Identification and assessment of the drift velocity of green tides using the maximum cross-correlation method in the Yellow Sea

被引：5
|
作者：
Ji, Menghao [1 ]
Zhao, Chengyi [1 ,3 ]
Dou, Xin [1 ]
Wang, Can [1 ]
Zhou, Dian [1 ]
Zhu, Jianting [2 ]
机构：
[1] Nanjing Univ Informat Sci & Technol, Sch Geog Sci, Nanjing 210044, Peoples R China
[2] Univ Wyoming, Dept Civil & Architectural Engn, Laramie, WY 82071 USA
[3] Nanjing Univ Informat Sci & Technol, Sch Geog Sci, 219 Ningliu Rd, Nanjing 210044, Peoples R China
来源：
MARINE POLLUTION BULLETIN | 2023年 / 194卷
关键词：
Green tides; Drift velocity; Maximum cross-correlation method (MCC); Windage; SEAWEED AQUACULTURE; BLOOM; OCEAN; TRAJECTORIES; MACROALGAE; EXPANSION; ALGAE; MODEL;
D O I：
10.1016/j.marpolbul.2023.115420
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
The green tides outbreak events seriously threaten the ecological balance of the coastal areas. Quickly and accurately obtaining the spatial distribution and drift state of green tides is key to early warning. Based on Landsat 8 (L8) and Sentinel-2 (S2) image pair, the green tides drift velocity was extracted using the maximum cross-correlation (MCC) method, and windage was calculated by combining ocean current and wind data. The results of the MCC method were validated. Ulva's drift in the Yellow Sea is shaped by both ocean currents and wind, closely aligning with the direction of the currents. Notably, the northward drift velocity of Ulva exhibits a clear boundary around 34 degrees 40 & PRIME;N. Windage shows similar characteristics with the Ulva drift velocity, as its values vary with time and space. This study will enhance our comprehension of the dynamic mechanism of green tides drift.
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页数：14
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