Reconstructing the digital twin of forests from a 3D library: Quantifying trade-offs for radiative transfer modeling

Chang Liu; Kim Calders; Niall Origo; Mathias Disney; Félicien Meunier; William Woodgate; Jean-Philippe Gastellu-Etchegorry; Joanne Nightingale; Eija Honkavaara; Teemu Hakala; Lauri Markelin; Hans Verbeeck

doi:10.1016/j.rse.2023.113832

journal article Dec 01, 2023

Reconstructing the digital twin of forests from a 3D library: Quantifying trade-offs for radiative transfer modeling

Chang Liu

Kim Calders

Niall Origo Mathias Disney

Félicien Meunier William Woodgate

Jean-Philippe Gastellu-Etchegorry Joanne Nightingale Eija Honkavaara

Teemu Hakala Lauri Markelin Hans Verbeeck

Remote Sensing of Environment Vol. 298 pp. 113832 · Elsevier BV

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Citations

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References

Details

Published: Dec 01, 2023
Vol/Issue: 298
Pages: 113832
License: View

Authors

C

Chang Liu

Universiti Malaysia Kelantan

K

Kim Calders

Computational & Applied Vegetation Ecology Laboratory, Department of Environment, Ghent University, Belgium.; School of Forest Sciences, University of Eastern Finland, Joensuu, Finland.

Jean-Philippe Gastellu-Etchegorry

Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (National Land Survey of Finland), Masala, Finland

Funding

Australian Research Council Award: DE190101182

European Commission

China Scholarship Council Award: 201906600031

Université Catholique de Louvain

Academy of Finland Award: 327861

National Centre for Earth Observation

Cite This Article

Chang Liu, Kim Calders, Niall Origo, et al. (2023). Reconstructing the digital twin of forests from a 3D library: Quantifying trade-offs for radiative transfer modeling. Remote Sensing of Environment, 298, 113832. https://doi.org/10.1016/j.rse.2023.113832

Reconstructing the digital twin of forests from a 3D library: Quantifying trade-offs for radiative transfer modeling

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