Landslide Susceptibility Mapping of Chamoli (Uttarakhand) Using Random Forest Machine Learning Method
- 4 May 2024
- book chapter
- Published by Springer Nature
- p. 207-217
Abstract
No abstract availableKeywords
This publication has 23 references indexed in Scilit:
- Probabilistic Arias Intensity Maps of Uttarakhand State (India)2023
- Probabilistic assessment of seismically triggered landslide hazard for Uttarakhand (India) in the Western HimalayasNatural Hazards, 2023
- Seismic Hazard Assessment of Kashmir Region Using Logic Tree Approach: Focus on Sensitivity of PSHA Results Towards Declustering Procedures and GMPEsPure and Applied Geophysics, 2023
- Probabilistic physical modelling and prediction of regional seismic landslide hazard in Uttarakhand state (India)Landslides, 2023
- Estimation of Arias intensity and peak ground acceleration (PGA) using probabilistic seismic hazard assessment of Uttarakhand state (India)Arabian Journal of Geosciences, 2022
- Developing a prototype landslide early warning system for Darjeeling Himalayas using SIGMA model and real-time field monitoringGeosciences Journal, 2021
- Impact of Main Boundary Thrust (MBT) on Landslide Susceptibility in Garhwal Himalaya: A Case StudyIndian Geotechnical Journal, 2021
- Forecasting Landslides Using Mobility Functions: A Case Study from Idukki District, IndiaIndian Geotechnical Journal, 2021
- Spatial clustering and modelling for landslide susceptibility mapping in the north of the Kathmandu Valley, NepalLandslides, 2020
- Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterizationLandslides, 2020