Efficient registration of terrestrial LiDAR scans using a coarse-to-fine strategy for forestry applications

作者:Zhang, WM (Zhang, Wuming)[ 1 ] ; Chen, YM (Chen, Yiming)[ 1 ] ; Wang, HT (Wang, Hongtao)[ 1,2 ] ; Chen, M (Chen, Mei)[ 1 ] ; Wang, XY (Wang, Xiaoyan)[ 1 ] ; Yan, GJ (Yan, Guangjian)[ 1 ]

AGRICULTURAL AND FOREST METEOROLOGY

卷: 225  页: 8-23

DOI: 10.1016/j.agrformet.2016.05.005

出版年: SEP 15 2016

摘要

Terrestrial Laser Scanning (TLS) plays an increasing role in acquiring 3-dimensional forest structure information. Obstructions and stem density often need multiple scans, making the registration procedure vitally important. Since natural features are difficult to find, traditional registration methods often use artificial reflectors as tie points in forest areas. However, the placement of reflectors reduces the scanning efficiency, especially in forest stands with severe obstructions. In this paper, an efficient registration method using a coarse-to-fine strategy is proposed to overcome the challenge of placing artificial targets so as to improve the scanning efficiency. The coarse registration step utilizes the backsighting orientation approach to form a coarse alignment. Unlike other backsighting research used in urban areas, we solely rely on a TLS system with an internal compass and a built-in inclination sensor. In the fine registration step, stem center locations are calculated in each individual scan. Then, corresponding stem center pairs are found between adjacent scans with the help of the coarse registration results. They are used as tie points to perform a rigid-body transformation for the fine registration. The proposed coarse to-fine registration method was tested at two forest sites in northeast China. The registration accuracy is approximately 1.5 cm. Results also show that the diameters at breast height (DBHs) extracted from registered TLS data sets are highly correlated with field-measured DBHs (coefficient of determination (R-2): 0.92, root mean square error (RMSE): 0.27 cm). Considering both the scanning efficiency and accuracy, the proposed coarse-to-fine registration method provides a feasible and effective way for forest measurements. (C) 2016 Elsevier B.V. All rights reserved.

通讯作者地址: Chen, YM (通讯作者)

Beijing Normal Univ, Sch Geog, Beijing Key Lab Environm Remote Sensing & Digital, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.

地址:

[ 1 ] Beijing Normal Univ, Sch Geog, Beijing Key Lab Environm Remote Sensing & Digital, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[ 2 ] Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454003, Peoples R China