Geomorphic Risk Reduction Using Geospatial Methods and Tools

Landslide Susceptibility Assessment Based on Machine Learning Techniques.- Measuring landslide susceptibility in Jakholi region of Garhwal Himalaya applying novel ensembles of statistical and machine learning algorithms.- Landslide Susceptibility Mapping using GIS-based Frequency Ratio, Shannon Entropy, Information Value and Weight-of-Evidence approaches in part of Kullu district, Himachal Pradesh, India.- An advanced hybrid machine learning technique for assessing the susceptibility to landslides in the Meenachil river basin of Kerala, India.- Novel ensemble of M5P and Deep learning neural network for predicting landslide susceptibility: A cross-validation approach.- Artificial neural network ensemble with General linear model for modeling the Landslide Susceptibility in Mirik region of West Bengal, India.- Modeling gully erosion susceptibility using advanced machine learning method in Pathro River Basin, India.- Quantitative Assessment of Interferometric Synthetic Aperture 2 Radar(INSAR) for Landslide Monitoring and Mitigation.- Assessment of Landslide Vulnerability using Statistical and Machine Learning Methods in Bageshwar District of Uttarakhand, India.- Assessing the shifting of the River Ganga along Malda District of West Bengal, India.- An ensemble of J48 Decision Tree with AdaBoost, and Bagging for flood susceptibility mapping in the Sundarban of West Bengal, India.- Assessment of mouza level flood resilience in lower part of Mayurakshi River basin, Eastern India.- Spatial flashflood modeling in Beas River Basin of Himachal Pradesh, India using GIS-based machine learning algorithms.- Geospatial study of river shifting and erosion deposition phenomenon along a selected stretch of River Damodar, West Bengal, India.- An Evaluation of Hydrological Modeling Using CN Method in Ungauged Barsa River Basin of Pasakha, Bhutan.- The Adoption of Random Forest (RF) and Support Vector Machine (SVM) with Cat Swarm Optimization (CSO) to Predict the Soil Liquefaction.

Dr. Raju Sarkar is a professor in the Department of Civil Engineering, Delhi Technological University (DTU). Prior to returning to his parent organization, DTU, Dr. Sarkar was a professor in the Department of Civil Engineering and Architecture, College of Science and Technology, Royal University of Bhutan (RUB), under the Ministry of External Affairs, Government of India on deputation to Bhutan. During his tenure in Bhutan, he established the Center for Disaster Risk Reduction and Community Development Studies and also worked as the team leader to start the new undergraduate programme of Engineering Geology in the RUB. Currently, he is also the Chair of the Commission on Education and Outreach and the Co-chair of the Commission on Earthquake Hazard, Risk and Strong Ground Motion in the International Association of Seismology and Physics of the Earth's Interior (IASPEI)-IUGG. He has vast experience in working in the Hindu-Kush Himalayas region both at the government and community level. He has published many original research articles in peer-reviewed journals, books, book chapters and proceedings of international societies, and he serves as an editorial member of several journals. Prof. Sarkar is collaborating in a number of research projects funded by the International Science Council (ISC), the World Bank and NERC-GCRF among others. He has a keen interest in geotechnics for natural disaster mitigation, geohazards risk management, landslides, seismology, community resilience against cataclysmic events, vulnerability and risk assessment and disaster management education. 



Dr. Sunil Saha is an assistant professor of geography at the University of Gour Banga, India, and is specialized in the field of environmental geography. His research interests include fluvial landforms, natural hazards (gully erosion, landslides and floods), surface and sub-surface hydrological conditions and their impacts on land use in regard to both time and space. He is