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Realistic forest stand reconstruction from terrestrial LiDAR for radiative transfer modelling

Kim Calders (UGent) , Niall Origo, Andrew Burt, Mathias Disney, Joanne Nightingale, Pasi Raumonen, Markku Åkerblom, Yadvinder Malhi and Philip Lewis
(2018) REMOTE SENSING. 10(6).
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Abstract
Forest biophysical variables derived from remote sensing observations are vital for climate research. The combination of structurally and radiometrically accurate 3D virtual forests with radiative transfer (RT) models creates a powerful tool to facilitate the calibration and validation of remote sensing data and derived biophysical products by helping us understand the assumptions made in data processing algorithms. We present a workflow that uses highly detailed 3D terrestrial laser scanning (TLS) data to generate virtual forests for RT model simulations. Our approach to forest stand reconstruction from a co-registered point cloud is unique as it models each tree individually. Our approach follows three steps: (1) tree segmentation; (2) tree structure modelling and (3) leaf addition. To demonstrate this approach, we present the measurement and construction of a one hectare model of the deciduous forest in Wytham Woods (Oxford, UK). The model contains 559 individual trees. We matched the TLS data with traditional census data to determine the species of each individual tree and allocate species-specific radiometric properties. Our modelling framework is generic, highly transferable and adjustable to data collected with other TLS instruments and different ecosystems. The Wytham Woods virtual forest is made publicly available through an online repository.
Keywords
tree reconstruction, radiative transfer, terrestrial LiDAR, forestry, 3D modelling, calibration and validation, end-to-end traceability, LEAF-AREA INDEX, CANOPY STRUCTURE, TREE MODELS, LASER, PLANT, PROFILES, AIRBORNE, SYSTEM, cavelab

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MLA
Calders, Kim, et al. “Realistic Forest Stand Reconstruction from Terrestrial LiDAR for Radiative Transfer Modelling.” REMOTE SENSING, vol. 10, no. 6, 2018, doi:10.3390/rs10060933.
APA
Calders, K., Origo, N., Burt, A., Disney, M., Nightingale, J., Raumonen, P., … Lewis, P. (2018). Realistic forest stand reconstruction from terrestrial LiDAR for radiative transfer modelling. REMOTE SENSING, 10(6). https://doi.org/10.3390/rs10060933
Chicago author-date
Calders, Kim, Niall Origo, Andrew Burt, Mathias Disney, Joanne Nightingale, Pasi Raumonen, Markku Åkerblom, Yadvinder Malhi, and Philip Lewis. 2018. “Realistic Forest Stand Reconstruction from Terrestrial LiDAR for Radiative Transfer Modelling.” REMOTE SENSING 10 (6). https://doi.org/10.3390/rs10060933.
Chicago author-date (all authors)
Calders, Kim, Niall Origo, Andrew Burt, Mathias Disney, Joanne Nightingale, Pasi Raumonen, Markku Åkerblom, Yadvinder Malhi, and Philip Lewis. 2018. “Realistic Forest Stand Reconstruction from Terrestrial LiDAR for Radiative Transfer Modelling.” REMOTE SENSING 10 (6). doi:10.3390/rs10060933.
Vancouver
1.
Calders K, Origo N, Burt A, Disney M, Nightingale J, Raumonen P, et al. Realistic forest stand reconstruction from terrestrial LiDAR for radiative transfer modelling. REMOTE SENSING. 2018;10(6).
IEEE
[1]
K. Calders et al., “Realistic forest stand reconstruction from terrestrial LiDAR for radiative transfer modelling,” REMOTE SENSING, vol. 10, no. 6, 2018.
@article{8565424,
  abstract     = {{Forest biophysical variables derived from remote sensing observations are vital for climate research. The combination of structurally and radiometrically accurate 3D virtual forests with radiative transfer (RT) models creates a powerful tool to facilitate the calibration and validation of remote sensing data and derived biophysical products by helping us understand the assumptions made in data processing algorithms. We present a workflow that uses highly detailed 3D terrestrial laser scanning (TLS) data to generate virtual forests for RT model simulations. Our approach to forest stand reconstruction from a co-registered point cloud is unique as it models each tree individually. Our approach follows three steps: (1) tree segmentation; (2) tree structure modelling and (3) leaf addition. To demonstrate this approach, we present the measurement and construction of a one hectare model of the deciduous forest in Wytham Woods (Oxford, UK). The model contains 559 individual trees. We matched the TLS data with traditional census data to determine the species of each individual tree and allocate species-specific radiometric properties. Our modelling framework is generic, highly transferable and adjustable to data collected with other TLS instruments and different ecosystems. The Wytham Woods virtual forest is made publicly available through an online repository.}},
  articleno    = {{933}},
  author       = {{Calders, Kim and Origo, Niall and Burt, Andrew and Disney, Mathias and Nightingale, Joanne and Raumonen, Pasi and Åkerblom, Markku and Malhi, Yadvinder and Lewis, Philip}},
  issn         = {{2072-4292}},
  journal      = {{REMOTE SENSING}},
  keywords     = {{tree reconstruction,radiative transfer,terrestrial LiDAR,forestry,3D modelling,calibration and validation,end-to-end traceability,LEAF-AREA INDEX,CANOPY STRUCTURE,TREE MODELS,LASER,PLANT,PROFILES,AIRBORNE,SYSTEM,cavelab}},
  language     = {{eng}},
  number       = {{6}},
  pages        = {{15}},
  title        = {{Realistic forest stand reconstruction from terrestrial LiDAR for radiative transfer modelling}},
  url          = {{http://dx.doi.org/10.3390/rs10060933}},
  volume       = {{10}},
  year         = {{2018}},
}
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