Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references

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http://hdl.handle.net/10138/224194

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Liu , J , Liang , X , Hyyppä , J , Yu , X , Lehtomäki , M , Pyörälä , J , Zhu , L , Wang , Y & Chen , R 2017 , ' Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references ' International Journal of Applied Earth Observation and Geoinformation , vol 56 , pp. 13-23 . DOI: 10.1016/j.jag.2016.11.003

Title: Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references
Author: Liu, Jingbin; Liang, Xinlian; Hyyppä, Juha; Yu, Xiaowei; Lehtomäki, Matti; Pyörälä, Jiri; Zhu, Lingli; Wang, Yunsheng; Chen, Ruizhi
Contributor: University of Helsinki, Department of Forest Sciences
Belongs to series: International Journal of Applied Earth Observation and Geoinformation
ISSN: 1569-8432
Abstract: Terrestrial laser scanning has been widely used to analyze the 3D structure of a forest in detail and to generate data at the level of a reference plot for forest inventories without destructive measurements. Multi-scan terrestrial laser scanning is more commonly applied to collect plot-level data so that all of the stems can be detected and analyzed. However, it is necessary to match the point clouds of multiple scans to yield a point cloud with automated processing. Mismatches between datasets will lead to errors during the processing of multi-scan data. Classic registration methods based on flat surfaces cannot be directly applied in forest environments; therefore, artificial reference objects have conventionally been used to assist with scan matching. The use of artificial references requires additional labor and expertise, as well as greatly increasing the cost. In this study, we present an automated processing method for plot-level stem mapping that matches multiple scans without artificial references. In contrast to previous studies, the registration method developed in this study exploits the natural geometric characteristics among a set of tree stems in a plot and combines the point clouds of multiple scans into a unified coordinate system. Integrating multiple scans improves the overall performance of stem mapping in terms of the correctness of tree detection, as well as the bias and the root-mean-square errors of forest attributes such as diameter at breast height and tree height. In addition, the automated processing method makes stem mapping more reliable and consistent among plots, reduces the costs associated with plot-based stem mapping, and enhances the efficiency. (C) 2016 The Authors. Published by Elsevier B.V.
Peer review status: Peer reviewed
URI: http://hdl.handle.net/10138/224194
Date: 2017-04
Subject: Terrestrial laser scanning
Registration
Scan matching
Laser scanning
Stem mapping
Boreal forest
POINT CLOUDS
STANDING TREES
REGISTRATION
FOREST
LIDAR
SURFACES
ACCURACY
1171 Geosciences
Rights: Creative Commons License (CC BY-NC-ND 4.0)


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