Development and Assessment of GIS-Based Landslide Susceptibility Mapping Models Using ANN, Fuzzy-AHP, and MCDA in Darjeeling Himalayas, West Bengal, India

Abhik Saha, Vasanta Govind Kumar Villuri () and Ashutosh Bhardwaj
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Abhik Saha: Department of Mining Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India
Vasanta Govind Kumar Villuri: Department of Mining Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India
Ashutosh Bhardwaj: Photogrammetry and Remote Sensing Department, Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun 248001, India

Land, 2022, vol. 11, issue 10, 1-27

Abstract: Landslides, a natural hazard, can endanger human lives and gravely affect the environment. A landslide susceptibility map is required for managing, planning, and mitigating landslides to reduce damage. Various approaches are used to map landslide susceptibility, with varying degrees of efficacy depending on the methodology utilized in the research. An analytical hierarchy process (AHP), a fuzzy-AHP, and an artificial neural network (ANN) are utilized in the current study to construct maps of landslide susceptibility for a part of Darjeeling and Kurseong in West Bengal, India. On a landslide inventory map, 114 landslide sites were randomly split into training and testing with a 70:30 ratio. Slope, aspect, profile curvature, drainage density, lineament density, geomorphology, soil texture, land use and land cover, lithology, and rainfall were used as model inputs. The area under the curve (AUC) was used to examine the models. When tested for validation, the ANN prediction model performed best, with an AUC of 88.1%. AUC values for fuzzy-AHP and AHP are 86.1% and 85.4%, respectively. According to the statistics, the northeast and eastern portions of the study area are the most vulnerable. This map might help development in the area by preventing human and economic losses.

Keywords: landslide susceptibility mapping; multi-criteria decision analysis; fuzzy-analytical hierarchy process; artificial neural network; Darjeeling Himalayas (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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