Bi-directional Monte-Carlo modelling of solar-induced chlorophyll fluorescence images for 3D vegetation canopies in the DART model
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 RT...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223000766 |
| _version_ | 1797842878216536064 |
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| author | Omar Regaieg Nicolas Lauret Yingjie Wang Jordan Guilleux Eric Chavanon Jean-Philippe Gastellu-Etchegorry |
| author_facet | Omar Regaieg Nicolas Lauret Yingjie Wang Jordan Guilleux Eric Chavanon Jean-Philippe Gastellu-Etchegorry |
| author_sort | Omar Regaieg |
| collection | DOAJ |
| description | 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 < 2%) with much better computational efficiency depending on the scene complexity, number of spectral bands and needed accuracy. For example, simulation time is reduced by a factor of ≈48, and memory usage by ≈50 for a maize field at 1 cm resolution. It allowed to simulate SIF images of large scenes as the 3×3km2 Ripperdan agricultural site that DART-FT could not simulate. The new SIF modelling algorithm opens new horizons for RS studies of large and complex landscapes. It is available as part of released DART versions (v1152 onwards) (https://dart.omp.eu/). |
| first_indexed | 2024-04-09T16:55:17Z |
| format | Article |
| id | doaj.art-db6cc36206384749957333416ccb5b03 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-09T16:55:17Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-db6cc36206384749957333416ccb5b032023-04-21T06:41:12ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-04-01118103254Bi-directional Monte-Carlo modelling of solar-induced chlorophyll fluorescence images for 3D vegetation canopies in the DART modelOmar Regaieg0Nicolas Lauret1Yingjie Wang2Jordan Guilleux3Eric Chavanon4Jean-Philippe Gastellu-Etchegorry5Corresponding author.; CESBIO - UPS, CNES, CNRS, IRD, Université de Toulouse, 31401 Toulouse cedex 9, FranceCESBIO - UPS, CNES, CNRS, IRD, Université de Toulouse, 31401 Toulouse cedex 9, FranceCESBIO - UPS, CNES, CNRS, IRD, Université de Toulouse, 31401 Toulouse cedex 9, FranceCESBIO - UPS, CNES, CNRS, IRD, Université de Toulouse, 31401 Toulouse cedex 9, FranceCESBIO - UPS, CNES, CNRS, IRD, Université de Toulouse, 31401 Toulouse cedex 9, FranceCESBIO - UPS, CNES, CNRS, IRD, Université de Toulouse, 31401 Toulouse cedex 9, FranceRemote 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 < 2%) with much better computational efficiency depending on the scene complexity, number of spectral bands and needed accuracy. For example, simulation time is reduced by a factor of ≈48, and memory usage by ≈50 for a maize field at 1 cm resolution. It allowed to simulate SIF images of large scenes as the 3×3km2 Ripperdan agricultural site that DART-FT could not simulate. The new SIF modelling algorithm opens new horizons for RS studies of large and complex landscapes. It is available as part of released DART versions (v1152 onwards) (https://dart.omp.eu/).http://www.sciencedirect.com/science/article/pii/S1569843223000766SIFRemote sensingBi-directional path tracing3D vegetation structureDART |
| spellingShingle | Omar Regaieg Nicolas Lauret Yingjie Wang Jordan Guilleux Eric Chavanon Jean-Philippe Gastellu-Etchegorry Bi-directional Monte-Carlo modelling of solar-induced chlorophyll fluorescence images for 3D vegetation canopies in the DART model International Journal of Applied Earth Observations and Geoinformation SIF Remote sensing Bi-directional path tracing 3D vegetation structure DART |
| title | Bi-directional Monte-Carlo modelling of solar-induced chlorophyll fluorescence images for 3D vegetation canopies in the DART model |
| title_full | Bi-directional Monte-Carlo modelling of solar-induced chlorophyll fluorescence images for 3D vegetation canopies in the DART model |
| title_fullStr | Bi-directional Monte-Carlo modelling of solar-induced chlorophyll fluorescence images for 3D vegetation canopies in the DART model |
| title_full_unstemmed | Bi-directional Monte-Carlo modelling of solar-induced chlorophyll fluorescence images for 3D vegetation canopies in the DART model |
| title_short | Bi-directional Monte-Carlo modelling of solar-induced chlorophyll fluorescence images for 3D vegetation canopies in the DART model |
| title_sort | bi directional monte carlo modelling of solar induced chlorophyll fluorescence images for 3d vegetation canopies in the dart model |
| topic | SIF Remote sensing Bi-directional path tracing 3D vegetation structure DART |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223000766 |
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