Retrieving the Optical Properties of Aerosols Over Land With Directional Polarimetric Camera Observations and an Adaptive Algorithm

Autor: Meiru Zhao, Xiaobing Sun, Han Wang, Leiku Yang
Rok vydání: 2022
Předmět:
Zdroj: IEEE Geoscience and Remote Sensing Letters. 19:1-5
ISSN: 1558-0571
1545-598X
DOI: 10.1109/lgrs.2021.3049806
Popis: The Directional Polarimetric Camera (DPC) is a polarization sensor mounted on Chinese Gaofen-5 satellite. It has the capability of observing multispectral, multiangular, and polarized light, and can be used to monitor global aerosols and clouds. This work developed an adaptive algorithm to retrieve aerosol properties based on DPC measurements. It performs initial surface property estimations, aerosol parameter retrievals, surface parameter adjustments, and result assessments. In the algorithm, it allows global aerosol optical depths (AODs) and Angstrom exponents (AEs) to be retrieved. The AOD values show good consistency with that from AErosol RObotic NETwork (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS). The regression line between AODs from DPC and AERONET is y = 0.895x + 0.056, with a correlation coefficient of 0.894, and 49% of the DPC-retrieved AODs are within the expected error range of ±(15%AOD + 0.05). For the AEs, the regression line is y = 0.728x + 0.395, the correlation coefficient is 0.763, and 41.4% of the AEs are within the error range of (AE ± 0.4). We also investigated the possible influence of AOD errors retrieved from the DPC measurements over three typical areas. It was found that though the DPC-retrieved dust aerosols did not show so good consistency with the MODIS measurements as the smoke aerosols, the retrievals still matched well on the whole. It demonstrates the potential of DPC and the adaptive algorithm for aerosol remote sensing.
Databáze: OpenAIRE