Abstract
Landslide susceptibility zonation (LSZ) is necessary for disaster management and planning development activities in mountainous regions. A number of methods, viz. landslide distribution, qualitative, statistical and distribution-free analyses have been used for the LSZ studies and they are again briefly reviewed here. In this work, two methods, the Information Value (InfoVal) and the Landslide Nominal Susceptibility Factor (LNSF) methods that are based on bivariate statistical analysis have been applied for LSZ mapping in a part of the Himalayas. Relevant thematic maps representing various factors (e.g., slope, aspect, relative relief, lithology, buffer zones along thrusts, faults and lineaments, drainage density and landcover) that are related to landslide activity, have been generated using remote sensing and GIS techniques. The LSZ derived from the LNSF method, has been compared with that produced from the InfoVal method and the result shows a more realistic LSZ map from the LNSF method which appears to conform to the heterogeneity of the terrain.
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Acknowledgements
A. K. Saha is grateful to the Council of Scientific and Industrial Research (CSIR), New Delhi, India, for Senior Research Fellowship. He is also thankful to German Academic Exchange Service (DAAD), Bonn for the award of DAAD Sandwich Fellowship, during which a part of this work was carried out at the Institute of Photogrammetry and Remote Sensing, Dresden University of Technology, Germany. Thanks are due to Dr. L. Ayalew, Department of Environmental Science, Niigata University, Japan and Dr. R. Anbalagan, Department of Earth Sciences, IIT Roorkee, India, for their valuable comments.
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Saha, A.K., Gupta, R.P., Sarkar, I. et al. An approach for GIS-based statistical landslide susceptibility zonation—with a case study in the Himalayas. Landslides 2, 61–69 (2005). https://doi.org/10.1007/s10346-004-0039-8
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DOI: https://doi.org/10.1007/s10346-004-0039-8