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Remote Sens. 2018, 10(3), 474; https://doi.org/10.3390/rs10030474

Evaluating Eight Global Reanalysis Products for Atmospheric Correction of Thermal Infrared Sensor—Application to Landsat 8 TIRS10 Data

1,2
and
1,2,3,*
1
State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China
2
Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
3
U. S. Department of Agriculture, Agricultural Research Service, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705, USA
*
Author to whom correspondence should be addressed.
Received: 1 February 2018 / Revised: 12 March 2018 / Accepted: 14 March 2018 / Published: 19 March 2018
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Abstract

Global reanalysis products have been widely used for correcting the atmospheric effects of thermal infrared data, but their performances have not been comprehensively evaluated. In this paper, we evaluate eight global reanalysis products (NCEP/FNL; NCEP/DOE Reanalysis2; MERRA-3; MERRA-6; MERRA2-3; MERRA2-6; JRA-55; and ERA-Interim) commonly used in the atmospheric correction of Landsat 8 TIRS10 data by referencing global radiosonde observations collected from 163 stations. The atmospheric parameters (atmospheric transmittance, upward radiance, and downward radiance) simulated with MERRA-6 and ERA-Interim were accurate than those simulated with other reanalysis products for different water vapor contents and surface elevations. When global reanalysis products were applied to retrieve land surface temperature (LST) from simulated Landsat 8 TIRS10 data, ERA-Interim and MERRA-6 were accurate than other reanalysis products. The overall LST biases and RMSEs between the retrieved LSTs and LSTs that were used to generate the top-of-atmosphere radiances were less than 0.2 K and 1.09 K, respectively. When eight reanalysis products were used to estimate LSTs from thirty-two Landsat 8 TIRS10 images covering the Heihe River basin in China, the various reanalysis products showed similar validation accuracies for LSTs with low water vapor contents. The biases ranged from 0.07 K to 0.24 K, and the STDs (RMSEs) ranged from 1.93 K (1.93 K) to 2.02 K (2.04 K). Considering the above evaluation results, MERRA-6 and ERA-Interim are recommended for thermal infrared data atmospheric corrections. View Full-Text
Keywords: Landsat; atmospheric correction; NCEP; MERRA; MERRA2; JRA-55; ERA-Interim Landsat; atmospheric correction; NCEP; MERRA; MERRA2; JRA-55; ERA-Interim
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Meng, X.; Cheng, J. Evaluating Eight Global Reanalysis Products for Atmospheric Correction of Thermal Infrared Sensor—Application to Landsat 8 TIRS10 Data. Remote Sens. 2018, 10, 474.

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