A Novel Intercalibration Method for Fengyun(FY)-3 VIRR Using MERSI Onboard the Same Satellite Based on Pseudo-Invariant Pixels

This study presents a novel approach to the radiometric intercalibration between two sensors onboard the same satellite based on pseudo-invariant pixels (PIPs) using iteratively reweighted multivariate alteration detection (IR-MAD) method. The IR-MAD algorithm can statistically select PIPs from the...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2024, Vol.62, p.1-17
Main Authors: Wang, Junwei, Hu, Xiuqing, Gao, Kun, He, Yuqing, Wang, Ling, Li, Guorong, Xu, Na, Zhang, Peng
Format: Article
Language:English
Subjects:
Algorithms
Calibration
Degradation
Image acquisition
Image processing
Infrared radiometers
Intercalibration
Invariants
iteratively reweighted multivariate alteration detection (IR-MAD)
medium resolution spectral imager (MERSI)
Pixels
pseudo-invariant pixels (PIPs)
Radiometers
Radiometry
Reflectance
Satellite broadcasting
Satellites
Sensor systems
Sensors
Spatial distribution
Statistical analysis
Uncertainty
visible infrared radiometer (VIRR)
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Summary:This study presents a novel approach to the radiometric intercalibration between two sensors onboard the same satellite based on pseudo-invariant pixels (PIPs) using iteratively reweighted multivariate alteration detection (IR-MAD) method. The IR-MAD algorithm can statistically select PIPs from the multispectral image pair to assess the radiometric differences between them. Analysis of multiple image pairs from different acquisition times can provide long-term intercalibration results for the two sensors. The procedure is applied to Fengyun(FY)-3A&3B visible infrared radiometer (VIRR), with the medium resolution spectral imager (MERSI) onboard the same platform as the reference. Consistency of the spatial distribution of the PIPs selected by IR-MAD with pseudo-invariant calibration sites (PICSs) given by other scientists demonstrates the effectiveness of our method. The long-term time series trending of top-of-atmosphere (TOA) VIRR reflectance over LIBYA1 and LIBYA4 after intercalibration correction shows that the intercalibrated VIRR has good agreement with MERSI, with a mean bias of less than 1% and an uncertainty of less than 2% for most channels. The approach requires no prior knowledge of the intercalibration targets and extends PICS to the pixel-level targets, which results in more diverse samples, broader dynamic ranges, and lower uncertainty, yielding consistent and reliable long-term intercalibration results.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2024.3376580