Academic Journal
Evaluation of Three Modeling Frameworks of Thermal Infrared Radiative Transfer for Directional Anisotropies of Temperatures
| Τίτλος: | Evaluation of Three Modeling Frameworks of Thermal Infrared Radiative Transfer for Directional Anisotropies of Temperatures |
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| Συγγραφείς: | Zunjian Bian, J. L. Roujean, Mark Irvine, Hua Li, Fan Mo, Yao Chen, Biao Cao, Yongming Du, Qing Xiao, Qinhuo Liu |
| Συνεισφορές: | ROUJEAN, JEAN-LOUIS, Aerospace Information Research Institute (AIRICAS), Chinese Academy of Sciences Beijing (CAS), Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Chinese Academy of Sciences Beijing (UCAS) |
| Πηγή: | IEEE Transactions on Geoscience and Remote Sensing. 63:1-15 |
| Στοιχεία εκδότη: | Institute of Electrical and Electronics Engineers (IEEE), 2025. |
| Έτος έκδοσης: | 2025 |
| Θεματικοί όροι: | [SDE.IE]Environmental Sciences/Environmental Engineering, [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis, land surface temperature, FRT model, [SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces, environment, Vegetation canopies, directional anisotropy, EOF analysis, Angular uncertainty, [SDE.IE] Environmental Sciences/Environmental Engineering, Statistics and Probability [physics.data-an], [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Directional anisotropy, [PHYS.PHYS.PHYS-DATA-AN] Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an], Land surface temperature |
| Περιγραφή: | Radiative transfer models (RTMs) designed to reproduce the anisotropy of surface brightness temperature are particularly useful for applications on Earth’s energy budget when using remote sensing data sets. Despite the fact that several thermal infrared (TIR) RTMs have been developed, a quantitative analysis comparing the benefits and limits of these models remains necessary. Herein, three modeling frameworks (physical hybrid, analytical parameterization, kernel-driven) have been evaluated comparatively for a homogeneous vegetation, a row-planted crop and a sparse forest. Airborne measurements and the Discrete Anisotropy Radiative Transfer (DART) model simulations were retained as the benchmark. Forward modeling and inverse fitting schemes were proposed for the sake of comparison. Results reveal that: 1) in the forward modeling scheme, from airborne measurements, the hybrid model performs better with RMSEs of 0.17℃, 1.57℃, and 0.38℃ for homogenous, row-planted vineyard and sparse forest scenes, respectively; the analytical model appears similar performant (0.17℃, 0.40 ℃) for the homogeneous and sparse forest scenes, but less performant (2.39℃) for the row-planted scene; 2) In the inverse fitting scheme, the uncertainties (95% of probability) of model coefficients and predicted directional anisotropies were considered. The kernel-driven model has fewer modeling constraints and statistically performs better for the homogeneous and sparse forest scenes with RMSEs of 0.07 ℃ and 0.19 ℃, respectively whereas it is less efficient for the row-planted scene with RMSE of 0.80 ℃. This study highlights the differences of accuracy between models of different complexity, and provides reference information for researchers to improve existing models and for users to choose their best modeling solution. |
| Τύπος εγγράφου: | Article |
| Περιγραφή αρχείου: | application/pdf |
| ISSN: | 1558-0644 0196-2892 |
| DOI: | 10.1109/tgrs.2025.3530503 |
| Σύνδεσμος πρόσβασης: | https://hal.science/hal-04902255v1 https://doi.org/10.1109/tgrs.2025.3530503 https://hal.science/hal-04902255v1/document |
| Rights: | IEEE Copyright |
| Αριθμός Καταχώρησης: | edsair.doi.dedup.....974e8e7c989d5e5f6899e1c759b59dc4 |
| Βάση Δεδομένων: | OpenAIRE |
| ISSN: | 15580644 01962892 |
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| DOI: | 10.1109/tgrs.2025.3530503 |