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

Zhiqiang Gao; Fuxiang Xu; Debin Song; Xiangyu Zheng; Maosi Chen

doi:10.1117/12.2271732

1 September 2017 Multi-resource data-based research on remote sensing monitoring over the green tide in the Yellow Sea

Zhiqiang Gao, Fuxiang Xu, Debin Song, Xiangyu Zheng, Maosi Chen

Proceedings Volume 10405, Remote Sensing and Modeling of Ecosystems for Sustainability XIV; 104050N (2017) https://doi.org/10.1117/12.2271732
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

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.

Citation Download Citation

Zhiqiang Gao, Fuxiang Xu, Debin Song, Xiangyu Zheng, and Maosi Chen "Multi-resource data-based research on remote sensing monitoring over the green tide in the Yellow Sea", Proc. SPIE 10405, Remote Sensing and Modeling of Ecosystems for Sustainability XIV, 104050N (1 September 2017); https://doi.org/10.1117/12.2271732

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