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A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives
Open accessAbstract
The Earth surface thermal infrared (TIR) radiation shows conspicuously an anisotropic behavior just like the bi-directional reflectance of visible and near infrared spectral domains. The importance of thermal radiation directionality (TRD) is being more and more widely recognized in the applications because of the magnitude of the effects generated. The effects of TRD were originally evidenced through experiments in 1962, showing that two sensors simultaneously measuring temperature of the same scene may get significantly different values when the viewing geometry is different. Such effect limits inter-comparison of measurement datasets and land surface temperature (LST) products acquired at different view angles, while raising the question of measurement reliability when used to characterize land surface processes. These early experiments fostered the development of modeling approaches to quantify TRD with the aim of developing a correction for Earth surface TIR radiation. Initiatives for pushing the analysis of TIR data through modeling have been lasted since 1970s. They were initially aimed at mimicking the observed TIR radiance with consideration of canopy structure, component emissivities and temperatures, and Earth surface energy exchange processes. Presently, observing the Earth surface TRD effect is still a challenging task because the TIR status changes rapidly. Firstly, a brief theoretical background and the basic radiative transfer equation are presented. Then, this paper reviews the historical development and current status of observing TRD in the laboratory, in-situ, from airborne and space-borne platforms. Accordingly, the TRD model development, including radiative transfer models, geometric models, hybrid models, 3D models, and parametric models are reviewed for surfaces of water, ice and sea, snow, barren lands, vegetation and urban landscapes, respectively. Next, we introduce three potential applications, including normalizing the LST products, estimating the hemispheric upward longwave radiation using multi-angular TIR observations and separating surface component temperatures. Finally, we give hints and directions for future research work. The last section summarizes the study and stresses three main conclusions.
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“In contrast, although satellite data are available at a resolution of 1 km, this pixel-level data have a relatively high degree of uncertainty, particularly for urban areas80.”
From Disproportionate exposure to urban heat island intensity across major US cities (2021) · cites this paper as [80]
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Shi, H. (2026) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2026.3717292
Na, Q., Cao, B., Ermida, S. L., Qin, B., Yang, Z., Zhang, X., Zheng, L., Bian, Z., Du, Y., Li, H., et al. (2026) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2026.3720233
Self-citationZhu, Z., Wang, D., Cao, B., Bian, Z., Li, J., Liu, X., & Dong, Q. (2026) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2026.3726626
Self-citationAdvanced Multi-Angle Remote Sensing Observation of Vegetation Canopy Leveraging UAV Platform
Wang, R., Wang, Z., Liu, L., Jia, W., Liu, Y., Liu, Z., Mu, X., Wang, T., Qiu, F., Zhang, X., et al. (2026) · Forests · doi:10.3390/f17091039
Snyders, L., Blommaert, J. A. D. L., León-Tavares, J., Langsdale, M., & Genesio, L. (2026) · Remote Sensing · doi:10.3390/rs18203525
Metadata
- Authors
- Cao, B., Liu, Q., Du, Y., Roujean, J.-L., Gastellu-Etchegorry, J.-P., Trigo, I. F., Zhan, W., Yu, Y., Cheng, J., Jacob, F., Lagouarde, J.-P., Bian, Z., Li, H., Hu, T., & Xiao, Q.
- Affiliations
- Chinese Academy of Sciences (CN)
- Centre National de la Recherche Scientifique (FR)
- Portuguese Sea and Atmosphere Institute (PT)
- Nanjing University (CN)
- National Oceanic and Atmospheric Administration (US)
- Beijing Normal University (CN)
- Université de Montpellier (FR)
- Interaction Sol Plante Atmosphère (FR)
- Griffith University (AU)
- Corresponding author
- Liu, Qinhuo
- ORCID
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2019-10
- Volume
- 232
- Pages
- 111304
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W2963663407
- Cited by
- 196
- References
- 282
- Citations by year
- 2026: 18 · 2025: 43 · 2024: 40 · 2023: 26 · 2022: 12 · 2021: 31 · 2020: 17 · 2019: 8
- FWCI
- 12.50
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Remote Sensing of Environment (publishedVersion, cc-by)
- HAL (submittedVersion, cc-by)
- HAL (submittedVersion)
- NOAA Institutional Repository (submittedVersion)
- Griffith Research Online (submittedVersion, cc-by)
- Funders
- Chinese Academy of Sciences (XDA15012400)
- Institute of Remote Sensing and Digital Earth (Y5SJ1300CX)
- National Natural Science Foundation of China (41571359, 41671366, 41571357, 41501366, 41871258, 41571329)
- National Key Research and Development Program of China (2018YFA0605503)
- China Scholarship Council (201704910069, 2017VCA0034, 2019DC0020, 2017VCC0011)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Calibration and Measurement Techniques
- Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
- Physical Sciences › Engineering › Civil and Structural Engineering › Thermal Radiation and Cooling Technologies
- Keywords
- land surface temperature, radiative transfer modeling, thermal anisotropy, surface emissivity, snow and ice surfaces, vegetation surface, urban surfaces, barren land
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