Landslide susceptibility mapping in and around Mussoorie Township using fuzzy set procedure, MamLand and improved fuzzy expert system-A comparative study

Bipin Peethambaran (), R. Anbalagan and K. V. Shihabudheen
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Bipin Peethambaran: Indian Institute of Technology Roorkee
R. Anbalagan: Indian Institute of Technology Roorkee
K. V. Shihabudheen: Indian Institute of Technology Roorkee

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2019, vol. 96, issue 1, No 6, 147 pages

Abstract: Abstract A landslide susceptibility map (LSM) is an imperative element in the planning of sustainable development practices and geo-environmental conservations in mountainous terrains. In recent times, approaches that couple soft computing techniques and Geographic Information System (GIS) has emerged as better-suited models that can diminish the flaws and limitations of heuristic, probabilistic and distribution approaches in landslide susceptibility mapping. This paper presents an improved fuzzy expert system (FES) model, a fusion of Mamdani fuzzy inference system (Mamdani-FIS) and frequency ratio method for GIS-based landslide susceptibility mapping. The improved FES model has been applied for mesoscale (1:15,000) landslide susceptibility mapping of Mussoorie Township, Uttarakhand, India, along with conventional fuzzy set procedure (FSP) and an existing FES model, MamLand. The LSMs generated through different procedures have been validated and compared by means of spatial distribution of susceptibility zones and statistical analysis with the help of landslide inventory. The validation and comparative analysis have indicated the significantly better performance of the improved FES model over FSP and MamLand.

Keywords: Landslide susceptibility mapping; Geographic information system; Fuzzy set procedure; Mamdani-FIS; MamLand; Improved fuzzy expert system; Mussoorie Township (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11069-018-3532-4

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