在卫星遥感研究中, 云检测是基础环节, 其结果影响大气、地表各种参数的定量遥感, 同时也影响云微物理特性的反演。本研究针对多角度偏振卫星载荷 (高分五号 DPC 传感器), 建立了一种改进的光谱特征云检测算法。该算法综合利用云像元和非云像元在可见光反射率光谱、氧 A 波段吸收、蓝光偏振反射率以及偏振虹等特性上的差异, 分别提出了陆地、海洋上空的云检测方案, 并进一步建立了多角度云检测融合策略以标记云、晴空和未定像元。在陆地检测中, 通过增加表观压强检测和偏振虹检测分别改进了高层薄云和低层薄云的识别; 在海洋检测中, 利用表观压强与云层的退偏特性改进了耀光区云像元的识别。全球云检测结果示例显示该算法整体检测效果较好, 同时典型区域的检测结果与 MODIS 云产品也具有较好的一致性。该研究可为高分五号 02 星上的多角度偏振传感器云检测提供方法基础。

Cloud detection is a crucial process of satellite remote sensing because of its significant impacts on the monitoring and quantitative retrieval of various atmospheric and surface parameters, and its accuracy also affects the retrieval of cloud microphysical properties. In this study, an improved cloud detection algorithm based on spectral information is established for the directional polarimetric camera (DPC) onboard Gaofen-5 satellite. Based on thedifferences between cloud pixels and clear pixels in the visible spectrum, the absorption characteristics of oxygen A-band, the polarized reflectance of blue band, and the polarized rainbow feature, the algorithm establishes a comprehensive cloud detection method over land and ocean area, and further proposes a multi-angle fusion strategy for the final determination of cloud detection. The recognition of high thin clouds and low thin clouds is improved by adding apparent pressure detection and polarization rainbow detection over land, respectively, and in other hand, the combination of apparent pressure and degree of linear polarization is used to improve the detection of cloud pixels in the sun-glint area over ocean. Examples of global cloud detection results of DPC have shown the effectiveness of this method, and the results of typical areas have also shown good consistency with MODIS cloud products. This research can be expected to provide a methodological basis for the cloud detection on the multi-angle and polarimetric sensor onboard the recently launched Gaofen-5(02) satellite.