A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives

Cao, Biao; Liu, Qinhuo; Du, Yongming; Roujean, Jean-Louis; Gastellu-Etchegorry, Jean-Philippe; Trigo, Isabel F.; Zhan, Wenfeng; Yu, Yunyue; Cheng, Jie; Jacob, Frédéric; Lagouarde, Jean-Pierre; Bian, Zunjian; Li, Hua; Hu, Tian; Xiao, Qing

doi:10.1016/j.rse.2019.111304

Cited by 196Calibration and Measurement TechniquesRemote Sensing in AgricultureThermal Radiation and Cooling Technologies

A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives

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Cao, Biao, Liu, Qinhuo, Du, Yongming, Roujean, Jean-Louis, Gastellu-Etchegorry, Jean-Philippe, Trigo, Isabel F., Zhan, Wenfeng, Yu, Yunyue +7 more·2019·Remote Sensing of Environment

DOI 10.1016/j.rse.2019.111304

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Abstract

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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Satellite data at 1 km resolution have a relatively high degree of uncertainty, particularly for urban areas.
“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.”
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Performance evaluation of four directional emissivity analytical models with thermal SAIL model and airborne images
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Driving factors of the directional variability of thermal infrared signal in temperate regions
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McGuire, M., Balick, L., Smith, J. A., & Hutchison, B. A. (1989) · Remote Sensing of Environment · doi:10.1016/0034-4257(89)90016-3 · Cited by 39 · see citing works

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Remote sensing for agricultural applications: A meta-review
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Thermal Infrared Remote Sensing of Stress Responses in Forest Environments: a Review of Developments, Challenges, and Opportunities
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Reviews of methods for land surface temperature retrieval from Landsat thermal infrared data
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Synergies between Urban Heat Island and Urban Heat Wave Effects in 9 Global Mega-Regions from 2003 to 2020
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Spatial Downscaling of Land Surface Temperature over Heterogeneous Regions Using Random Forest Regression Considering Spatial Features
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Quantifying the influences of land surface parameters on LST variations based on GeoDetector model in Syr Darya Basin, Central Asia
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Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data
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A mechanism-guided machine learning method for mapping gapless land surface temperature
Ma, J., Shen, H., Jiang, M., Lin, L., Meng, C., Zeng, C., Li, H., & Wu, P. (2024) · Remote Sensing of Environment · doi:10.1016/j.rse.2024.114001 · Cited by 38 · see citing works
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Comparison of the accuracy of daytime land surface temperature retrieval methods using Landsat 8 images in arid regions
Aliabad, F. A., Zare, M., & Malamiri, H. R. G. (2021) · Infrared Physics & Technology · doi:10.1016/j.infrared.2021.103692 · Cited by 38 · see citing works
Is satellite land surface temperature an appropriate proxy for intra-urban variability of daytime heat stress?
Briegel, F., Pinto, J. G., & Christen, A. (2025) · Remote Sensing of Environment · doi:10.1016/j.rse.2025.115045 · Cited by 39 · see citing works
Assessing spatiotemporal variations in land surface temperature and SUHI intensity with a cloud based computational system over five major cities of India
Ghosh, S., Kumar, D., & Kumari, R. (2022) · Sustainable Cities and Society · doi:10.1016/j.scs.2022.104060 · Cited by 35 · see citing works
Atmospheric and emissivity corrections for ground-based thermography using 3D radiative transfer modelling
Morrison, W., Yin, T., Lauret, N., Guilleux, J., Kotthaus, S., Gastellu‐Etchegorry, J., Norford, L. K., & Grimmond, S. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.111524 · Cited by 35 · see citing works
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A TIR forest reflectance and transmittance (FRT) model for directional temperatures with structural and thermal stratification
Bian, Z., Wu, S., Roujean, J., Cao, B., Li, H., Yin, G., Du, Y., Xiao, Q., & Liu, Q. (2021) · Remote Sensing of Environment · doi:10.1016/j.rse.2021.112749 · Cited by 35 · see citing works
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A practical method for angular normalization of global MODIS land surface temperature over vegetated surfaces
Wang, J., Tang, R., Jiang, Y., Liu, M., & Li, Z.-L. (2023) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2023.04.015 · Cited by 34 · see citing works
How does the ambient environment respond to the industrial heat island effects? An innovative and comprehensive methodological paradigm for quantifying the varied cooling effects of different landscapes
Gao, J., Meng, Q., Zhang, L., & Hu, D. (2022) · GIScience & Remote Sensing · doi:10.1080/15481603.2022.2127463 · Cited by 34 · see citing works
A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data
Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022) · Remote Sensing · doi:10.3390/rs14205170 · Cited by 31 · see citing works
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A thermal radiation directionality correction method for the surface upward longwave radiation of geostationary satellite based on a time-evolving kernel-driven model
Qin, B., Cao, B., Roujean, J., Gastellu‐Etchegorry, J., Ermida, S. L., Bian, Z., Du, Y., Hu, T., Li, H., Xiao, Q., et al. (2023) · Remote Sensing of Environment · doi:10.1016/j.rse.2023.113599 · Cited by 30 · see citing works
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A framework of correcting the angular effect of land surface temperature on evapotranspiration estimation in single-source energy balance models
Jiang, Y., Tang, R., & Li, Z.-L. (2022) · Remote Sensing of Environment · doi:10.1016/j.rse.2022.113306 · Cited by 29 · see citing works
Urban surface temperature observations from ground-based thermography: intra- and inter-facet variability
Morrison, W., Kotthaus, S., & Grimmond, S. (2020) · Urban Climate · doi:10.1016/j.uclim.2020.100748 · Cited by 28 · see citing works
Assessment of different kernel-driven models for daytime urban thermal radiation directionality simulation
Jiang, L., Zhan, W., Hu, L., Huang, F., Hong, F., Liu, Z., Lai, J., & Wang, C. (2021) · Remote Sensing of Environment · doi:10.1016/j.rse.2021.112562 · Cited by 28 · see citing works
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A semi-empirical approach for modeling the vegetation thermal infrared directional anisotropy of canopies based on using vegetation indices
Bian, Z., Roujean, J., Lagouarde, J., Cao, B., Li, H., Du, Y., Liu, Q., Xiao, Q., & Liu, Q. (2019) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.12.004 · Cited by 27 · see citing works
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An Operational Split-Window Algorithm for Retrieving Land Surface Temperature from Geostationary Satellite Data: A Case Study on Himawari-8 AHI Data
Li, R., Li, H., Sun, L., Yang, Y., Hu, T., Bian, Z., Cao, B., Du, Y., & Liu, Q. (2020) · Remote Sensing · doi:10.3390/rs12162613 · Cited by 27 · see citing works
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Simulating satellite urban land surface temperatures: sensitivity to sensor view angle and assumed landscape complexity
Morrison, W., Grimmond, S., & Kotthaus, S. (2023) · Remote Sensing of Environment · doi:10.1016/j.rse.2023.113579 · Cited by 27 · see citing works
Assessing urban surface thermal environment and heat health risk in Chinese cities: A twenty-year study
Zhang, C., Yang, Y., & Yu, L. (2025) · Urban Climate · doi:10.1016/j.uclim.2025.102304 · Cited by 26 · see citing works
The 4SAILT Model: An Improved 4SAIL Canopy Radiative Transfer Model for Sloping Terrain
Shi, H., & Xiao, Z. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3022874 · Cited by 26 · see citing works
A practical method for angular normalization on land surface temperature using space between thermal radiance and fraction of vegetation cover
Teng, Y., Ren, H., Zhu, J., Jiang, C., Ye, X., & Zeng, H. (2023) · Remote Sensing of Environment · doi:10.1016/j.rse.2023.113558 · Cited by 26 · see citing works
An Operational Split-Window Algorithm for Generating Long-Term Land Surface Temperature Products From Chinese Fengyun-3 Series Satellite Data
Li, H., Li, R., Tu, H., Cao, B., Liu, F., Bian, Z., Hu, T., Du, Y., Sun, L., & Liu, Q. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3315968 · Cited by 24 · see citing works
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Local surface warming assessment in response to vegetation shifts over arid lands of Central Asia (2001−2020)
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Quantifying Thermal Infra-Red directional anisotropy using Master and Landsat-8 simultaneous acquisitions
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Research on ultraviolet degradation behavior and aging mechanisms of fluorosilicone rubber in simulated tropical marine atmospheric environment
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Fine scale optical remote sensing experiment of mixed stand over complex terrain (FOREST) in the Genhe Reserve Area: objective, observation and a case study
Cao, B., Qi, J., Chen, E., Xiao, Q., Liu, Q., & Li, Z. (2021) · International Journal of Digital Earth · doi:10.1080/17538947.2021.1968047 · Cited by 22 · see citing works
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Retrieving Land Surface Temperature From Chinese FY-3D MERSI-2 Data Using an Operational Split Window Algorithm
Tang, K., Zhu, H., Ni, P., Li, R., & Fan, C. (2021) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2021.3075698 · Cited by 20 · see citing works
Retrieving Soil and Vegetation Temperatures From Dual-Angle and Multipixel Satellite Observations
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Diurnal variations in directional brightness temperature over urban areas through a multi-angle UAV experiment
Jiang, L., Zhan, W., Tu, L., Dong, P., Wang, S., Li, L., Wang, C., & Wang, C. (2022) · Building and Environment · doi:10.1016/j.buildenv.2022.109408 · Cited by 19 · see citing works
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Impact of 3-D structures on directional effective emissivity in urban areas based on DART model
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The Effects of Tree Trunks on the Directional Emissivity and Brightness Temperatures of a Leaf-Off Forest Using a Geometric Optical Model
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The importance of total hemispherical emittance in evaluating performance of building-integrated silicon and perovskite solar cells in insulated glazings
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Urban thermal anisotropies by local climate zones: An assessment using multi-angle land surface temperatures from ECOSTRESS
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Assessment of an extended SPARSE model for estimating evapotranspiration from directional thermal infrared data
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Ground validation of land surface temperature and surface emissivity from thermal infrared remote sensing data
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The anisotropy of MODIS LST in urban areas: A perspective from different time scales using model simulations
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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: Cao, Biao
Liu, Qinhuo
Du, Yongming
Roujean, Jean-Louis
Gastellu-Etchegorry, Jean-Philippe
Trigo, Isabel F.
Zhan, Wenfeng
Yu, Yunyue
Cheng, Jie
Jacob, Frédéric
Bian, Zunjian
Li, Hua
Hu, Tian
Xiao, Qing
Venue: Remote Sensing of Environment
Publisher: Elsevier BV
Published: 2019-10
Volume: 232
Pages: 111304
ISSN: 0034-4257 (ISSN-L)
DOI: 10.1016/j.rse.2019.111304
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: cc-by
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
creativecommons.org/licenses/by/4.0/ (vor)
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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A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives

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