Landslide Hazard, Vulnerability, and Risk Analysis (HVRA) Using Machine Learning and AI: A Case Study of the Darma Valley, Kumaun Himalaya, India

Mohd Shawez; Sandeep Kumar; Vikram Gupta; Parveen Kumar; Gautam Rawat

doi:https://doi.org/10.5194/egusphere-egu26-18022

[Back] [Session VPS12]

EGU26-18022, updated on 14 Mar 2026

https://doi.org/10.5194/egusphere-egu26-18022

EGU General Assembly 2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Landslide Hazard, Vulnerability, and Risk Analysis (HVRA) Using Machine Learning and AI: A Case Study of the Darma Valley, Kumaun Himalaya, India

Mohd Shawez^1,2, Sandeep Kumar¹, Vikram Gupta³, Parveen Kumar^1,2, and Gautam Rawat^1,2

Mohd Shawez et al.

¹Wadia Institute of Himalayan Geology, Dehradun (India), Geomorphology group, India (shawezk074@gmail.com)
²Academy of Scientific and Innovative Research, Ghaziabad, India
³Department of Geology, Sikkim University, Gangtok, India

How to cite: Shawez, M., Kumar, S., Gupta, V., Kumar, P., and Rawat, G.: Landslide Hazard, Vulnerability, and Risk Analysis (HVRA) Using Machine Learning and AI: A Case Study of the Darma Valley, Kumaun Himalaya, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18022, https://doi.org/10.5194/egusphere-egu26-18022, 2026.

This abstract has been withdrawn after no-show on 11 Aug 2026.