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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing. >Performance of COCTS in Global Ocean Color Remote Sensing
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Performance of COCTS in Global Ocean Color Remote Sensing

机译：COCTS在全球海洋颜色遥感中的表现

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摘要

Ocean color satellite sensors have become an indispensable component in the Earth Observing System, in which the use of multiple ocean color satellite sensors not only improves the spatiotemporal coverage of the global oceans but also maintains the continuity of the data products for long-term monitoring. In this research, the performance of a new ocean color satellite sensor Chinese Ocean Color and Temperature Scanner (COCTS) from HY1C launched in September 2018 is thoroughly evaluated with two important aspects: the signal-to-noise ratio (SNR) at the top of the atmosphere and the uncertainty in the remote-sensing reflectance ${R} _{mathrm {rs}}$ ) products. The results showed that the SNR of the COCTS can satisfy the requirements of the ocean color applications, and the uncertainty in the ${R} _{mathrm {rs}}$ at the blue bands in the ocean waters meets the demand of less than 5%. A further comparison with other well-known ocean color sensors indicates that not only the COCTS can provide reliable ocean color data but also the processing system is robust and reliable. These results provide a solid base for merging the COCTS products with other ocean color sensors for the studies of ocean biogeochemistry.
机译：Ocean Color卫星传感器已成为地球观测系统中不可或缺的组成部分，其中使用多个海洋卫星传感器的使用不仅可以提高全球海洋的时空覆盖率，而且还保持了长期监测的数据产品的连续性。在本研究中，2018年9月推出的新海洋卫星传感器中华海洋和温度扫描仪（COCTS）的性能得到了两种重要方面的综合评估：顶部的信噪比（SNR）遥感反射的气氛和不确定性<内联公式XMLNS：MML =“http://www.w3.org/1998/math/mathml”xmlns：xlink =“http://www.w3.org / 1999 / xlink“> $ {R} _ {r} _ { mathrm {rs}} $ ）产品。结果表明，COCTS的SNR可以满足海洋颜色应用的要求，以及<内联公式XMLNS：MML =“http://www.w3.org/1998/math/mathml”xmlns的不确定性：xlink =“http://www.w3.org/1999/xlink”> $ {r} _ {r} _ { mathrm {rs}} $ 海水中的蓝乐队符合小于5％的需求。与其他众所周知的海洋颜色传感器的进一步比较表明，不仅COCTS可以提供​​可靠的海洋颜色数据，而且处理系统也是坚固且可靠的。这些结果提供了一种用于将COCTS产品与其他海洋颜色传感器合并的固体碱，用于海洋生物地球化学研究。

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  • 作者

    Shuguo Chen; Keping Du; Zhongping Lee; Jianqiang Liu; Qingjun Song; Cheng Xue; Daosheng Wang; Mingsen Lin; Junwu Tang; Chaofei Ma;

  • 作者单位

    Ocean University of China Qingdao China;

    Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities Faculty of Geographical Science Beijing Normal University Beijing China;

    School for the Environment University of Massachusetts Boston Boston MA USA;

    National Satellite Ocean Application Service Ministry of Natural Resources of the People’s Republic of China Beijing China;

    National Satellite Ocean Application Service Ministry of Natural Resources of the People’s Republic of China Beijing China;

    Ocean University of China Qingdao China;

    College of Ocean and Earth Sciences Xiamen University Xiamen China;

    National Satellite Ocean Application Service Ministry of Natural Resources of the People’s Republic of China Beijing China;

    Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and Technology (Qingdao) Qingdao China;

    National Satellite Ocean Application Service Ministry of Natural Resources of the People’s Republic of China Beijing China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Oceans; Image color analysis; Signal to noise ratio; Temperature sensors; Uncertainty; Oceanography;

    机译：海洋;图像颜色分析;信噪比;温度传感器;不确定性;海洋学;

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