UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Estimation of above-ground biomass of large tropical trees with Terrestrial LiDAR

Gonzalez de Tanago Menaca, J; Lau, A; Bartholomeusm, H; Herold, M; Avitabile, V; Raumonen, P; Martius, C; ... Calders, K; + view all (2017) Estimation of above-ground biomass of large tropical trees with Terrestrial LiDAR. Methods in Ecology and Evolution 10.1111/2041-210X.12904. (In press). Green open access

[thumbnail of Disney_Menaca_et_al-2017-Methods_in_Ecology_and_Evolution (1).pdf]
Preview
Text
Disney_Menaca_et_al-2017-Methods_in_Ecology_and_Evolution (1).pdf - Published Version

Download (970kB) | Preview

Abstract

Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above-ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three-dimensional (3D) tree modelling of TLS point clouds. Twenty-nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species-specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements. AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV-RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV-RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics. Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non-destructive method can be further used for testing and calibrating new allometric models, reducing the current under-representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests.

Type: Article
Title: Estimation of above-ground biomass of large tropical trees with Terrestrial LiDAR
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/2041-210X.12904
Publisher version: http://dx.doi.org/10.1111/2041-210X.12904
Language: English
Additional information: Copyright © 2017 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Keywords: above-ground biomass; allometric models; LiDAR; terrestrial laser scanning; tree volume; tropical trees; 3D modeling
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography
URI: https://discovery.ucl.ac.uk/id/eprint/10022856
Downloads since deposit
197Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item