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Development of an all-sky imaging system for cloud cover assessment

机译:开发云覆盖评估的全天成像系统

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摘要

This study develops a novel automatic all-sky imaging system, namely, an all-sky camera (ASC) system, for cloud cover assessment. The proposed system does not require conventional solar occulting devices and can capture complete hemispheric sky images. Cloud detection is performed innovatively using a convolutional neural network model (i.e., the optimized U-Net model). Experiments demonstrate that the optimized U-Net model can effectively detect clouds from sky images. In terms of cloud cover, the estimation results of the ASC system exhibit a high correlation with those obtained via manual observation, thereby indicating the applicability of the ASC system in ground-based cloud observation and analysis. (C) 2019 Optical Society of America
机译:本研究开发了一种新型的自动全天成像系统,即全天候相机(ASC)系统,用于云覆盖评估。 所提出的系统不需要常规的太阳掩埋装置,可以捕获完整的半球天空图像。 使用卷积神经网络模型(即,优化的U-Net模型)进行创新地执行云检测。 实验表明优化的U-Net模型可以有效地从天空图像中检测云。 在云覆盖方面,ASC系统的估计结果与通过手动观察获得的那些表现出高的相关性,从而指示ASC系统在基于地面云观察和分析中的适用性。 (c)2019年光学学会

著录项

  • 来源
    《Applied optics》 |2019年第20期|共9页
  • 作者单位

    Nanjing Univ Informat Sci &

    Technol Nanjing 210044 Jiangsu Peoples R China;

    Chinese Acad Sci Anhui Inst Opt &

    Fine Mech Key Lab Atmospher Opt Hefei 230088 Anhui Peoples R China;

    Chinese Acad Sci Inst Appl Technol Hefei 230031 Anhui Peoples R China;

    Chinese Acad Sci Inst Appl Technol Hefei 230031 Anhui Peoples R China;

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  • 正文语种 eng
  • 中图分类 应用;
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