Early Detection of Slope Deformation Using Airborne LiDAR Monitoring

Understanding subsurface movement on slopes is crucial for ensuring the stability of geoinfrastructure. Traditional slope monitoring methods often fail to detect subtle subsurface movements in their early stages, leading to delayed intervention and increased risk of failure. This study presents an automated monitoring framework utilizing airborne Light Detection and Ranging (LiDAR) data acquisition for slope deformation analysis. The methodology involves conducting weekly aerial surveys using an Uncrewed Aerial Vehicle (UAV) equipped with LiDAR, systematically capturing detailed point cloud data of the target slope. The collected point clouds undergo processing to generate high-resolution surface models for deformation analysis. This high-frequency monitoring approach demonstrates innovative capability in early detection of slope instability compared to conventional methods. Preliminary findings highlight detectable shifts in surface elevation, which correlate with underlying soil movement. By integrating airborne LiDAR technology into routine geotechnical monitoring, this research advances the capabilities of predictive maintenance strategies, improving resilience and sustainability in geotechnical asset management.