Fusion of Terrestrial Laser Scanning and UAV Photogrammetry for Advanced Landslide Monitoring: Integrated Assessment of the Kshetrapal Landslide, Chamoli District, Uttarakhand, India

Abstract

This study presents an integrated TLS-UAV photogrammetry approach for monitoring the Kshetrapal landslide in Chamoli, Uttarakhand, India, where steep slopes (45˚ - 65˚) and dense vegetation challenge conventional methods. By combining terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry, the method enhances ground control point (GCP) density in visible areas while employing assumed control points (ACPs) derived from TLS data to reconstruct UAV models in obscured zones. The Newton integration model quantifies discrepancies between coordinate displacement (CD) and real displacement (RD), achieving sub-pixel accuracy (errors: 0.0235 - 0.8021 pixels) validated through field data. Key results include a 40% improvement in spatial coverage through TLS-UAV fusion, reduced RMSE to 0.2 m in fused point clouds, and detection of monsoon-induced displacements up to 1.7 m during the 2023 reactivation. The approach demonstrates 26% higher accuracy than traditional GCP-dependent methods in Himalayan conditions, offering a replicable framework for landslide risk management in geologically sensitive regions. Validated through multi-temporal datasets and real-world scenarios, this methodology addresses critical gaps in accessibility and precision, providing actionable insights for disaster management agencies like the Uttarakhand State Disaster Management Authority.