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Proceedings Paper

Multi-resource data-based research on remote sensing monitoring over the green tide in the Yellow Sea
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Paper Abstract

This paper conducted dynamic monitoring over the green tide (large green alga—Ulva prolifera) occurred in the Yellow Sea in 2014 to 2016 by the use of multi-source remote sensing data, including GF-1 WFV, HJ-1A/1B CCD, CBERS-04 WFI, Landsat-7 ETM+ and Landsta-8 OLI, and by the combination of VB-FAH (index of Virtual-Baseline Floating macroAlgae Height) with manual assisted interpretation based on remote sensing and geographic information system technologies. The result shows that unmanned aerial vehicle (UAV) and shipborne platform could accurately monitor the distribution of Ulva prolifera in small spaces, and therefore provide validation data for the result of remote sensing monitoring over Ulva prolifera. The result of this research can provide effective information support for the prevention and control of Ulva prolifera.

Paper Details

Date Published: 1 September 2017
PDF: 5 pages
Proc. SPIE 10405, Remote Sensing and Modeling of Ecosystems for Sustainability XIV, 104050N (1 September 2017); doi: 10.1117/12.2271732
Show Author Affiliations
Zhiqiang Gao, Yantai Institute of Coastal Zone Research (China)
Fuxiang Xu, Yantai Institute of Coastal Zone Research (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Debin Song, Yantai Institute of Coastal Zone Research (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Xiangyu Zheng, Yantai Institute of Coastal Zone Research (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Maosi Chen, USDA UV-B Monitoring and Research Program (United States)


Published in SPIE Proceedings Vol. 10405:
Remote Sensing and Modeling of Ecosystems for Sustainability XIV
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

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