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Mobile 3d mapping with a low-cost uav-based lidar system

Phan Department of Geomatics Engineering, Faculty of Civil Engineering, Ho Chi Minh University of Technology, 268 Ly Thuong Kiet Street, Ward 14, District 10, Ho Chi Minh City, Viet Nam|
K. (56164601300) | C.B.V. (57225220307); Takahashi Nagaoka University of Technology, 1603-1, Kami-Tomioka, Niigata, Nagaoka, 940-2188, Japan| A.T.T. (57195512411); Dang Vietnam National University Ho Chi Minh City, Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Viet Nam|

International Journal of Geoinformatics Số 3, năm 2021 (Tập 17, trang 108-116)

ISSN: 16866576

ISSN: 16866576

DOI: 10.52939/ijg.v17i3.1905

Tài liệu thuộc danh mục:

Article

English

Từ khóa: Chubu; Honshu; Japan; Nagaoka; Niigata; accuracy assessment; crop yield; error correction; experimental study; growth response; image analysis; lidar; three-dimensional modeling; topographic mapping; unmanned vehicle
Tóm tắt tiếng anh
Recently, many UAVs (unmanned aerial vehicles) based on LiDAR (light detection and ranging) systems have been developed for various purpose because of the effective of LIDAR technique and low-cost UAV. In this study, the accuracy of point clouds generated by the developed for a low-cost UAV-based LiDAR systems is evaluated. The system consisting of a multi-beam laser scanner-Velodyne VLP 16 and DJI M600 UAV. The experimental site is undulation with less object in Nagaoka city, Niigata Prefecture, Japan Twelve reflectance makers are arranged as ground control point for the positioning evaluating process. The observed data was collected on Nov. 8th, 2019 with three different flight height at 10m, 20m and 30m. For generating the point clouds, the mounting parameters and sensor parameters are combined. The generated point clouds are corrected by applying bias correction and the 7 parameters transformation. The result is validated using three different experimental setups with three various flight height which indicate that the most accurate and reliable results are obtained. As a result, the point clouds after calibrating attained an accuracy of approximate 0.2 m in vertical and horizontal for both correction methods. In conclusion, the point cloud accuracy is not good enough for generating the topographic map at large scale. However, the stable results and the present accuracy are good for other purposes with less accuracy requirement such as monitoring the crop growth. � Geoinformatics International.

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