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Summary of sharing platforms for ocean color remote sensing in situ measurement data
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Qiang Li1, 2, 3, Junwu Tang2, 4, 5, Huaxin Ge6, Guojun Wu2, 4, Lingling Jiang7, Xiaopeng Shao2, *
Haiyang Xuebao | 2025, 47(2) : 108 - 130
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Haiyang Xuebao | 2025, 47(2): 108-130
Summary of sharing platforms for ocean color remote sensing in situ measurement data
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Qiang Li1, 2, 3, Junwu Tang2, 4, 5, Huaxin Ge6, Guojun Wu2, 4, Lingling Jiang7, Xiaopeng Shao2, *
Affiliations
  • 1School of Optoelectronic Engineering, Xidian University, Xi’an 710071, China
  • 2Xi’an Institute of Optics and Precision Mechanics of Chinese Academy of Science, Xi’an 710119, China
  • 3University of Chinese Academy of Science, Beijing 100049, China
  • 4Laoshan Laboratory, Qingdao 266237, China
  • 5College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
  • 6Gosci Technology Group, Qingdao 266237, China
  • 7College of Environment Science and Engineering, Dalian Maritime University, Dalian 116026, China
Published: 2025-02-28 doi: 10.12284/hyxb2025005
Outline
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High-quality in situ measurement data is a prerequisite for the validation of ocean color remote sensing data products, algorithm development, and climate change research. The collection of in situ measurement data, however, typically requires a substantial investment of human, material and financial resources. The data collected by a single research team often insufficient to support long-term and large-scale research. Driven by the advances in scientific research of “big data”, several open-access data platforms, intergovernmental and national marine scientific data centers, as well as database platforms of major marine-related departments, have released diverse types of in-situ measurement data and shared them with users. This is aimed at giving full play to the value of in-situ measurement data and supporting the research on major scientific issues. It is difficult for data users to quickly understand and apply shared data from these platforms, because of the discrete distribution of datasets on different platforms, and differences in data collection time, regions, disciplinary categories, and acquisition methods. This results in a time-consuming and labor-intensive process of gathering relevant research data. Therefore, this paper compiles and organizes 29 database platforms from which parameters such as ocean optics, biogeochemistry can be obtained. These platforms store in-situ measurement data from the global ocean over the past century. This paper reviews the typical applications of these shared data in the research of ocean color remote sensing, and provides suggestions for data retrieval of commonly used parameters, with the aim of helping data users obtain research data quickly.

ocean color  /  ocean optics  /  bio-optics  /  in situ measurements  /  database  /  shared data  /  biogeochemistry
Qiang Li, Junwu Tang, Huaxin Ge, Guojun Wu, Lingling Jiang, Xiaopeng Shao. Summary of sharing platforms for ocean color remote sensing in situ measurement data[J]. Haiyang Xuebao, 2025 , 47 (2) : 108 -130 . DOI: 10.12284/hyxb2025005
Year 2025 volume 47 Issue 2
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Article Info
doi: 10.12284/hyxb2025005
  • Receive Date:2024-07-11
  • Online Date:2025-10-27
  • Published:2025-02-28
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  • Received:2024-07-11
  • Revised:2024-12-10
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Affiliations
    1School of Optoelectronic Engineering, Xidian University, Xi’an 710071, China
    2Xi’an Institute of Optics and Precision Mechanics of Chinese Academy of Science, Xi’an 710119, China
    3University of Chinese Academy of Science, Beijing 100049, China
    4Laoshan Laboratory, Qingdao 266237, China
    5College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
    6Gosci Technology Group, Qingdao 266237, China
    7College of Environment Science and Engineering, Dalian Maritime University, Dalian 116026, China
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表12种不同金属材料的力学参数

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多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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