TY - JOUR
T1 - Preflight radiometric calibration of TIS sensor onboard SDG-1 satellite and estimation of its LST retrieval ability
AU - Liu, Wanyue
AU - Li, Jiaguo
AU - Zhang, Ying
AU - Zhao, Limin
AU - Cheng, Qiuming
N1 - Funding Information:
Funding: This research was funded by Strategic Priority Research Program of Chinese Academy of Sciences, grant number XDA19010403 and National Key Research and Development Program of China, grant number 2019YFE0126600.
Funding Information:
Acknowledgments: The authors would like to thank Fansheng Chen and Zhuoyue Hu at Shanghai Institute of Technical Physics, Chinese Academy of Science, for providing the prototype of TIS with its laboratory results. This study was also funded by China Scholarship Council (CSC).
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/8/16
Y1 - 2021/8/16
N2 - The thermal Infrared Spectrometer (TIS) is the thermal infrared (TIR) sensor on-board the first Sustainable Development Goals (SDG-1) satellite. The TIS data can potentially be used to support improved monitoring of ground conditions with high-spatial resolutions, so accurate radiometric calibration is required. A meticulous radiometric calibration was conducted on the prototype of TIS to test its ability to convert a raw digital number (DN) to at-aperture radiance. The initial maximum radiometric error was 2.19 K at 300 K for Band 1(B1) and the minimum radiometric error was 0.25 K at 300 K rooted in Band 3 (B3). The R-Squared (R2) was over 0.99 for each band. The methodology was refined to divide the channel detectable temperature range into three sub-ranges and then the maximum radiometric errors were reduced to less than 1 K at 300 K for three bands. Subsequently, the Generalized Split-Window (SW) algorithm was preformed to estimate the ability of TIS on land surface temperature (LST) retrieval. In order to take advantage of its high-spatial resolution and make full use of TIR data, three-channel SW algorithm was also performed for intercomparison. Results showed that the SW algorithm can obtain LST with root-mean-square error (RMSE) less than 1K. Compared with two-channel algorithm with RMSE = 0.94 K, three-channel algorithm achieves better results in retrieving LST with RMSE = 0.82 K. For different land surface types, water samples achieved the minimum RMSE, and for different atmospheric column water vapor (CWV), dry atmospheres obtained better results. The sensitivity analysis of SW algorithm was considered along with noise-equivalent differential temperature (NEDT), uncertainty of land surface emissivity (LSE) and input land surface temperature (Ts). Generally, three-channel algorithm was more stable to LSE uncertainties, and the error changes were within 40%. But when NEΔT and Ts uncertainties were included, the error percentage of three-channel SW method increases more, which means three-channel SW method is more sensitive to those two factors. All in all, the methodology and results used for radiometric calibration and LST retrieval in this study provide valuable guidance for the flight model of TIS and post-launch applications.
AB - The thermal Infrared Spectrometer (TIS) is the thermal infrared (TIR) sensor on-board the first Sustainable Development Goals (SDG-1) satellite. The TIS data can potentially be used to support improved monitoring of ground conditions with high-spatial resolutions, so accurate radiometric calibration is required. A meticulous radiometric calibration was conducted on the prototype of TIS to test its ability to convert a raw digital number (DN) to at-aperture radiance. The initial maximum radiometric error was 2.19 K at 300 K for Band 1(B1) and the minimum radiometric error was 0.25 K at 300 K rooted in Band 3 (B3). The R-Squared (R2) was over 0.99 for each band. The methodology was refined to divide the channel detectable temperature range into three sub-ranges and then the maximum radiometric errors were reduced to less than 1 K at 300 K for three bands. Subsequently, the Generalized Split-Window (SW) algorithm was preformed to estimate the ability of TIS on land surface temperature (LST) retrieval. In order to take advantage of its high-spatial resolution and make full use of TIR data, three-channel SW algorithm was also performed for intercomparison. Results showed that the SW algorithm can obtain LST with root-mean-square error (RMSE) less than 1K. Compared with two-channel algorithm with RMSE = 0.94 K, three-channel algorithm achieves better results in retrieving LST with RMSE = 0.82 K. For different land surface types, water samples achieved the minimum RMSE, and for different atmospheric column water vapor (CWV), dry atmospheres obtained better results. The sensitivity analysis of SW algorithm was considered along with noise-equivalent differential temperature (NEDT), uncertainty of land surface emissivity (LSE) and input land surface temperature (Ts). Generally, three-channel algorithm was more stable to LSE uncertainties, and the error changes were within 40%. But when NEΔT and Ts uncertainties were included, the error percentage of three-channel SW method increases more, which means three-channel SW method is more sensitive to those two factors. All in all, the methodology and results used for radiometric calibration and LST retrieval in this study provide valuable guidance for the flight model of TIS and post-launch applications.
KW - LST retrieval
KW - Radiometric calibration
KW - The first Sustainable Development Goals (SDG-1) satellite
KW - Thermal infrared (TIR)
KW - Thermal Infrared Spectrometer (TIS)
KW - ITC-ISI-JOURNAL-ARTICLE
KW - ITC-GOLD
UR - https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2021/isi/li_pre.pdf
U2 - 10.3390/rs13163242
DO - 10.3390/rs13163242
M3 - Article
AN - SCOPUS:85113674676
VL - 13
SP - 1
EP - 17
JO - Remote sensing
JF - Remote sensing
SN - 2072-4292
IS - 16
M1 - 3242
ER -