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Remote Sens. 2018, 10(6), 933; https://doi.org/10.3390/rs10060933

Realistic Forest Stand Reconstruction from Terrestrial LiDAR for Radiative Transfer Modelling

1
Earth Observation, Climate and Optical Group, National Physical Laboratory, Teddington TW11 0LW, UK
2
Department of Geography, University College London, Gower Street, London WC1E 6BT, UK
3
CAVElab-Computational & Applied Vegetation Ecology, Ghent University, 9000 Ghent, Belgium
4
NERC National Centre for Earth Observation (NCEO), UCL Geography, Gower Street, London WC1E 6BT, UK
5
Laboratory of Mathematics, Tampere University of Technology, P.O. Box 692, FI-33101 Tampere, Finland
6
Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK
*
Author to whom correspondence should be addressed.
Received: 2 May 2018 / Revised: 29 May 2018 / Accepted: 11 June 2018 / Published: 13 June 2018
(This article belongs to the Special Issue Radiative Transfer Modelling and Applications in Remote Sensing)
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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. View Full-Text
Keywords: tree reconstruction; radiative transfer; terrestrial LiDAR; forestry; 3D modelling; calibration and validation; end-to-end traceability tree reconstruction; radiative transfer; terrestrial LiDAR; forestry; 3D modelling; calibration and validation; end-to-end traceability
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Calders, K.; Origo, N.; Burt, A.; Disney, M.; Nightingale, J.; Raumonen, P.; Åkerblom, M.; Malhi, Y.; Lewis, P. Realistic Forest Stand Reconstruction from Terrestrial LiDAR for Radiative Transfer Modelling. Remote Sens. 2018, 10, 933.

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