Based on the optimal estimation (OE) theory, an inversion framework for aerosol retrieval from multiviewing polarimetric satellite measurements, is presented. The retrieved parameters include the wavelength-independent volume concentration and spectral aerosol optical depth (AOD). An OE-iteration approach is proposed to implement the framework. Polarization data from the polarization and directionality of the Earth’s reflectance sensor over the Chinese Beijing–Tianjin–Hebei region are selected to test the proposed algorithm. The validation against aerosol robotic network products produces high correlation coefficients (R) of 0.85, 0.9, and 0.86 for the fine-mode volume concentration, fine-mode AOD, and total AOD at 500 nm, respectively. These results indicate that the OE retrieval framework is practical and useful in the quantitative retrieval of AOD and fine-mode volume concentration from the multiangle polarization data.
Environment-2 (HJ-2) satellites will be launched after 2019, which are designed as the successor of Environment-1 (HJ- 1) satellites in Chinese Environment and Disaster Monitoring and Prediction Satellite Constellation. Different from HJ-1 satellites, a new multispectral single-viewing polarimetric instrument called Polarized Scanning Atmospheric Corrector (PSAC) will be onboard on HJ-2 satellites, and further provide the aerosol properties for synchronous atmospheric correction of the main sensors, such as the multispectral charge-coupled device (CCD) cameras onboard the same satellite. In this way, the multispectral surface reflectance could be further obtained from the remote sensing measurements of CCD cameras by the atmospheric correction with the retrieved aerosol properties from PSAC. In this paper, based on the optimal estimation (OE) theory and information content analysis method, we have a preliminary study on the propagation errors from the retrieved aerosol properties to multispectral surface reflectance in the process of synchronous atmospheric correction. The priori information and errors for the analysis are assumed based on the measurement noise of CCD cameras and a priori error of retrieved aerosol optical depth (AOD), as well as typical multispectral reflectance from USGS and ASTER spectral library. For the simulation of synthetic measurements of CCD cameras, Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) has been used as the forward model. By this means, the posterior errors of multispectral surface reflectance are calculated, and the errors propagations can be evaluated theoretically, which can further provide key support for the study of synchronous atmospheric correction in HJ-2 satellites.
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