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A critical review on landslide susceptibility zonation: recent trends, techniques, and practices in Indian Himalaya

Author

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  • Suvam Das

    (Academy of Scientific and Innovative Research (AcSIR)
    CSIR-Central Building Research Institute)

  • Shantanu Sarkar

    (Academy of Scientific and Innovative Research (AcSIR)
    CSIR-Central Building Research Institute)

  • Debi Prasanna Kanungo

    (Academy of Scientific and Innovative Research (AcSIR)
    CSIR-Central Building Research Institute)

Abstract

The Indian Himalayan region is highly susceptible to landslides because of its complex geology, rugged topography, steep slopes augmented by seismo-tectonic activities and heavy rainfalls, and often causes life losses with huge economic damages. Therefore, landslide susceptibility zonation (LSZ) mapping provides an effective solution for the end-users to estimate the vulnerability level and determine potential consequences. To date, different methodological frameworks have been implemented in terms of spatial modelling and predict future landslide locations for meeting these needs. Hence, it is necessary and meaningful to conduct a review of the current state of the studies addressed to LSZ mapping in the Indian Himalayan region. Based on this, the present paper reviews 144 research articles published in the last decade (2010–2020) to understand the recent trends, techniques and practices adopted by researches. Along with the review process, some critical points are emphasized with short- and long-term visions based on the issues discussed by various researchers; thereby, we try to ensure that this review work presents a more general deliberation of LSZ mapping which may also be relevant for global practitioners. At the same time this review also serves as a relevant database for scientist and researchers working in the field of landslide particularly in the Himalayan region.

Suggested Citation

  • Suvam Das & Shantanu Sarkar & Debi Prasanna Kanungo, 2023. "A critical review on landslide susceptibility zonation: recent trends, techniques, and practices in Indian Himalaya," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(1), pages 23-72, January.
  • Handle: RePEc:spr:nathaz:v:115:y:2023:i:1:d:10.1007_s11069-022-05554-x
    DOI: 10.1007/s11069-022-05554-x
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    References listed on IDEAS

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    1. D. Kanungo & S. Sarkar & Shaifaly Sharma, 2011. "Combining neural network with fuzzy, certainty factor and likelihood ratio concepts for spatial prediction of landslides," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 59(3), pages 1491-1512, December.
    2. Yang Hong & Robert Adler & George Huffman, 2007. "Use of satellite remote sensing data in the mapping of global landslide susceptibility," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 43(2), pages 245-256, November.
    3. R. Sharma & B. Mehta, 2012. "Macro-zonation of landslide susceptibility in Garamaura-Swarghat-Gambhar section of national highway 21, Bilaspur District, Himachal Pradesh (India)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 60(2), pages 671-688, January.
    4. Amit Bera & Bhabani Prasad Mukhopadhyay & Debasish Das, 2019. "Landslide hazard zonation mapping using multi-criteria analysis with the help of GIS techniques: a case study from Eastern Himalayas, Namchi, South Sikkim," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 96(2), pages 935-959, March.
    5. D. Ramakrishnan & T. Singh & A. Verma & Akshay Gulati & K. Tiwari, 2013. "Soft computing and GIS for landslide susceptibility assessment in Tawaghat area, Kumaon Himalaya, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(1), pages 315-330, January.
    6. Guru Balamurugan & Veerappan Ramesh & Mangminlen Touthang, 2016. "Landslide susceptibility zonation mapping using frequency ratio and fuzzy gamma operator models in part of NH-39, Manipur, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 465-488, October.
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