Abstract
Landslides are movement of rocks, debris or earth along a slope. There are seven states into which the activities of a landslide can be classified into; they are dormant, relict, suspended, reactivated, active and stabilized. Landslide susceptibility map is very crucial as it provides significant data and information that is required for planning of landslide-prone areas as it provides crucial information about spatial probability regarding the occurrence of landslide which is very important in the planning of land use. This paper provides a review of various studies and experiments conducted in this domain of research. The focus area of the study is Sikkim Himalayan region as it shares some similar type of parameters.
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Bhutia, S.L., Borah, S., Pradhan, R. (2020). Landslide Susceptibility Mapping: Development Towards a Machine Learning-Based Model. In: Sarma, H., Bhuyan, B., Borah, S., Dutta, N. (eds) Trends in Communication, Cloud, and Big Data. Lecture Notes in Networks and Systems, vol 99. Springer, Singapore. https://doi.org/10.1007/978-981-15-1624-5_13
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DOI: https://doi.org/10.1007/978-981-15-1624-5_13
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