Nondestructive estimates of above-ground biomass using terrestrial laser scanning

Calders, Kim, Newnham, Glenn, Burt, Andrew, Murphy, Simon, Raumonen, Pasi, Herold, Martin, Culvenor, Darius, Avitabile, Valerio, Disney, Mathias, Armston, John and Kaasalainen, Mikko (2015) Nondestructive estimates of above-ground biomass using terrestrial laser scanning. Methods in Ecology and Evolution, 6 2: 198-208. doi:10.1111/2041-210X.12301

Author Calders, Kim
Newnham, Glenn
Burt, Andrew
Murphy, Simon
Raumonen, Pasi
Herold, Martin
Culvenor, Darius
Avitabile, Valerio
Disney, Mathias
Armston, John
Kaasalainen, Mikko
Title Nondestructive estimates of above-ground biomass using terrestrial laser scanning
Journal name Methods in Ecology and Evolution   Check publisher's open access policy
ISSN 2041-210X
Publication date 2015-02
Year available 2014
Sub-type Article (original research)
DOI 10.1111/2041-210X.12301
Open Access Status
Volume 6
Issue 2
Start page 198
End page 208
Total pages 11
Place of publication Oxford, United Kingdom
Publisher Wiley-Blackwell Publishing
Collection year 2015
Language eng
Formatted abstract
1. Allometric equations are currently used to estimate above-ground biomass (AGB) based on the indirect relationship with tree parameters. Terrestrial laser scanning (TLS) can measure the canopy structure in 3D with high detail. In this study, we develop an approach to estimate AGB from TLS data, which does not need any prior information about allometry. We compare these estimates against destructively harvested AGB estimates and AGB derived from allometric equations. We also evaluate tree parameters, diameter at breast height (DBH) and tree height, estimated from traditional field inventory and TLS data.
2. Tree height, DBH and AGB data are collected through traditional forest inventory, TLS and destructive sampling of 65 trees in a native Eucalypt Open Forest in Victoria, Australia. Single trees are extracted from the TLS data and quantitative structure models are used to estimate the tree volume directly from the point cloud data. AGB is inferred from these volumes and basic density information and is then compared with the estimates derived from allometric equations and destructive sampling.
3. AGB estimates derived from TLS show a high agreement with the reference values from destructive sampling, with a concordance correlation coefficient (CCC) of 0·98. The agreement between AGB estimates from allometric equations and the reference is lower (CCC = 0·68–0·78). Our TLS approach shows a total AGB overestimation of 9·68% compared to an underestimation of 36·57–29·85% for the allometric equations.
4. The error for AGB estimates using allometric equations increases exponentially with increasing DBH, whereas the error for AGB estimates from TLS is not dependent on DBH. The TLS method does not rely on indirect relationships with tree parameters or calibration data and shows better agreement with the reference data compared to estimates from allometric equations. Using 3D data also enables us to look at the height distributions of AGB, and we demonstrate that 80% of the AGB at plot level is located in the lower 60% of the trees for a Eucalypt Open Forest. This method can be applied in many forest types and can assist in the calibration and validation of broad-scale biomass maps.
Keyword LiDAR
Above-ground biomass
Forest inventory
Destructive harvesting
Tree reconstruction
Allometric equations
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online ahead of print 21 Nov 2014

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
Official 2015 Collection
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Citation counts: TR Web of Science Citation Count  Cited 25 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 25 times in Scopus Article | Citations
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