| Autor: |
Omar Regaieg, Nicolas Lauret, Yingjie Wang, Jordan Guilleux, Eric Chavanon, Jean-Philippe Gastellu-Etchegorry |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
International Journal of Applied Earth Observations and Geoinformation, Vol 118, Iss , Pp 103254- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1569-8432 |
| DOI: |
10.1016/j.jag.2023.103254 |
| Popis: |
Remote sensing (RS) of solar-induced chlorophyll fluorescence (SIF) has a great potential for monitoring plant photosynthetic activity. Radiative transfer models (RTM) are essential to better interpret and extract information from SIF signals. DART is one of the most comprehensive and accurate 3D RTMs. Its standard mode DART-FT simulates SIF using a discrete ordinates method but is not adapted to large landscapes due to computational constraints. DART-Lux, the new mode based on a bi-directional path tracing algorithm, greatly improves DART computational efficiency for simulating images. This paper presents the theory of a novel SIF modelling algorithm in DART-Lux. We verified its accuracy with DART-FT and the SCOPE model for three types of canopies: turbid medium, maize field and forest. DART-Lux closely matches DART-FT (relative difference |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full Text from ScienceDirect