Remote Sensing of Ulva Prolifera Green Tide in the Yellow Sea Using Multisource Satellite Data: Progress and prospects
文献类型：期刊论文
| 作者 | Pan, Xinliang13,14,15; Cao, Mengmeng16; Zheng, Longxiao13,14,15; Xiao, Yanfang17; Qi, Lin1; Xing, Qianguo2 ; Kim, Keunyong3; Sun, Deyong4; Wang, Ning5; Guo, Maohua7
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| 刊名 | IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
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| 出版日期 | 2024-08-28 |
| 页码 | 22 |
| 关键词 | Remote sensing Monitoring Green products Optical sensors Tides Synthetic aperture radar Satellites |
| ISSN号 | 2473-2397 |
| DOI | 10.1109/MGRS.2024.3364678 |
| 通讯作者 | Cui, Tingwei(cuitw@mail.sysu.edu.cn) |
| 英文摘要 | As a marine ecological disaster caused by the explosive proliferation of green macroalgae, green tides impair economic development and the ecological environment, affecting dozens of regions worldwide. The largest green tide in the world occurs in the Yellow Sea, with Ulva prolifera (U. prolifera) the dominant species. Satellite remote sensing technology, with its advantages of a large scale, a long time series, and traceability, plays a significant role in U. prolifera monitoring, providing important support for obtaining deeper scientific understanding and promoting disaster prevention and control. To systematically and comprehensively summarize research progress and identify weaknesses and priorities for future development, this article reviews over 350 articles on U. prolifera green tide remote sensing in the Yellow Sea, published before November 2023 from three aspects: remote sensing mechanisms (electromagnetic scattering and remote sensing image features), methods (detection, coverage area retrieval, species discrimination, biomass estimation, drift velocity determination, and so on), and applications (growth and decay, interannual variabilities, and so forth). Additionally, challenges, opportunities, and development priorities are analyzed (see "Article Contents"). The findings in this article promote the future development of U. prolifera remote sensing technology to assist with disaster prevention and ecosystem protection. |
| WOS关键词 | LARGEST MACROALGAL BLOOM ; SEAWEED AQUACULTURE ; CHINA ; ALGAE ; BIOMASS ; EXTRACTION ; COVERAGE ; IMAGER ; THRESHOLD ; EXPANSION |
| WOS研究方向 | Geochemistry & Geophysics ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001303384800001 |
| 资助机构 | Southern Marine Science and Engineering Guangdong Laboratory (Zhu-hai) ; National Key Research and Development Program of China ; Fundamental Research Funds for the Central Universities ; Sun Yat-sen University ; China-Korea Joint OceanSun Research Center, China |
| 源URL | [http://ir.yic.ac.cn/handle/133337/35812]  |
| 专题 | 烟台海岸带研究所_中科院海岸带环境过程与生态修复重点实验室 烟台海岸带研究所_海岸带信息集成与综合管理实验室 |
| 通讯作者 | Cui, Tingwei |
| 作者单位 | 1.NOAA, Ctr Satellite Applicat & Res, College Pk, MD 20740 USA 2.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China 3.Korea Inst Ocean Sci & Technol, Korea Ocean Satellite Ctr, Busan 49111, South Korea 4.Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Nanjing 210044, Peoples R China 5.Minist Nat Resources, North China Sea Marine Forecasting Ctr, Qingdao 266061, Peoples R China 6.Ludong Univ, Coll Resources & Environm Engn, Yantai 264025, Peoples R China 7.Minist Nat Resources, Natl Satellite Ocean Applicat Serv, Beijing 100081, Peoples R China 8.Qingdao Ecol & Environm Monitoring Ctr Shandong Pr, Qingdao 266003, Peoples R China 9.China Univ Petr East China, Coll Oceanog & Space Informat, Qingdao 266580, Peoples R China 10.Wuhan Univ, Sch Remote Sensing Informat Engn, Wuhan 430079, Peoples R China |
| 推荐引用方式 GB/T 7714 | Pan, Xinliang,Cao, Mengmeng,Zheng, Longxiao,et al. Remote Sensing of Ulva Prolifera Green Tide in the Yellow Sea Using Multisource Satellite Data: Progress and prospects[J]. IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE,2024:22. |
| APA | Pan, Xinliang.,Cao, Mengmeng.,Zheng, Longxiao.,Xiao, Yanfang.,Qi, Lin.,...&Cui, Tingwei.(2024).Remote Sensing of Ulva Prolifera Green Tide in the Yellow Sea Using Multisource Satellite Data: Progress and prospects.IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE,22. |
| MLA | Pan, Xinliang,et al."Remote Sensing of Ulva Prolifera Green Tide in the Yellow Sea Using Multisource Satellite Data: Progress and prospects".IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE (2024):22. |
入库方式： OAI收割
来源：烟台海岸带研究所
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