Abstract
Landslides are one of the major natural hazards that are experienced in hilly terrains all over the world and Himalayas are no exception to this. Though primarily attributed to natural causes, landslides are increasing in frequency and magnitude due to anthropogenic disturbances. This has resulted in enormous damage to both life and property. Hence, identification of landslide prone areas is essential for safer strategic planning of future developmental activities. A landslide hazard zonation (LHZ) map is generated by multi-criteria evaluation (MCE) of various responsible factors like slope, drainage, land use and land cover, lithology, soil and aspect which are weighted on the basis of their relative contribution to the occurrence of landslides. These weights are normalized such that the sum of normalized weights is equal to unity. The study area is divided into five zones based on the deciles of the normalized weights. The results reveal that 40% of the area falls under high LHZ which needs immediate engineering and agronomic measures. The MCE model presented in this study could be utilized for other mountainous regions in general and Himalayas in particular.
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Acknowledgements
Acknowledgements are due to Border Roads Organisation, Srinagar and various field departments for necessary data. Thanks are also to Dr. Gunter Dörhöfer Editor-in-Chief Environmental Earth Sciences, and anonymous reviewers for their valuable suggestions and comments which have greatly helped in improving upon the manuscript. Thanks are also due to Dr. Zahoor ul Islam and Dr. Mohammad Imran Malik, Department of Geography and Regional Development, University of Kashmir for his valuable suggestions and comments from time to time.
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Bhat, I.A., Shafiq, M.u., Ahmed, P. et al. Multi-criteria evaluation for landslide hazard zonation by integrating remote sensing, GIS and field data in North Kashmir Himalayas, J&K, India. Environ Earth Sci 78, 613 (2019). https://doi.org/10.1007/s12665-019-8631-3
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DOI: https://doi.org/10.1007/s12665-019-8631-3