Evaluation of automated pipelines for tree and plot metric estimation from TLS data in tropical forest areas

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2021-11-02
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Mcode
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Language
en
Pages
14
753-766
Series
ANNALS OF BOTANY, Volume 128, issue 6
Abstract
Background and Aims: Terrestrial LiDAR scanning (TLS) data are of great interest in forest ecology and management because they provide detailed 3-D information on tree structure. Automated pipelines are increasingly used to process TLS data and extract various tree- A nd plot-level metrics. With these developments comes the risk of unknown reliability due to an absence of systematic output control. In the present study, we evaluated the estimation errors of various metrics, such as wood volume, at tree and plot levels for four automated pipelines. Methods: We used TLS data collected from a 1-ha plot of tropical forest, from which 391 trees >10 cm in diameter were fully processed using human assistance to obtain control data for tree- A nd plot-level metrics. Key Results: Our results showed that fully automated pipelines led to median relative errors in the quantitative structural model (QSM) volume ranging from 39 to 115 % at the tree level and 10 to 134 % at the 1-ha plot level. For tree-level metrics, the median error for the crown-projected area ranged from 46 to 59 % and that for the crown-hull volume varied from 72 to 88 %. This result suggests that the tree isolation step is the weak link in automated pipeline methods. We further analysed how human assistance with automated pipelines can help reduce the error in the final QSM volume. At the tree scale, we found that isolating trees using human assistance reduced the error in wood volume by a factor of 10. At the 1-ha plot scale, locating trees with human assistance reduced the error by a factor of 3. Conclusions: Our results suggest that in complex tropical forests, fully automated pipelines may provide relatively unreliable metrics at the tree and plot levels, but limited human assistance inputs can significantly reduce errors.
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Publisher Copyright: © 2021 The Author(s). Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved.
Keywords
AGB estimation, wood volume, tree crown metrics, quantitative structural model (QSM)
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Citation
Martin-Ducup , O , Mofack , G , Wang , D , Raumonen , P , Ploton , P , Sonké , B , Barbier , N , Couteron , P & Pélissier , R 2021 , ' Evaluation of automated pipelines for tree and plot metric estimation from TLS data in tropical forest areas ' , Annals of Botany , vol. 128 , no. 6 , pp. 753-766 . https://doi.org/10.1093/aob/mcab051