• Acta Optica Sinica
  • Vol. 40, Issue 11, 1101002 (2020)
Yuyang Chang1、2, Bin Sun1、*, Chan Huang1、2, Jin Hong1, and Yanli Qiao1
Author Affiliations
  • 1Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, Anhui 230031, China
  • 2University of Science and Technology of China, Hefei, Anhui 230026, China
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    DOI: 10.3788/AOS202040.1101002 Cite this Article Set citation alerts
    Yuyang Chang, Bin Sun, Chan Huang, Jin Hong, Yanli Qiao. Cloud Detection and Parameter Inversion Using Multi-Directional Polarimetric Observations[J]. Acta Optica Sinica, 2020, 40(11): 1101002 Copy Citation Text show less

    Abstract

    The directional polarimetric camera (DPC) aboard the GF-5 satellite is the first domestic space-born instrument with operational multi-spectral, multi-directional, and polarimetric observations. A series of algorithms used for DPC measurements were formulated to acquire cloud detection results, cloud thermodynamic phase distribution, and cloud optical thickness of the observed zones. The cloud detection results were derived from the reflectance at 670 and 865 nm, the geometric normalized polarized radiance was obtained at 490 nm, and the linear degree of polarization was obtained at 865 nm. The cloud thermodynamic phase was derived from the normalized polarized radiance at 865 nm; the cloud optical thickness was obtained from the reflectance at 670 and 865 nm and results of cloud thermodynamic phase. Because of the lack of L1 data of DPC, the algorithms were applied to POLDER data to validate their feasibility. Results indicated that the consistency of “cloudy judgment” and “clear judgment” was 93.3% and 92.9%, respectively. Further, the consistency of “water clouds,” “ice clouds,” and “mixed-phase clouds” was 87.4%, 76.6% and 22.8%, respectively. The correlation coefficient of the optical thickness was 0.89, which demonstrates the feasibility of the proposed algorithms. The proposed algorithms can develop the operational cloud production of DPC.
    Yuyang Chang, Bin Sun, Chan Huang, Jin Hong, Yanli Qiao. Cloud Detection and Parameter Inversion Using Multi-Directional Polarimetric Observations[J]. Acta Optica Sinica, 2020, 40(11): 1101002
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