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- W4381095031 abstract "The Mountainous terrain is experiencing rapid development in a bewildering manner, which makes it more susceptible to landslides. Management and mitigation of landslide hazard begin with its mapping by integrating numerous methods and Geographic Information System (GIS) tools. However, it is difficult to produce reliable landslide susceptibility maps (LSM) due to their complex nature. Therefore, the present study investigates the applicability of Mamdani’s fuzzy inference system (FIS) to produce LSM in Himalayan terrain in India. It is compared with commonly used frequency ratio (FR) and information value method (IVM) approaches. Several causative factors were extracted and used to prepare thematic layers, including slope, aspect, curvature, solar radiance, SPI, TWI, rainfall, soil depth and NDVI. Landslide inventory was also created using google earth images and previously published work. The accuracy estimates for FR, IVM and FIS were performed based on ROC curves. FIS was found to provide an accuracy of 77.7%, followed by IVM (72%) and FR (71%) for LSM. The current study is a prototype for further studies in the Garhwal Himalayas and similar terrains, based on the vigorous Mamdani’s techniques of fuzzy inference theory. The outcomes of this work propose that an expert’s knowledge-based FIS method can produce an accurate LSM in such a complex terrain. Planners and concerned authorities can use the results further for landslide management and mitigation." @default.
- W4381095031 created "2023-06-18" @default.
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- W4381095031 date "2023-06-01" @default.
- W4381095031 modified "2023-10-03" @default.
- W4381095031 title "Rule-based fuzzy inference system for landslide susceptibility mapping along national highway 7 in Garhwal Himalayas, India" @default.
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- W4381095031 doi "https://doi.org/10.1016/j.qsa.2023.100093" @default.
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