pawłuszek

Borkowski

2016

Nat Hazards

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Choosing appropriate landslide-controlling factors (LCFs) in landslide susceptibility mapping (LSM) is a challenging task and depends on the nature of terrain and expert knowledge and experience. Nowadays, it is very common to use digital elevation model (DEM) and DEM-derivatives, as a representation of the topographic conditions. The objective of this study is to explore topography in depth and simultaneously reduce redundant information within DEM-derivatives using principal component analysis. Moreover, this study investigates the impact of DEM-derived factors on LSM. Therefore, three various strategies were tested. The first strategy included a set of LCFs created from the four initial principal components, which were provided from DEM-derived factors. The second strategy included a set of parameters which contained additional lithological and environmental factors. The third strategy utilises the analytical hierarchy process (AHP) to assign weights to each LCF. The LSM was performed based on landslide susceptibility index. Obtained results show that 60% of existing landslides fell into high and very high susceptibility zones using first and second strategies. It proves that topographic factors play a significant role in LSM. Adding additional lithological and environmental factors to the set of LCFs did not improve the results significantly, unless the AHP was used in the third strategy. It improved results significantly; up to 70%. Results from second and third strategies highlight utility of AHP in LSM. Presented studies were performed on the area very prone to landslide occurrence in the region of Ro_ znów Lake, Poland.

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Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: A case study from the Tinau watershed, west Nepal

Cited by 456 publications

References 45 publications

Debris Flow Susceptibility Assessment in the Wudongde Dam Area, China Based on Rock Engineering System and Fuzzy C-Means Algorithm

Debris Flow Susceptibility Assessment in the Wudongde Dam Area, China Based on Rock Engineering System and Fuzzy C-Means Algorithm

GIS-Based Integration of Subjective and Objective Weighting Methods for Regional Landslides Susceptibility Mapping

Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

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