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Article

Bitemporal Radiative Transfer Modeling Using Bitemporal 3D-Explicit Forest Reconstruction from Terrestrial Laser Scanning

1
Q-ForestLab, Department of Environment, Ghent University, 9000 Gent, Belgium
2
Climate and Earth Observation Group, National Physical Laboratory, Hampton Road, Teddington TW11 0LW, UK
3
Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
4
CESBIO, Université de Toulouse, CNES/CNRS/INRAE/IRD/UT3-Paul Sabatier, 18, Avenue Edouard Belin, 31401 Toulouse, France
5
ISOFYS—Isotope Bioscience Laboratory, Department of Green chemistry and Technology, Ghent University, 9000 Gent, Belgium
6
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
7
Department of Geography, University College London (UCL), Gower Street, London WC1E 6BT, UK
8
NERC National Centre for Earth Observation (NCEO), UCL, Gower Street, London WC1E 6BT, UK
9
School of the Environment, The University of Queensland, St Lucia, QLD 4072, Australia
10
CSIRO, Space and Astronomy, Kensington, WA 6151, Australia
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(19), 3639; https://doi.org/10.3390/rs16193639 (registering DOI)
Submission received: 30 August 2024 / Revised: 27 September 2024 / Accepted: 28 September 2024 / Published: 29 September 2024
(This article belongs to the Section Forest Remote Sensing)

Abstract

Radiative transfer models (RTMs) are often used to retrieve biophysical parameters from earth observation data. RTMs with multi-temporal and realistic forest representations enable radiative transfer (RT) modeling for real-world dynamic processes. To achieve more realistic RT modeling for dynamic forest processes, this study presents the 3D-explicit reconstruction of a typical temperate deciduous forest in 2015 and 2022. We demonstrate for the first time the potential use of bitemporal 3D-explicit RT modeling from terrestrial laser scanning on the forward modeling and quantitative interpretation of: (1) remote sensing (RS) observations of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and canopy light extinction, and (2) the impact of canopy gap dynamics on light availability of explicit locations. Results showed that, compared to the 2015 scene, the hemispherical-directional reflectance factor (HDRF) of the 2022 forest scene relatively decreased by 3.8% and the leaf FAPAR relatively increased by 5.4%. At explicit locations where canopy gaps significantly changed between the 2015 scene and the 2022 scene, only under diffuse light did the branch damage and closing gap significantly impact ground light availability. This study provides the first bitemporal RT comparison based on the 3D RT modeling, which uses one of the most realistic bitemporal forest scenes as the structural input. This bitemporal 3D-explicit forest RT modeling allows spatially explicit modeling over time under fully controlled experimental conditions in one of the most realistic virtual environments, thus delivering a powerful tool for studying canopy light regimes as impacted by dynamics in forest structure and developing RS inversion schemes on forest structural changes.
Keywords: radiative transfer; forest reconstruction; bitemporal; 3D-explicit; terrestrial LiDAR; remote sensing; DART radiative transfer; forest reconstruction; bitemporal; 3D-explicit; terrestrial LiDAR; remote sensing; DART

Share and Cite

MDPI and ACS Style

Liu, C.; Calders, K.; Origo, N.; Terryn, L.; Adams, J.; Gastellu-Etchegorry, J.-P.; Wang, Y.; Meunier, F.; Armston, J.; Disney, M.; et al. Bitemporal Radiative Transfer Modeling Using Bitemporal 3D-Explicit Forest Reconstruction from Terrestrial Laser Scanning. Remote Sens. 2024, 16, 3639. https://doi.org/10.3390/rs16193639

AMA Style

Liu C, Calders K, Origo N, Terryn L, Adams J, Gastellu-Etchegorry J-P, Wang Y, Meunier F, Armston J, Disney M, et al. Bitemporal Radiative Transfer Modeling Using Bitemporal 3D-Explicit Forest Reconstruction from Terrestrial Laser Scanning. Remote Sensing. 2024; 16(19):3639. https://doi.org/10.3390/rs16193639

Chicago/Turabian Style

Liu, Chang, Kim Calders, Niall Origo, Louise Terryn, Jennifer Adams, Jean-Philippe Gastellu-Etchegorry, Yingjie Wang, Félicien Meunier, John Armston, Mathias Disney, and et al. 2024. "Bitemporal Radiative Transfer Modeling Using Bitemporal 3D-Explicit Forest Reconstruction from Terrestrial Laser Scanning" Remote Sensing 16, no. 19: 3639. https://doi.org/10.3390/rs16193639

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