Estimation and analysis of the green-tide drift velocity using ship-borne UAV

Jiang Xiaopeng; Gao Zhiqiang; Wu Xiaoqing; Wang Yueqi; Ning Jicai

doi:10.12284/hyxb2021054

Volume 43 Issue 4

Apr. 2021

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Jiang Xiaopeng，Gao Zhiqiang，Wu Xiaoqing, et al. Estimation and analysis of the green-tide drift velocity using ship-borne UAV[J]. Haiyang Xuebao，2021, 43(4)：96–105 doi: 10.12284/hyxb2021054

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Jiang Xiaopeng，Gao Zhiqiang，Wu Xiaoqing, et al. Estimation and analysis of the green-tide drift velocity using ship-borne UAV[J]. Haiyang Xuebao，2021, 43(4)：96–105 doi: 10.12284/hyxb2021054

Citation:

Jiang Xiaopeng，Gao Zhiqiang，Wu Xiaoqing, et al. Estimation and analysis of the green-tide drift velocity using ship-borne UAV[J]. Haiyang Xuebao，2021, 43(4)：96–105 doi: 10.12284/hyxb2021054

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Estimation and analysis of the green-tide drift velocity using ship-borne UAV

doi: 10.12284/hyxb2021054

Jiang Xiaopeng^{1, 2, 3
,},
Gao Zhiqiang^{1, 3
,
,},
Wu Xiaoqing^{1, 3},
Wang Yueqi^{1, 3},
Ning Jicai^{1, 3}

1.
Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Chinese Academy of Sciences, Yantai 264003, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
Shandong Key Laboratory of Coastal Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China

Received Date: 2020-07-27
Rev Recd Date: 2020-12-08

Available Online: 2021-03-24

Publish Date: 2021-04-01

Abstract

Abstract

Unmanned aerial vehicle (UAV) remote sensing has distinct advantages of flexible use, no cloud interference, and high spatial-temporal resolution. Aim to explore UAV’s utilization potential in marine disaster monitoring, research ship was used as the UAV landing pad, and for the first time, based on the bi-temporal orthophotos acquired by the ship-borne UAV, the drift velocity of green-tide in the Yellow Sea was estimated. In addition, the velocity result extracted from satellite images was compared, and the influences of wind and tidal currents on green-tide drift were analyzed. The results show that: (1) the red-green-blue floating algae index (RGB-FAI) can extract green-tide patches from UAV-based RGB orthophotos with a high-accuracy (kappa coefficient=0.95); (2) the green-tidal speed of three sites estimated by UAV remote sensing are 0.26−0.44 m/s, and the drift direction changed significantly throughout the day; (3) the short-term drift of green-tide is forced by the wind and tidal current. The drift direction of the green-tide is basically consistent with the tidal current of M₂, at 1°−62° to the right of wind direction. The ability to estimate green-tidal velocity accurately from the ship-borne UAV images is expected to provide technical support for the precise prediction, warning and control of green-tide disaster.
- UAV remote sensing,
- Yellow Sea,
- green tides,
- drift velocity,
- RGB-FAI

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References(29)

References

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