ABSTRACT
Unmanned Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR) systems can potentially generate high precision Digital Terrain Models (DTM), especially for railway surveys. However, traditional feature points do not exist in LiDAR systems due to discrete sampling. Artificial control targets (ACTs) can be used as ground control points (GCPs) in a LiDAR system. In this paper, we present a new type of ACT suitable for a UAV-LiDAR system. The design of X-type ACTs and railway survey experiments with a multi-rotor UAV-LiDAR system are illustrated. Six ACTs are settled in the study area. The root mean square errors (RMSE) in the x, y direction are 0.15 m and 0.13 m, respectively, from collected multi-rotor UAV-LiDAR data. Planimetric errors in the LiDAR data were corrected with the six ACTs. With 22 horizontal and 32 elevation checkpoints, the accuracy estimation results demonstrate that RMSE values in the x, y, z directions are 0.06 m, 0.07 m and 0.030 m, respectively. The design of X-type ACTs, accuracy estimations and improvements for railway surveys with the multi-rotor UAV-LiDAR system presented in this paper will provide a reference for 3D measurements along other railways.
Acknowledgements
The authors are very thankful to the partial support of the National Natural Science Foundation of China (grant No. 41601446 and 41431179), and Tianjin Natural Science Foundation (grant No. 16JCQNJC01200).
Disclosure statement
No potential conflict of interest was reported by the authors.