FDRL: a data-driven algorithm for forecasting subsidence velocities in Himalayas using conventional and traditional soil features

FDRL: a data-driven algorithm for forecasting subsidence velocities in Himalayas using conventional and traditional soil features

Abstract Landslides are a frequent geohazard within the Himalayas, threatening human lives, infrastructure, and indigenous economies. Traditional subsidence velocity forecasting models, however, typically rely on either satellite remote sensing data or geotechnical parameters in isolation, which lim...

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Bibliographic Details
Main Authors: Sahil Sankhyan, Ajoy Kumar, Praveen Kumar, Aaditya Sharma, K. V. Uday, Varun Dutt
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Subsidence velocity forecasting
Rainfall-Induced landslides
Traditional soil indicators
InSAR deformation analysis
Machine learning in geohazards
Stacking ensemble regression
Online Access:https://doi.org/10.1038/s41598-025-12932-5
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https://doi.org/10.1038/s41598-025-12932-5

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