JOURNAL ARTICLE

Derivation of tree stem structural parameters from static terrestrial laser scanning data

Wei TianYi LinYajing LiuZheng Niu

Year: 2014 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 9262 Pages: 92620Z-92620Z   Publisher: SPIE

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.

Keywords:
Azimuth Mean squared error Elevation (ballistics) Position (finance) Optics Root mean square Tree (set theory) Physics Remote sensing Mathematics Geometry Geology Statistics

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Citation History

Topics

Remote Sensing and LiDAR Applications
Physical Sciences →  Environmental Science →  Environmental Engineering
Forest ecology and management
Physical Sciences →  Environmental Science →  Nature and Landscape Conservation
Remote Sensing in Agriculture
Physical Sciences →  Environmental Science →  Ecology

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