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Tree crown segmentation in three dimensions using density models derived from airborne laser scanning

Holmgren, Johan and Lindberg, Eva and Olofsson, Kenneth and Persson, Henrik (2022). Tree crown segmentation in three dimensions using density models derived from airborne laser scanning. International Journal of Remote Sensing. 43 , 299-329
[Research article]

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Abstract

This article describes algorithms to extract tree crowns using two-dimensional (2D) and three-dimensional (3D) segmentation. As a first step, a 2D-search detected the tallest trees but was unable to detect trees located below other trees. However, a 3D-search for local maxima of model fits could be used in a second step to detect trees also in lower canopy layers. We compared tree detection results from ALS carried out at 1450 m above ground level (high altitude) and tree detection results from ALS carried out at 150 m above ground level (low altitude). For validation, we used manual measurements of trees in ten large field plots, each with an 80 m diameter, in a hemiboreal forest in Sweden (lat. 58 degrees 28' N, long. 13 degrees 38' E). In order to measure the effect of using algorithms with different computational costs, we validated the tree detection from the 2D segmentation step and compared the results with the 2D segmentation followed by 3D segmentation of the ALS point cloud. When applying 2D segmentation only, the algorithm detected 87% of the trees measured in the field using high-altitude ALS data; the detection rate increased to 91% using low-altitude ALS data. However, when applying 3D segmentation as well, the algorithm detected 92% of the trees measured in the field using high-altitude ALS data; the detection rate increased to 99% using low-altitude ALS data. For all combinations of algorithms and data resolutions, undetected trees accounted for, on average, 0-5% of the total stem volume in the field plots. The 3D tree crown segmentation, which was using crown density models, made it possible to detect a large percentage of trees in multi-layered forests, compared with using only a 2D segmentation method.

Authors/Creators:Holmgren, Johan and Lindberg, Eva and Olofsson, Kenneth and Persson, Henrik
Title:Tree crown segmentation in three dimensions using density models derived from airborne laser scanning
Series Name/Journal:International Journal of Remote Sensing
Year of publishing :2022
Volume:43
Page range:299-329
Number of Pages:31
Publisher:TAYLOR AND FRANCIS LTD
ISSN:0143-1161
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing
URN:NBN:urn:nbn:se:slu:epsilon-p-115383
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-115383
Additional ID:
Type of IDID
DOI10.1080/01431161.2021.2018149
Web of Science (WoS)000739361200001
ID Code:26698
Faculty:S - Faculty of Forest Sciences
Department:(S) > Dept. of Forest Resource Management
(NL, NJ) > Dept. of Forest Resource Management
Deposited By: SLUpub Connector
Deposited On:14 Jan 2022 14:20
Metadata Last Modified:14 Jan 2022 14:21

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