The Directional Polarimetric Camera (DPC) is the first Chinese multi-angle polarized Earth observation satellite sensor, which was successfully launched on 9 May 2018, onboard the GaoFen-5 satellite in the Chinese High-Resolution Earth Observation Program. The DPC’s observation is one of the most important space-borne multi-spectral, multi-angular polarimetric measurements of the global Earth-atmosphere system at the present stage. Although rigorous radiometric calibration had been performed for the DPC before launch, its in-flight performance may change because of the process of launch, harsh environment of space, and aging of the sensor. Due to the absence of the onboard calibration system, vicarious calibration methods are necessary for the DPC’s in-flight performance monitoring and calibration. In this paper, we adapted the Rayleigh absolute calibration method, the sun glint inter-band calibration method, and the sun glint polarization calibration method to the DPC sensor. First, the calibration errors of these three methods caused by ancillary data uncertainties (e.g.,  aerosol, chlorophyll concentration, absorption gases amount, and wind speed) were analyzed in detail. The error budgets show that the aerosol parameters (optical thickness and aerosol model) are some of the critical factors affecting both the radiometric and polarimetric calibration accuracies for the Rayleigh and sun glint methods. The DPC radiometric and polarimetric in-flight calibration during its commissioning phase was then implemented. The absolute coefficients of short spectral bands (443, 490, 565, and 670 nm) were calibrated by the well-characterized Rayleigh scattering signal over the ocean. Using the 565 nm band as a reference band, the Rayleigh absolute calibration was then transferred to other bands (443, 490, 670, and 865 nm) through inter-band calibration using the specular reflection of the sun over the ocean. The polarization measurements of the DPC at polarized bands (490, 670, and 865 nm) were calibrated with the polarized reflection of the sun glint over ocean. The preliminary results show that the radiometric sensitivity of the DPC changed very little after launch at the four visible bands. The absolute calibration coefficient differences from pre-flight calibration are smaller than 0.5% at the 443 and 670 nm bands, while they are within ± 2 % at the 490 and 565 nm bands. However, a large deviation at 865 nm band of about 9% from pre-flight calibration was indicated by the sun glint inter-band calibration. The degree of linear polarization measurement of the DPC is validated with high accuracy of about 0.02 at the 865 nm band, while the deviation at 490 and 670 nm bands are relatively larger, reaching 0.04. The DPC/GaoFen-5 shows a good in-flight performance of radiometric measurement and generally reliable polarimetric measurement after launch.

The DPC is a multiangle sensor that detects atmospheric parameters. However, the retrieval of high-precision and high-spatial-resolution aerosol products from the DPC remains a great challenge due to the ill-posed nature of the problem. Thus, a novel aerosol optical depth (AOD) retrieval algorithm was proposed using visible surface reflectance relationships (VISRRs). The VISRR algorithm accounts for the surface anisotropy and needs neither a shortwave infrared band nor a surface reflectance database that can retrieve AOD over dark and bright land cover. Firstly, moderate-resolution imaging spectroradiometer (MODIS) surface reflectance (MYD09) products were used to derive the preceding surface reflectance relationships (SRRs), which are related to surface types, scattering angle, and normalized difference vegetation index (NDVI). Furthermore, to solve the problem of the NDVI being susceptible to the atmosphere, an innovative method based on an iterative atmospheric correction was proposed to provide a realistic NDVI. The VISRR algorithm was then applied to the thirteen months of DPC multiangle data over the China region. AOD product comparison between the DPC and MODIS showed that they had similar spatial distribution, but the DPC had both high spatial resolution and coverage. The validation between the ground-based sites and the retrieval results showed that the DPC AOD performed best, with a Pearson correlation coefficient (R) of 0.88, a root mean square error (RMSE) of 0.17, and a good fraction (Gfrac) of 62.7%. Then, the uncertainties regarding the AOD products were discussed for future improvements. Our results revealed that the VISRR algorithm is an effective method for retrieving reliable, simultaneously high-spatial-resolution and full-surface-coverage AOD data with good accuracy.