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

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dc.contributor.author Liu, Jingbin
dc.contributor.author Liang, Xinlian
dc.contributor.author Hyyppä, Juha
dc.contributor.author Yu, Xiaowei
dc.contributor.author Lehtomäki, Matti
dc.contributor.author Pyörälä, Jiri
dc.contributor.author Zhu, Lingli
dc.contributor.author Wang, Yunsheng
dc.contributor.author Chen, Ruizhi
dc.date.accessioned 2017-09-14T12:53:01Z
dc.date.available 2017-09-14T12:53:01Z
dc.date.issued 2017-04
dc.identifier.citation 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 . https://doi.org/10.1016/j.jag.2016.11.003
dc.identifier.other PURE: 82081746
dc.identifier.other PURE UUID: 52363dfa-2781-4224-bce5-e78b4854f5f9
dc.identifier.other WOS: 000392781200002
dc.identifier.uri http://hdl.handle.net/10138/224194
dc.description.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. en
dc.format.extent 11
dc.language.iso eng
dc.relation.ispartof International Journal of Applied Earth Observation and Geoinformation
dc.rights cc_by_nc_nd
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject Terrestrial laser scanning
dc.subject Registration
dc.subject Scan matching
dc.subject Laser scanning
dc.subject Stem mapping
dc.subject Boreal forest
dc.subject POINT CLOUDS
dc.subject STANDING TREES
dc.subject REGISTRATION
dc.subject FOREST
dc.subject LIDAR
dc.subject SURFACES
dc.subject ACCURACY
dc.subject 1171 Geosciences
dc.title Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references en
dc.type Article
dc.contributor.organization Department of Forest Sciences
dc.contributor.organization Laboratory of Forest Resources Management and Geo-information Science
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1016/j.jag.2016.11.003
dc.relation.issn 1569-8432
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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