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UAV-Laser scanning based metrics for individual tree volume estimation across forest types

Benjamin Brede, Nicolas Barbier, Harm Bartholomeus, Renee Bartolo, Kim Calders (UGent) , Géraldine Derroire, Alvaro Lau, Shaun Levick, Sruthi Krishna Moorthy Parvathi (UGent) , Pasi Raumonen, et al.
(2021) Proceedings of the SilviLaser Conference 2021. In Geowissenschaftliche Mitteilungen 104. p.68-70
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Abstract
Upcoming satellite missions targeting the estimation of forest Above-Ground Biomass require an expansion of calibration and validation capabilities. Terrestrial Laser Scanning (TLS) has been demonstrated to be an unbiased estimation tool for single tree wood volume and AGB, especially in large trees. However, TLS field data acquisition is labour-intense and time consuming, and might be overcome by Unmanned Aerial Vehicle Laser Scanning (UAV-LS). In this context, the aim of this study was to explore the potential of individual tree metrics derived from automatically segmented UAV-LS point clouds to estimate tree wood volume across a range of forest sites with varying structural complexity. Four sites were involved, one temperate mixed, two tropical wet and one savanna forest site. Each was surveyed with both TLS (RIEGL VZ-400) and UAV-LS (RIEGL VUX-1UAV). Based on TLS point clouds, reference trees were segmented and wood volume was estimated via Quantitative Structural Modelling (QSM). The UAV-LS point clouds were automatically segmented and trees corresponding to the TLS reference trees were identified. Then, a range of individual tree metrics was derived from the UAV-LS point clouds and compared with TLS reference wood volume. Results showed asymptotic behaviour of metrics tree height and crown diameter (R2 0.16 to 0.78), while crown area, tree volume and novel graph-based metrics showed more linear relationships with volume (R2 0.22 to 0.88). Overall, the available metrics offer promising opportunities for wood volume modelling and future biomass estimation. This will allow the estimation forest biomass across hectare-scales for efficient satellite mission calibration and validation.

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MLA
Brede, Benjamin, et al. “UAV-Laser Scanning Based Metrics for Individual Tree Volume Estimation across Forest Types.” Proceedings of the SilviLaser Conference 2021, edited by Markus Hollaus and Norbert Pfeifer, vol. 104, Technische Universität Wien, 2021, pp. 68–70, doi:10.34726/wim.1918.
APA
Brede, B., Barbier, N., Bartholomeus, H., Bartolo, R., Calders, K., Derroire, G., … Herold, M. (2021). UAV-Laser scanning based metrics for individual tree volume estimation across forest types. In M. Hollaus & N. Pfeifer (Eds.), Proceedings of the SilviLaser Conference 2021 (Vol. 104, pp. 68–70). https://doi.org/10.34726/wim.1918
Chicago author-date
Brede, Benjamin, Nicolas Barbier, Harm Bartholomeus, Renee Bartolo, Kim Calders, Géraldine Derroire, Alvaro Lau, et al. 2021. “UAV-Laser Scanning Based Metrics for Individual Tree Volume Estimation across Forest Types.” In Proceedings of the SilviLaser Conference 2021, edited by Markus Hollaus and Norbert Pfeifer, 104:68–70. Technische Universität Wien. https://doi.org/10.34726/wim.1918.
Chicago author-date (all authors)
Brede, Benjamin, Nicolas Barbier, Harm Bartholomeus, Renee Bartolo, Kim Calders, Géraldine Derroire, Alvaro Lau, Shaun Levick, Sruthi Krishna Moorthy Parvathi, Pasi Raumonen, Louise Terryn, Hans Verbeeck, Tim Whiteside, and Martin Herold. 2021. “UAV-Laser Scanning Based Metrics for Individual Tree Volume Estimation across Forest Types.” In Proceedings of the SilviLaser Conference 2021, ed by. Markus Hollaus and Norbert Pfeifer, 104:68–70. Technische Universität Wien. doi:10.34726/wim.1918.
Vancouver
1.
Brede B, Barbier N, Bartholomeus H, Bartolo R, Calders K, Derroire G, et al. UAV-Laser scanning based metrics for individual tree volume estimation across forest types. In: Hollaus M, Pfeifer N, editors. Proceedings of the SilviLaser Conference 2021. Technische Universität Wien; 2021. p. 68–70.
IEEE
[1]
B. Brede et al., “UAV-Laser scanning based metrics for individual tree volume estimation across forest types,” in Proceedings of the SilviLaser Conference 2021, Vienna, Austria, 2021, vol. 104, pp. 68–70.
@inproceedings{01J9RGPVD8NT2DRGSAJ3WM1EQA,
  abstract     = {{Upcoming satellite missions targeting the estimation of forest Above-Ground Biomass require an expansion of calibration and validation capabilities. Terrestrial Laser Scanning (TLS) has been demonstrated to be an unbiased estimation tool for single tree wood volume and AGB, especially in large trees. However, TLS field data acquisition is labour-intense and time consuming, and might be overcome by Unmanned Aerial Vehicle Laser Scanning (UAV-LS). In this context, the aim of this study was to explore the potential of individual tree metrics derived from automatically segmented UAV-LS point clouds to estimate tree wood volume across a range of forest sites with varying structural complexity. Four sites were involved, one temperate mixed, two tropical wet and one savanna forest site. Each was surveyed with both TLS (RIEGL VZ-400) and UAV-LS (RIEGL VUX-1UAV). Based on TLS point clouds, reference trees were segmented and wood volume was estimated via Quantitative Structural Modelling (QSM). The UAV-LS point clouds were automatically segmented and trees corresponding to the TLS reference trees were identified. Then, a range of individual tree metrics was derived from the UAV-LS point clouds and compared with TLS reference wood volume. Results showed asymptotic behaviour of metrics tree height and crown diameter (R2 0.16 to 0.78), while crown area, tree volume and novel graph-based metrics showed more linear relationships with volume (R2 0.22 to 0.88). Overall, the available metrics offer promising opportunities for wood volume modelling and future biomass estimation. This will allow the estimation forest biomass across hectare-scales for efficient satellite mission calibration and validation.}},
  author       = {{Brede, Benjamin and Barbier, Nicolas and Bartholomeus, Harm and Bartolo, Renee and Calders, Kim and Derroire, Géraldine and Lau, Alvaro and Levick, Shaun and Krishna Moorthy Parvathi, Sruthi and Raumonen, Pasi and Terryn, Louise and Verbeeck, Hans and Whiteside, Tim and Herold, Martin}},
  booktitle    = {{Proceedings of the SilviLaser Conference 2021}},
  editor       = {{Hollaus, Markus and Pfeifer, Norbert}},
  issn         = {{1811-8380}},
  language     = {{eng}},
  location     = {{Vienna, Austria}},
  pages        = {{68--70}},
  publisher    = {{Technische Universität Wien}},
  title        = {{UAV-Laser scanning based metrics for individual tree volume estimation across forest types}},
  url          = {{http://doi.org/10.34726/wim.1918}},
  volume       = {{104}},
  year         = {{2021}},
}
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