A practical method for angular normalization of global MODIS land surface temperature over vegetated surfaces

Land surface temperature (LST) is an essential physical quantity in surface energy balance and a good indicator of exchange of heat and water between the land and atmosphere at regional and global scales. However, the thermal-infrared remotely sensed LST from large swath-width polar-orbiting and geo...

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Published inISPRS journal of photogrammetry and remote sensing Vol. 199; pp. 289 - 304
Main Authors Wang, Junrui, Tang, Ronglin, Jiang, Yazhen, Liu, Meng, Li, Zhao-Liang
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.05.2023
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Abstract Land surface temperature (LST) is an essential physical quantity in surface energy balance and a good indicator of exchange of heat and water between the land and atmosphere at regional and global scales. However, the thermal-infrared remotely sensed LST from large swath-width polar-orbiting and geostationary satellite sensors is usually subject to the angular anisotropy, bringing great uncertainties in the application of LST products in many fields such as evapotranspiration estimation, urban thermal environment monitoring, and climate change study. In this study, a practical angular normalization method was developed for the first time for correcting global MODIS off-nadir LST to nadir over vegetated surfaces, using MODIS (Terra + Aqua) products from 2000 to 2020, simultaneous and collocated observations at 213 sites worldwide from the AmeriFlux, FLUXNET, and National Tibetan Plateau/Third Pole Environment Data Center (TPDC), and ERA5-Land reanalysis datasets. Results showed that the angular normalization method could well correct the angular anisotropy of MODIS LST products. Validated against datasets at 213 sites, the angular normalization model showed root mean square errors (RMSE) of 1.57 K, mean bias errors (MBE) of 0 K, and coefficient of determination (R2) of 0.99. In the cross-validation of nadir LST by correcting global MODIS/Terra off-nadir LST products against Sentinel-3A nadir LST products over four typical days in 2020 (February 26, June 1, August 12 and November 16), the angular normalization model presented the RMSE of 2.26 K and the MBE of −1.20 K, in contrast to the RMSE of 3.01 K and the MBE of −2.15 K when MODIS off-nadir LST was compared to the Sentinel-3A nadir LST. The angular anisotropy of global MODIS/Terra LST over vegetated surfaces for the four days of interest ranged between −1.79 to −1.30 K (1% quantile) and 3.64 to 4.37 K (99% quantile), with a median of 0.33 to 0.74 K, and a mean of 0.46 to 0.89 K. The developed angular normalization model is a promising approach to operationally correcting all time-series of global MODIS/Terra and MODIS/Aqua LST products with high accuracies, which is significant to provide a benchmark of angle-consistent MODIS LST product for its further application.
AbstractList Land surface temperature (LST) is an essential physical quantity in surface energy balance and a good indicator of exchange of heat and water between the land and atmosphere at regional and global scales. However, the thermal-infrared remotely sensed LST from large swath-width polar-orbiting and geostationary satellite sensors is usually subject to the angular anisotropy, bringing great uncertainties in the application of LST products in many fields such as evapotranspiration estimation, urban thermal environment monitoring, and climate change study. In this study, a practical angular normalization method was developed for the first time for correcting global MODIS off-nadir LST to nadir over vegetated surfaces, using MODIS (Terra + Aqua) products from 2000 to 2020, simultaneous and collocated observations at 213 sites worldwide from the AmeriFlux, FLUXNET, and National Tibetan Plateau/Third Pole Environment Data Center (TPDC), and ERA5-Land reanalysis datasets. Results showed that the angular normalization method could well correct the angular anisotropy of MODIS LST products. Validated against datasets at 213 sites, the angular normalization model showed root mean square errors (RMSE) of 1.57 K, mean bias errors (MBE) of 0 K, and coefficient of determination (R²) of 0.99. In the cross-validation of nadir LST by correcting global MODIS/Terra off-nadir LST products against Sentinel-3A nadir LST products over four typical days in 2020 (February 26, June 1, August 12 and November 16), the angular normalization model presented the RMSE of 2.26 K and the MBE of −1.20 K, in contrast to the RMSE of 3.01 K and the MBE of −2.15 K when MODIS off-nadir LST was compared to the Sentinel-3A nadir LST. The angular anisotropy of global MODIS/Terra LST over vegetated surfaces for the four days of interest ranged between −1.79 to −1.30 K (1% quantile) and 3.64 to 4.37 K (99% quantile), with a median of 0.33 to 0.74 K, and a mean of 0.46 to 0.89 K. The developed angular normalization model is a promising approach to operationally correcting all time-series of global MODIS/Terra and MODIS/Aqua LST products with high accuracies, which is significant to provide a benchmark of angle-consistent MODIS LST product for its further application.
Land surface temperature (LST) is an essential physical quantity in surface energy balance and a good indicator of exchange of heat and water between the land and atmosphere at regional and global scales. However, the thermal-infrared remotely sensed LST from large swath-width polar-orbiting and geostationary satellite sensors is usually subject to the angular anisotropy, bringing great uncertainties in the application of LST products in many fields such as evapotranspiration estimation, urban thermal environment monitoring, and climate change study. In this study, a practical angular normalization method was developed for the first time for correcting global MODIS off-nadir LST to nadir over vegetated surfaces, using MODIS (Terra + Aqua) products from 2000 to 2020, simultaneous and collocated observations at 213 sites worldwide from the AmeriFlux, FLUXNET, and National Tibetan Plateau/Third Pole Environment Data Center (TPDC), and ERA5-Land reanalysis datasets. Results showed that the angular normalization method could well correct the angular anisotropy of MODIS LST products. Validated against datasets at 213 sites, the angular normalization model showed root mean square errors (RMSE) of 1.57 K, mean bias errors (MBE) of 0 K, and coefficient of determination (R2) of 0.99. In the cross-validation of nadir LST by correcting global MODIS/Terra off-nadir LST products against Sentinel-3A nadir LST products over four typical days in 2020 (February 26, June 1, August 12 and November 16), the angular normalization model presented the RMSE of 2.26 K and the MBE of −1.20 K, in contrast to the RMSE of 3.01 K and the MBE of −2.15 K when MODIS off-nadir LST was compared to the Sentinel-3A nadir LST. The angular anisotropy of global MODIS/Terra LST over vegetated surfaces for the four days of interest ranged between −1.79 to −1.30 K (1% quantile) and 3.64 to 4.37 K (99% quantile), with a median of 0.33 to 0.74 K, and a mean of 0.46 to 0.89 K. The developed angular normalization model is a promising approach to operationally correcting all time-series of global MODIS/Terra and MODIS/Aqua LST products with high accuracies, which is significant to provide a benchmark of angle-consistent MODIS LST product for its further application.
Author Jiang, Yazhen
Wang, Junrui
Tang, Ronglin
Li, Zhao-Liang
Liu, Meng
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TaERA5
ASPECTSTD
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Land surface temperature
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Snippet Land surface temperature (LST) is an essential physical quantity in surface energy balance and a good indicator of exchange of heat and water between the land...
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SubjectTerms Angular anisotropy
Angular normalization
anisotropy
China
climate change
data collection
energy balance
evapotranspiration
heat
Land surface temperature
MODIS
photogrammetry
satellites
surface temperature
time series analysis
Title A practical method for angular normalization of global MODIS land surface temperature over vegetated surfaces
URI https://dx.doi.org/10.1016/j.isprsjprs.2023.04.015
https://www.proquest.com/docview/2834272073
Volume 199
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