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The Multi-angle Polarization Imager (MAI) is the first multi-angle polarization imaging instrument operating in orbit in China. It is important to the development of the polarized remote sensing technology. This study uses onorbit polarization calibration of the MAI based on sunglint over the ocean to determine the accuracy of the MAI data and to lay the foundations for the study of clouds and aerosols using this instrument. The retrieved degree of polarization at the top of atmosphere (TOA) is in good agreement with the degree of polarization simulated by the Second Simulation of a Satellite Signal in the Solar Spectrum -Vector (6SV) radiation transfer mode with a correlation coefficient of 0.992 and a method uncertainty of <1%. The calibration pixels are selected by combining the theoretical analysis and 6SV simulation, and the MAI on-orbit polarization calibration test is carried out using the selected pixels. There is good agreement between the retrieved degree of polarization at the TOA and the measured degree of polarization by the MAI, with a correlation coefficient of 0.9576, an average absolute deviation of 6.06%, and a standard deviation of the difference between the retrieved degree of polarization and the measured degree of polarization of 1.29%. The method of on-orbit polarization calibration based on sunglint over the ocean can realize on-orbit polarization monitoring and calibration of the MAI.
The Multi-angle Polarization Imager (MAI) is the first multi-angle polarization imaging instrument operating in orbit in China. It is important to the development of the polarized remote sensing technology. This study uses onorbit polarization calibration of the MAI based on sunglint over the ocean to determine the accuracy of the MAI data and to lay the foundations for the study of clouds and aerosols using this instrument. The retrieved degree of polarization at the top of atmosphere (TOA) is in good agreement with the degree of polarization simulated by the Second Simulation of a Satellite Signal in the Solar Spectrum -Vector (6SV) radiation transfer mode with a correlation coefficient of 0.992 and a method uncertainty of <1%. The calibration pixels are selected by combining the theoretical analysis and 6SV simulation, and the MAI on-orbit polarization calibration test is carried out using the selected pixels. There is good agreement between the retrieved degree of polarization at the TOA and the measured degree of polarization by the MAI, with a correlation coefficient of 0.9576, an average absolute deviation of 6.06%, and a standard deviation of the difference between the retrieved degree of polarization and the measured degree of polarization of 1.29%. The method of on-orbit polarization calibration based on sunglint over the ocean can realize on-orbit polarization monitoring and calibration of the MAI.
Cross-calibration methods are widely used in high-precision remote sensor calibrations and ensure observational consistency between sensors. Because two sensors must be observed under the same or similar conditions, the cross-calibration frequency is greatly reduced; performing cross-calibrations on Aqua/Terra MODIS, Sentinel-2A/Sentinel-2B MSI and other similar sensors is difficult due to synchronous-observation limitations. Additionally, few studies have cross-calibrated water-vapor-observation bands sensitive to atmospheric changes. In recent years, standard automated observation sites and unified processing technology networks, such as an Automated Radiative Calibration Network (RadCalNet) and an automated vicarious calibration system (AVCS), have provided automatic observation data and means for independently, continuously monitoring sensors, thus offering new cross-calibration references and bridges. We propose an AVCS-based cross-calibration method. By limiting the observational-condition differences when two remote sensors transit over wide temporal ranges through AVCS observation data, we improve the cross-calibration opportunity. Thereby, cross-calibrations and observation consistency evaluations between the abovementioned instruments are realized. The influence of AVCS-measurement uncertainties on the cross-calibration is analyzed. The consistency between the MODIS cross-calibration and sensor observation is within 3% (5% in SWIR bands); that for the MSI is within 1% (2.2% in the water-vapor-observation band); and for the cross-calibration of Aqua MODIS and the two MSI, the consistency between the cross-calibration-predicted TOA reflectance and the sensor-measured TOA reflectance was within 3.8%. Thus, the absolute AVCS-measurement uncertainty is also reduced, especially in the water-vapor-observation band. This method can be applied to cross-calibrations and measurement consistency evaluations of other remote sensors. Later, the spectral-difference influences on cross-calibrations will be further studied.
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