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Proceedings Paper

Registration between uav LiDAR datasets for under-forest areas
Author(s): Wang Tao
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Paper Abstract

Due to the absence of control points, direct use of georeferencing data leads to registration errors between light detection and ranging (LiDAR) datasets for under-forest areas captured by unmanned aerial vehicles (UAVs). This study aims to propose a registration method for LiDAR data captured by UAVs for under-forest areas. First, a bare-earth digital elevation model (DEM) was created by filtering from a point cloud. Then a canopy height model (CHM) was generated by subtracting the DEM from the original point cloud, and CHM was reduced to one layer, as only the layer just above the ground was needed. Next, the point cloud was transformed into a voxel space with a resolution of 0.4 m; the verticalcolumn voxels were from the tree stem if the number of points in the vertical-column voxels exceeded the threshold. Finally, tree-height detection was used to find the same stem location, and the transformation matrices between corresponding cloud points were calculated using the same stem location from different UAV LiDAR data.

Paper Details

Date Published: 14 August 2019
PDF: 7 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111794G (14 August 2019); doi: 10.1117/12.2539687
Show Author Affiliations
Wang Tao, Guangzhou Univ. (China)

Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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