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Geomorphic, Geo-tectonic, and Hydrologic Attributes and Landslide Probability

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Statistical Approaches for Landslide Susceptibility Assessment and Prediction

Abstract

Landslides are caused due to the prevalence of geomorphic, tectonic, and hydrologic parameters which changes slope materials state and force them to move down slope. Darjeeling Himalaya exhibits a wide range of all these parameters and as a result of which slope failure has become a quite common phenomena in every monsoon which inflicts a great damage to human lives and properties. To mitigate the landslides and its destructive nature, the relationship between landslides location and various landslides occurrence factors are to be analysed scientifically. In the present work, various data layers such as elevation, slope aspect, slope angle, slope curvature, geology, soil, lineament density, distance to lineament, drainage density, distance to drainage, stream power index (SPI), topographic wetted index (TWI), rainfall, normalized differential vegetation index (NDVI) and land use and land cover (LULC) were prepared in ARC GIS environment. To assess the probability of each class of the landslide causative factors, frequency ratio (FR) value was estimated considering both landslide affected pixels and landslide non-affected pixels. The derived frequency ratio established the relationship between the probability of landslide and each class of the landslide causative factor. The study revealed that steep slope zones; south, south-east, and south-west facing slope; high positive and high negative curvature areas; areas of weak lithology; places close to drainage; locations close to lineaments; high stream power index and high topographic wetness index areas; and land use character of wasteland dry/barren land, wastelands with scrub, forest, agricultural single crop and agricultural plantation are registered with high frequency ratio and high landslide probability.

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Authors and Affiliations

  1. Department of Geography, Diamond Harbour Women’s University, Sarisha, West Bengal, India

    Sujit Mandal

  2. University of Gour Banga, Mokdumpur, West Bengal, India

    Subrata Mondal

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  1. Sujit Mandal
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  2. Subrata Mondal
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Mandal, S., Mondal, S. (2019). Geomorphic, Geo-tectonic, and Hydrologic Attributes and Landslide Probability. In: Statistical Approaches for Landslide Susceptibility Assessment and Prediction. Springer, Cham. https://doi.org/10.1007/978-3-319-93897-4_2

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