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  1. No Access

    Article

    Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region

    This research aims to generate a landslide susceptibility map (LSM) for the Bhagirathi river basin located in the Tehri Garhwal district of Uttarakhand state in India. For this study, we incorporated and utili...

    Sunil Saha, Anik Saha, Tusar Kanti Hembram… in Stochastic Environmental Research and Risk… (2022)

  2. No Access

    Chapter

    Predicting the Landslide Susceptibility in Eastern Sikkim Himalayan Region, India Using Boosted Regression Tree and REPTree Machine Learning Techniques

    In the mountainous parts of the world, landslides are considered as the most dangerous to people and property. The number and the amount of damage caused by landslides have been steadily growing globally. As a...

    Kanu Mandal, Sunil Saha, Sujit Mandal in Applied Geomorphology and Contemporary Issues (2022)

  3. No Access

    Article

    Modeling and map** landslide susceptibility zones using GIS based multivariate binary logistic regression (LR) model in the Rorachu river basin of eastern Sikkim Himalaya, India

    Multivariate binary logistic regression (LR) model was used for the assessment of landslide susceptibility in the Rorachu river basin of eastern Sikkim Himalaya. For this purpose, a spatial database of 13 fact...

    Sujit Mandal, Kanu Mandal in Modeling Earth Systems and Environment (2018)

  4. No Access

    Article

    Bivariate statistical index for landslide susceptibility map** in the Rorachu river basin of eastern Sikkim Himalaya, India

    The main goal of the study is to prepare a landslide susceptibility map under Geographical Information System (GIS) environment using statistical index model to identify and demarcate the areas of future lands...

    Sujit Mandal, Kanu Mandal in Spatial Information Research (2018)