Comparative analysis of surface deformation monitoring in a mining area based on <scp>UAV‐lidar</scp> and <scp>UAV</scp> photogrammetry
Xilin Zhan, Xingzhong Zhang, Xiao Wang, Xinpeng Diao, Lizhuan Qi
Abstract
Abstract Unmanned aerial vehicle light detection and ranging (UAV‐lidar) and unmanned aerial vehicle (UAV) photogrammetry are currently commonly used surface monitoring technologies. Previous studies have used the two technologies interchangeably and ignored their correlation, or only compared them on a single product. However, there are few quantitative assessments of the differences between these two techniques in monitoring surface deformation and prediction of their application prospects. Therefore, the paper compared the differences between the digital elevation model (DEM) and subsidence basins obtained by the two techniques using Gaussian analysis. The results indicate that the surface DEMs obtained by both the techniques exhibit a high degree of similarity. The statistical analysis of the difference values in the z direction between the two DEMs follows a Gaussian distribution with a standard deviation of less than 0.36 m. When comparing the surface subsidence values monitored by the two techniques, it was found that UAV‐lidar was more sensitive to small‐scale deformation, with a difference range of 0.23–0.44 m compared to photogrammetry. The conclusion provides valuable information regarding the utilisation of multisource monitoring data.