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Proceedings Paper

Derivation of tree stem structural parameters from static terrestrial laser scanning data
Author(s): Wei Tian; Yi Lin; Yajing Liu; Zheng Niu
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Paper Abstract

Accurate tree-level characteristic information is increasingly demanded for forest management and environment protection. The cutting-edge remote sensing technique of terrestrial laser scanning (TLS) shows the potential of filling this gap. This study focuses on exploring the methods for deriving various tree stem structural parameters, such as stem position, diameter at breast height (DBH), the degree of stem shrinkage, and the elevation angle and azimuth angle of stem inclination. The data for test was collected with a Leica HDS6100 TLS system in Seurasaari, Southern Finland in September 2010. In the field, the reference positions and DBHs of 100 trees were measured manually. The isolation of individual trees is based on interactive segmentation of point clouds. The estimation of stem position and DBH is based on the schematic of layering and then least-square-based circle fitting in each layer. The slope of robust fit line between the height of each layer and DBH is used to characterize the stem shrinkage. The elevation angle of stem inclination is described by the angle between the ground plane and the fitted stem axis. The angle between the north direction and the fitted stem axis gives the azimuth angle of stem inclination. The estimation of the DBHs performed with R square (R2) of 0.93 and root mean square error (RMSE) of 0.038m.The average angle corresponding to stem shrinkage is -1.86°. The elevation angles of stem inclinations are ranged from 31° to 88.3°. The results have basically validated TLS for deriving multiple structural parameters of stem, which help better grasp tree specialties.

Paper Details

Date Published: 17 November 2014
PDF: 7 pages
Proc. SPIE 9262, Lidar Remote Sensing for Environmental Monitoring XIV, 92620Z (17 November 2014); doi: 10.1117/12.2068571
Show Author Affiliations
Wei Tian, Hebei United Univ. (China)
Yi Lin, Peking Univ. (China)
Yajing Liu, Hebei United Univ. (China)
Zheng Niu, Institute of Remote Sensing and Digital Earth (China)

Published in SPIE Proceedings Vol. 9262:
Lidar Remote Sensing for Environmental Monitoring XIV
Upendra N. Singh; Kazuhiro Asai, Editor(s)

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