LAUSR

Terrestrial laser scanning (TLS) is an important means to monitor landslides, and the layout is the key to guarantee captured point clouds with a high quality and low cost. Nevertheless, TLS layout in landslide monitoring is currently determined by user’s subjective experience and shows a poor performance in reliability and point accuracy. Therefore, we propose multiobjective optimization-based TLS layout planning for landslide monitoring. 3-D scanning simulation of candidate scan positions is first carried out. A multiobjective optimization problem (MOP) is then constructed according to the requirements of landslide TLS monitoring in the coverage, cost, and point accuracy. Finally, the combination of an improved nondominated sorting genetic algorithm II (NSGA-II) and the Pareto–Edgeworth–Grierson (PEG) algorithm is introduced to solve the MOP and obtain the optimal layout. To test the proposed method, experiments were performed in two landslide sites in Wuhan, China. Results showed that the planned TLS layouts reached a tradeoff among coverage, point accuracy, and the number of TLS scan positions. Comparison experiments based on simulation demonstrated that the constraints fused into NSGA-II dramatically improved the reliability of the planned TLS layout, and the proposed method improved the coverage and point accuracy by 11.62% and 1.52 times compared to the user’s experience. Real scanning demonstrated that the proposed method improved the coverage by 10.48% and reduced the deformation error by 0.78–7.66 mm compared to the user’s experience. In summary, the proposed method is an efficient approach for TLS layout planning, which can improve the ability of landslide TLS monitoring.