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Comparing the accuracies of sUAV-SFM and UAV-LiDAR point clouds for topographic measurements

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Abstract

Small unmanned aerial vehicle structure-from-motion (sUAV-SFM) photogrammetry and the UAV-based light detection and ranging (UAV-LiDAR) have been widely applied to acquire topographic data. The point clouds play key roles in both the sUAV-SFM and UAV-LiDAR topographic measurements. In order to assess the measurement accuracy and forecast the application prospects of sUAV-SFM photogrammetry, in this study, the same point cloud filtering algorithm was used to process the dense point clouds generated by sUAV-SFM and UAV-LiDAR. After filtering, the filtered point cloud acquired with UAV-LiDAR served as a benchmark, and a point-by-point comparison with the filtered dense point clouds generated by sUAV-SFM was performed. It was concluded that (i) the interferences caused by both vegetation and artificial structures can be significantly reduced by using the cloth simulation filter (CSF) algorithm to classify these two types of point clouds, supplementing manual interpretation to obtain accurate ground points. (ii) sUAV-SFM can be used to obtain high-precision dense point clouds at a consistent quality compared with UAV-LiDAR, which was verified by applying the multiscale model-to-model cloud comparison (M3C2) algorithm for a comparative analysis of the point clouds. (iii) The accuracy of the results derived from the sUAV-SFM point clouds was consistent with that of the results extracted from the UAV-LiDAR point clouds. This result was ascertained through an analysis using digital terrain model (DTM) profiles and calculated earthwork volumes. (iv) Compared with the UAV-LiDAR, sUAV-SFM has notable advantages ranging from the inexpensive equipment required and its ease of operation to a high degree of automation. Therefore, sUAV-SFM has broad application prospects in the supervision of construction sites and for earthworks measurements.

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Acknowledgements

The authors thank the anonymous reviewers and academic editors of the journal for their useful comments and suggestions to improve the manuscript.

Funding

This work was partly supported by the National Key Research and Development Program of China under Grant No. 2018YFC1508302, 2019YFC0408805, and the Innovation Team Project of Changjiang River Scientific Research Institute under Grant No.CKSF2017063/KJ, and the Key Research Projects of Hubei Provincial Department of Water Resources under Grant No.HBSLKY201704.

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Authors and Affiliations

  1. School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China

    Song Ye & Qiuwen Zhang

  2. Changjiang Water Resources Commission, Changjiang River Scientific Research Institute, 23 Huangpu Avenue, Wuhan, 430010, China

    Song Ye & Dingtao Shen

  3. Changjiang Institute of Survey, Planning, Design and Research Co., Ltd., 1863 Jiefang Avenue, Wuhan, 430010, China

    Fei Yan

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  1. Song Ye
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Correspondence to Qiuwen Zhang.

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Responsible Editor: Biswajeet Pradhan

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Ye, S., Yan, F., Zhang, Q. et al. Comparing the accuracies of sUAV-SFM and UAV-LiDAR point clouds for topographic measurements. Arab J Geosci 15, 388 (2022). https://doi.org/10.1007/s12517-022-09683-2

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