Displacement monitoring and stability analysis of an artificial-fill landslide using terrestrial laser scanning

This study employs terrestrial laser scanning (TLS) to monitor deformation of an artificial‑fill landslide. We introduce a method for spatial deformation analysis. It relies on feature - based registration of multi-temporal 3D point cloud datasets. To evaluate the approach, data were acquired using a long-range terrestrial laser scanner at the Dingguanfeng landfill slope in Wuhan, China, and validated against data from Global Navigation Satellite System (GNSS) monitoring stations installed on the slope surface. After a series of preprocessing, the point clouds were aligned using both natural scene features and pre-arranged control points. The first-epoch point cloud was reconstructed into a polygonal mesh, while the second-epoch point cloud was orthorectified for cloud-to-mesh (C2M) deformation analysis, yielding a 3D displacement field. A three-dimensional, color-coded displacement map was generated to facilitate detailed interpretation of slope deformation. The results indicate that the Dingguanfeng artificial-fill landslide was generally stable, with two zones of anomalous displacement (>5 cm) detected in the lower and southern portions, consistent with GNSS observations. Compared with GNSS monitoring, the TLS-based method provides comparable accuracy while offering enhanced spatial detail. This study demonstrates the potential of TLS point cloud analysis for landfill slope monitoring and identifies directions for method standardization and error source mitigation.