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Article

3D Forest Mapping Using A Low-Cost UAV Laser Scanning System: Investigation and Comparison

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State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2
Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, 159 Longpan Road, Nanjing 210037, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(6), 717; https://doi.org/10.3390/rs11060717
Received: 21 February 2019 / Revised: 16 March 2019 / Accepted: 22 March 2019 / Published: 25 March 2019
(This article belongs to the Section Forest Remote Sensing)
Automatic 3D forest mapping and individual tree characteristics estimation are essential for forest management and ecosystem maintenance. The low-cost unmanned aerial vehicle (UAV) laser scanning (ULS) is a newly developed tool for cost-effectively collecting 3D information and attempts to use it for 3D forest mapping have been made, due to its capability to provide 3D information with a lower cost and higher flexibility than the standard ULS and airborne laser scanning (ALS). As the direct georeferenced point clouds may suffer from distortion caused by the poor performance of a low-cost inertial measurement unit (IMU), and 3D forest mapping using low-cost ULS poses a great challenge. Therefore, this paper utilized global navigation satellite system (GNSS) and IMU aided Structure-from-Motion (SfM) for trajectory estimation, and, hence, overcomes the poor performance of low-cost IMUs. The accuracy of the low-cost ULS point clouds was compared with the ground truth data collected by a commercial ULS system. Furthermore, the effectiveness of individual trees segmentation and tree characteristics estimation derived from the low-cost ULS point clouds were accessed. Experiments were undertaken in Dongtai forest farm, Yancheng City, Jiangsu Province, China. The results showed that the low-cost ULS achieved good point clouds quality from visual inspection and comparable individual tree segmentation results (P = 0.87, r = 0.84, F = 0.85) with the commercial system. Individual tree height estimation performed well (coefficient of determination (R2) = 0.998, root-mean-square error (RMSE) = 0.323 m) using the low-cost ULS. As for individual tree crown diameter estimation, low-cost ULS achieved good results (R2 = 0.806, RMSE = 0.195 m) after eliminating outliers. In general, such results illustrated the high potential of the low-cost ULS in 3D forest mapping, even though 3D forest mapping using the low-cost ULS requires further research. View Full-Text
Keywords: 3D forest mapping; low-cost; unmanned aerial vehicle (UAV); laser scanning 3D forest mapping; low-cost; unmanned aerial vehicle (UAV); laser scanning
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MDPI and ACS Style

Li, J.; Yang, B.; Cong, Y.; Cao, L.; Fu, X.; Dong, Z. 3D Forest Mapping Using A Low-Cost UAV Laser Scanning System: Investigation and Comparison. Remote Sens. 2019, 11, 717. https://doi.org/10.3390/rs11060717

AMA Style

Li J, Yang B, Cong Y, Cao L, Fu X, Dong Z. 3D Forest Mapping Using A Low-Cost UAV Laser Scanning System: Investigation and Comparison. Remote Sensing. 2019; 11(6):717. https://doi.org/10.3390/rs11060717

Chicago/Turabian Style

Li, Jianping, Bisheng Yang, Yangzi Cong, Lin Cao, Xiaoyao Fu, and Zhen Dong. 2019. "3D Forest Mapping Using A Low-Cost UAV Laser Scanning System: Investigation and Comparison" Remote Sensing 11, no. 6: 717. https://doi.org/10.3390/rs11060717

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