A new method to estimate branch biomass from terrestrial laser scanning data by bridging tree structure models

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Hu , M , Pitkanen , T P , Minunno , F , Tian , X , Lehtonen , A & Makela , A 2021 , ' A new method to estimate branch biomass from terrestrial laser scanning data by bridging tree structure models ' , Annals of Botany , vol. 128 , no. 6 , pp. 737-751 . https://doi.org/10.1093/aob/mcab037

Title: A new method to estimate branch biomass from terrestrial laser scanning data by bridging tree structure models
Author: Hu, Man; Pitkanen, Timo P.; Minunno, Francesco; Tian, Xianglin; Lehtonen, Aleksi; Makela, Annikki
Contributor organization: Forest Modelling Group
Department of Forest Sciences
Ecosystem processes (INAR Forest Sciences)
Date: 2021-11-02
Language: eng
Number of pages: 15
Belongs to series: Annals of Botany
ISSN: 0305-7364
DOI: https://doi.org/10.1093/aob/mcab037
URI: http://hdl.handle.net/10138/340142
Abstract: Background and Aims Branch biomass and other attributes are important for estimating the carbon budget of forest stands and characterizing crown structure. As destructive measuring is time-consuming and labour-intensive, terrestrial laser scanning (TLS) as a solution has been used to estimate branch biomass quickly and non-destructively. However, branch information extraction from TLS data alone is challenging due to occlusion and other defects, especially for estimating individual branch attributes in coniferous trees. Methods This study presents a method, entitled TSMtls, to estimate individual branch biomass non-destructively and accurately by combining tree structure models and TLS data. The TSMtls method constructs the stem-taper curve from TLS data, then uses tree structure models to determine the number, basal area and biomass of individual branches at whorl level. We estimated the tree structural model parameters from 122 destructively measured Scots pine (Pinus sylvestris) trees and tested the method on six Scots pine trees that were first TLS-scanned and later destructively measured. Additionally, we estimated the branch biomass using other TLS-based approaches for comparison. Key Results Tree-level branch biomass estimates derived from TSMtls showed the best agreement with the destructive measurements [coefficient of variation of root mean square error (CV-RMSE) = 9.66 % and concordance correlation coefficient (CCC) = 0.99], outperforming the other TLS-based approaches (CV-RMSE 12.97-57.45 % and CCC 0.43-0.98 ). Whorl-level individual branch attributes estimates produced from TSMtls showed more accurate results than those produced from TLS data directly. Conclusions The results showed that the TSMtls method proposed in this study holds promise for extension to more species and larger areas.
Subject: Branch biomass
terrestrial laser scanning
tree-structure model
individual branch attributes
quantitative structure model
NORWAY SPRUCE
SCOTS PINE
ABOVEGROUND BIOMASS
GROWTH
LIDAR
ARCHITECTURE
ALLOCATION
EQUATIONS
BIRCH
4112 Forestry
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


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