Analysis of surface and aerosol polarized reflectance for aerosol retrievals from polarized remote sensing in PRD urban region

Abstract A precise estimate of polarization induced by surface is crucial for polarized remote sensing dedicated to monitoring aerosol properties over urban area. The accurate knowledge of interaction between surface and aerosol polarized reflectance is essential for accurately achieving aerosol properties. In order to study surface and aerosol polarized reflectance for aerosol retrievals over urban area, a new airborne directional polarimetric camera (DPC) with high spatial resolution (4 m at 4000 m a.g.l) was developed. The surface polarized reflectance over distinct surface covers of urban area (forest, shrub, and soil) were studied using DPC measurements during a field campaign in the Pearl River Delta (PRD), China. The large variations were found in surface polarized reflectance of distinct urban covers due to surface type variability. For all surface types, the empirical BPDF model cannot describe accurately surface polarized reflectance at all possible illumination and observation geometries. From the quantitatively study of relationship between surface and aerosol polarized contribution to DPC measurements, we show that the polarized contributions of aerosol, which optical properties were defined by ground-based measurements, are much larger than the polarized contribution of surface, and found that the polarized contribution of surface covers increases with decreasing NDVI. The effect of polarization accuracy of measurements on aerosol retrieval was also investigated using DPC measurements, and found that 0.1% polarization accuracy of measurements can be neglected when AOD is retrieved using polarized measurements. Based on the information of effects of polarized reflectance differences between distinct surface covers and polarization accuracy of polarized measurements on retrieved aerosols over urban area, we found that the accuracy of aerosol retrieval over forest covers is higher than other surface types using polarized remote sensing.

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