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Landslide susceptibility zonation of the Chamoli region, Garhwal Himalayas, using logistic regression model

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Abstract

A remote sensing and Geographic Information System-based study has been carried out for landslide susceptibility zonation in the Chamoli region, part of Garhwal Himalayas. Logistic regression has been applied to correlate the presence of landslides with independent physical factors including slope, aspect, relative relief, land use/cover, lithology, lineament, and drainage density. Coefficients of the categories of each factor have been obtained and used to assess the landslide probability value to ultimately categorize the area into various landslide susceptibility zones; very low, low, moderate, high, and very high. The results show that 71.13% of observed landslides fall in 21.96% of predicted very high and high susceptibility zone, which in fact should be the case. Furthermore, lineament first buffer category (0–500 m) and the east and south aspects are the most influential in causing landslides in the region.

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Acknowledgments

This paper is an outcome of a landslide-based study under a Department of Science and Technology (DST)-sponsored research project, Government of India.

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Authors and Affiliations

  1. Geomatics Engineering Group, Department of Civil Engineering, Indian Institute of Technology, Roorkee, India

    Shivani Chauhan, Mukta Sharma & Manoj K. Arora

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  1. Shivani Chauhan
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  2. Mukta Sharma
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  3. Manoj K. Arora
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Correspondence to Manoj K. Arora.

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Chauhan, S., Sharma, M. & Arora, M.K. Landslide susceptibility zonation of the Chamoli region, Garhwal Himalayas, using logistic regression model. Landslides 7, 411–423 (2010). https://doi.org/10.1007/s10346-010-0202-3

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  • DOI: https://doi.org/10.1007/s10346-010-0202-3

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