Landslide susceptibility mapping by using fuzzy logic: a case study of Cham-gardalan catchment, Ilam, Iran

Rostami, Zabih Alah; Almodaresi, Seyed Ali; Fathizad, Hassan; Faramarzi, Marzban

doi:10.1007/s12517-016-2720-3

Cited by 12 publications

(4 citation statements)

References 6 publications

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“…The geomorphological element is the most notable phenomenon which plays an important role in landslides [55]. The high peak in the study area appears in the north-western part.…”

Section: Geologicalmentioning

confidence: 89%

“…Geological map of the study area was collected from the Geological Survey of India (GSI). The boundaries of geological segment and names of the geological unit were used in previous studies [34,43,55,56]. This region is dissected into numerous small ridges, spurs, deep 'V'-shaped valleys and other erosional features.…”

Section: Geologicalmentioning

confidence: 99%

“…Another important, promising and functional variable is the distance from the river for landslide occurrences [43,45,47]. Howard (1997) notified that isolation is a limited model, which influences the dominant hills-shield transportation process in relation to distance from the river and mean decay rates, through a threshold presence or absence for landslides and climate corrosion [55,56]. The distance from the river was divided into 5 categories where an interval of 500 m was taken into account [36,[55][56][57][58][59][60] (Fig.…”

Section: Distance From the Rivermentioning

confidence: 99%

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Geo-spatial approach-based landslide susceptibility mapping using analytical hierarchical process, frequency ratio, logistic regression and their ensemble methods

2020

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Kurseong municipality and its surrounding hill slope are famous high altitudinal residential areas in the Darjeeling Himalayan region of India. In Darjeeling Himalayas, huge landslides occur in the rainy season every year. This paper was aimed to delineate landslide susceptibility zone (LSZ) in Kurseong and its surrounding hill slope in Darjeeling Himalayas. Nine landslide inducing parameters (i.e., slope, altitude, rainfall, geological structure, distance from river channels, distance from lineament, soil type or characteristics, land-use/land-cover and aspect) were used for mapping LSZ applying analytic hierarchy process (AHP), frequency ratio (FR), binary logistic regression (BLR) models and their ensemble (AHP-FR; AHP-BLR; and FR-BLR) with the aid of ArcGIS, SPSS and ERDAS software. The landslide susceptible maps produced in GIS environment by the AHP, FR, BLR and their ensemble models were classified into five susceptibility classes such as very low, low, moderate, high and very high. The area under curve (AUC) of receiver operating characteristics (ROC) and kappa statistics were used to analyze the accuracy of the LSZ maps. The AUC values of prepared maps were 78.86% (AHP), 80.22% (FR), 80.67% (BLR), 83.44% (AHP-FR), 84.39% (AHP-BLR) and 84.73% (FR-BLR). Overall kappa statistics were 0.789 (AHP), 0.812 (FR), 0.799 (BLR), 0.837 (AHP-FR), 0856 (AHP-BLR) and 0.868 (FR-BLR), indicating the good accuracy of the models. The mapping of LSZ will be useful for land-use planning and future landslide hazard mitigation strategies.

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“…The geomorphological element is the most notable phenomenon which plays an important role in landslides [55]. The high peak in the study area appears in the north-western part.…”

Section: Geologicalmentioning

confidence: 89%

Section: Geologicalmentioning

confidence: 99%

Section: Distance From the Rivermentioning

confidence: 99%

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Geo-spatial approach-based landslide susceptibility mapping using analytical hierarchical process, frequency ratio, logistic regression and their ensemble methods

2020

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“…Applying the GAMMA operator improved accuracy and reduced the high sensitivity of fuzzy multiplication. and the low accuracy of addition operators (Rostami et al 2016). The landslide susceptibility map shows that the majority of landslides (84%) are found in the high and very high susceptibility classes, while only 1.4% of landslides are located in the low susceptibility class (only 4 landslides).…”

Section: Expert Evaluationmentioning

confidence: 99%

Landslide susceptibility mapping by Frequency Ratio and Fuzzy logic approach, a case study of Mogods and Hedil (Northern Tunisia)

Klai

Katlane

Haddad

et al. 2023

Preprint

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The aim of this study is to produce a landslide susceptibility map in Mogods and Hedil using the fuzzy logic method. To increase the objectivity of the approach, the fuzzy membership was calculated using the frequency ratio (FR). Nine factors were considered for landslide control, including slope, aspect, plan curvature, profil curvature, distance from faults, distance from rivers, land use, precipitation, and lithology. The frequency ratio was used to calculate the fuzziness of each factor, and these results were then applied to the fuzzy operators to produce the landslide susceptibility map. The selection of the susceptibility map closest to reality was based on the spatial distribution of landslides in each susceptibility class of each fuzzy operator and on the application of the receiver operating curve (ROC). The results of the Area Under Curve (AUC) analysis show that the gamma operator (0.90) provided the most accurate prediction of the landslide susceptibility map, as indicated by the prediction accuracy of the model (0.766). The study area was classified into four classes using Jenks natural fracture classification method: low susceptibility zone, moderate susceptibility zone, high susceptibility zone and very high susceptibility zone. The use of the fuzzy gamma operator for landslide susceptibility mapping gave a very satisfactory result with a reliability rate of 76.6%.

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Landslide susceptibility mapping by using fuzzy logic: a case study of Cham-gardalan catchment, Ilam, Iran

Cited by 12 publications

References 6 publications

Geo-spatial approach-based landslide susceptibility mapping using analytical hierarchical process, frequency ratio, logistic regression and their ensemble methods

Geo-spatial approach-based landslide susceptibility mapping using analytical hierarchical process, frequency ratio, logistic regression and their ensemble methods

Landslide susceptibility mapping by Frequency Ratio and Fuzzy logic approach, a case study of Mogods and Hedil (Northern Tunisia)

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