A1 Refereed original research article in a scientific journal
Automated Stem Curve Measurement Using Terrestrial Laser Scanning
Authors: Liang, Xinlian; Kankare, Ville; Yu, Xiaowei; Hyyppä, Juha; Holopainen, Markus
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publishing place: PISCATAWAY
Publication year: 2014
Journal: IEEE Transactions on Geoscience and Remote Sensing
Journal name in source: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Journal acronym: IEEE T GEOSCI REMOTE
Volume: 52
Issue: 3
First page : 1739
Last page: 1748
Number of pages: 10
ISSN: 0196-2892
eISSN: 1558-0644
DOI: https://doi.org/10.1109/TGRS.2013.2253783
Abstract
This paper reports on a study of measuring stem curves of standing trees of different species and in different growth stages using terrestrial laser scanning (TLS). Pine and spruce trees are scanned using the multiscan approach in the field, and trees are felled to measure them destructively for the purpose of obtaining reference values. The stem curves are automatically retrieved from laser point clouds, resulting in an accuracy of similar to 1 cm. The corresponding manual measurements yield similar accuracy but fewer measurements at the upper parts of tree stems, compared with the automated measurements. The stem volumes based on stem curve data and field measurements and the best Finnish national allometric volume equations (using tree species, height, and diameters at heights of 1.3 and 6 m as predictors) result in similar accuracy. The measurement accuracy of the stem curves and stem volumes is similar for both pine and spruce trees. The results of this paper confirm the feasibility of using TLS to produce stem curve data in an automated, accurate and noninvasive way and indicate that the point cloud provides adequate information to accurately derive stem volumes from standing trees. The stem curves and volumes retrieved from point clouds can be employed in various forest management activities, such as the calibration of national or regional allometric curve functions and the prediction of profits in preharvest inventories.
This paper reports on a study of measuring stem curves of standing trees of different species and in different growth stages using terrestrial laser scanning (TLS). Pine and spruce trees are scanned using the multiscan approach in the field, and trees are felled to measure them destructively for the purpose of obtaining reference values. The stem curves are automatically retrieved from laser point clouds, resulting in an accuracy of similar to 1 cm. The corresponding manual measurements yield similar accuracy but fewer measurements at the upper parts of tree stems, compared with the automated measurements. The stem volumes based on stem curve data and field measurements and the best Finnish national allometric volume equations (using tree species, height, and diameters at heights of 1.3 and 6 m as predictors) result in similar accuracy. The measurement accuracy of the stem curves and stem volumes is similar for both pine and spruce trees. The results of this paper confirm the feasibility of using TLS to produce stem curve data in an automated, accurate and noninvasive way and indicate that the point cloud provides adequate information to accurately derive stem volumes from standing trees. The stem curves and volumes retrieved from point clouds can be employed in various forest management activities, such as the calibration of national or regional allometric curve functions and the prediction of profits in preharvest inventories.
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