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Soft computing and GIS for landslide susceptibility assessment in Tawaghat area, Kumaon Himalaya, India

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  • D. Ramakrishnan
  • T. Singh
  • A. Verma
  • Akshay Gulati
  • K. Tiwari

Abstract

This paper mainly presents a case study of landslide vulnerability zonation along Tawaghat-Mangti route corridor in Kumaon Himalaya, India. An attempt is made to predict landslide susceptibility using back-propagation neural network (BPNN) and propose a suitable model for that zone, which can be successfully implemented for the prevention of slides. Various landslide affecting parameters such as lithology, slope, aspect, structure, geotechnical properties, land use, landslide inventory, and distance from recorded epicenter are used to model the landslide susceptibility. The database on the above parameters derived from satellite imageries, topographic maps, and field work are integrated in the GIS to generate an information layer. Database of this information layer is used to train, test, and validate the BPNN model. A three-layered BPNN with an input layer, two hidden layers, and one output layer is found to be optimal. The developed model demonstrates a promising result, and the prediction accuracy has been found to be 80 % in the field. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • 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.
    • Handle: RePEc:spr:nathaz:v:65:y:2013:i:1:p:315-330
    DOI: 10.1007/s11069-012-0365-4
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    References listed on IDEAS

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    1. T. Singh & A. Gulati & L. Dontha & V. Bhardwaj, 2008. "Evaluating cut slope failure by numerical analysis—a case study," 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. 47(2), pages 263-279, November.
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    Citations

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    1. Sahil Sardana & A. K. Verma & Rahul Verma & T. N. Singh, 2019. "Rock slope stability along road cut of Kulikawn to Saikhamakawn of Aizawl, Mizoram, 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. 99(2), pages 753-767, November.
    2. T. N. Singh & Rajbal Singh & Bhoop Singh & L. K. Sharma & Rajesh Singh & M. K. Ansari, 2016. "Investigations and stability analyses of Malin village landslide of Pune district, Maharashtra, 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. 81(3), pages 2019-2030, April.
    3. Shakti Suman & S. Z. Khan & S. K. Das & S. K. Chand, 2016. "Slope stability analysis using artificial intelligence techniques," 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(2), pages 727-748, November.
    4. Ashok Kumar Singh & Jagadish Kundu & Kripamoy Sarkar, 2018. "Stability analysis of a recurring soil slope failure along NH-5, Himachal 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. 90(2), pages 863-885, January.
    5. 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.
    6. Zaobao Liu & Jianfu Shao & Weiya Xu & Hongjie Chen & Yu Zhang, 2014. "An extreme learning machine approach for slope stability evaluation and prediction," 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. 73(2), pages 787-804, September.
    7. Daniel Smith & Thomas Oommen & Luke Bowman & John Gierke & Stanley Vitton, 2015. "Hazard assessment of rainfall-induced landslides: a case study of San Vicente volcano in central El Salvador," 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. 75(3), pages 2291-2310, February.
    8. 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.
    9. Dattatray Khamkar & Sainath Aher & Praveen Gawali & Sumedh Mhaske, 2022. "Investigating probable causes for predicting catastrophic landslides along NH-60 excavated through semi-arid basaltic terrain of Chandanapuri Ghat, Maharashtra, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2362-2386, February.

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