基于HY-1C/D卫星数据的2021年黄海海域大型藻类时空分布特征分析-海洋预报

基于HY-1C/D卫星数据的2021年黄海海域大型藻类时空分布特征分析

单位：1. 自然资源部北海预报减灾中心山东青岛 266100;
2. 山东省海洋生态环境与防灾减灾重点实验室, 山东青岛 266061

分类号：X55

出版年·卷·期（页码）：2023·40·第五期（90-97）

摘要：

基于HY-1C/D（CZI）卫星遥感影像数据，利用归一化植被指数阈值判别方法提取大型藻类（浒苔绿潮）的分布和覆盖信息；结合实地考察，分析大型藻类的藻类构成与光谱信息特征；获取大型藻类灾害暴发时间、空间分布、密集度、漂移路径并对其分析。结果表明：2021年黄海海域大型藻类灾害最早发生于5月上旬，5月中旬—6月上旬进入发展期，6月中旬—7月上旬进入暴发期，7月中旬—8月下旬进入消亡期。从大型藻类的持续时间、时空分布、密集度变化等指标看，2021年黄海大型藻类分布面积和覆盖面积较大，发生时间较长，结束时间较晚。

Based on HY-1C / D (CZI) satellite remote sensing data, normalized vegetation index threshold iscrimination method is used to extract the distribution and coverage information of macroalgae（Enteromorpha prolifera）. The composition and spectral information characteristics of macroalgae are analyzed combined with field investigation. The occurrence time, spatial distribution, density and drift path of large algae disaster are obtained and analyzed. The results show that large-scale algae disaster in the Yellow Sea area in 2021 occurs in early May, develops between middle May and early June, blooms between middle June and early July, and perishes between middle July and late August. According to the duration, spatial and temporal distribution, and concentration changes of macroalgae, the distribution and coverage areas of macroalgae in the Yellow Sea in 2021 are relatively larger, the occurrence time is relatively longer, and the end time is relatively later.

参考文献：

[1] 叶娜, 贾建军, 田静, 等. 浒苔遥感监测方法的研究进展[J]. 国土资源遥感, 2013, 25(1): 7-12. YE N, JIA J J, TIAN J, et al. Advances in the study of Ulvapolifera monitoring with remote sensing[J]. Remote Sensing for Land Resources, 2013, 25(1): 7-12.
[2] 王建伟, 阎斌伦, 林阿朋, 等. 浒苔(Enteromorpha prolifera)生长及孢子释放的生态因子研究[J]. 海洋通报, 2007, 26(2): 60-65. WANG J W, YAN B L, LIN A P, et al. Ecological factor research on the growth and induction of spores release in Enteromorpha Prolifera (Chlorophyta)[J]. Marine Science Bulletin, 2007, 26(2): 60-65.
[3] 吴孟泉, 郭浩, 张安定, 等. 2008年-2012年山东半岛海域浒苔时空分布特征研究[J]. 光谱学与光谱分析, 2014, 34(5): 1312-1318. WU M Q, GUO H, ZHANG A D, et al. Research on the characteristics of Ulva. prolifera in Shandong Peninsula during 2008-2012 based on MODIS data[J]. Spectroscopy and Spectral Analysis, 2014, 34(5): 1312-1318.
[4] 章志, 陈艳拢, 罗锋. 基于遥感技术的2014年南黄海浒苔时空分布特征研究[J]. 淮海工学院学报(自然科学版), 2016, 25(1): 80-85. ZHANG Z, CHEN Y L, LUO F. Temporal and spatial distribution characteristics of Enteromorpha prolifera in the south Yellow Sea based on remote sensing data of 2014[J]. Journal of Huaihai Institute of Technology (Natural Science Edition), 2016, 25(1): 80- 85.
[5] 矫新明, 袁广旺, 毛成责, 等. 2015年南黄海海域浒苔时空分布特征[J]. 杭州师范大学学报(自然科学版), 2017, 16(1): 51-56. JIAO X M, YUAN G W, MAO C Z, et al. Tempo-spatial distribution features of Ulva prolifera in South Yellow Sea in 2015[J]. Journal of Hangzhou Normal University (Natural Science Edition), 2017, 16(1): 51-56.
[6] 盛辉, 郭结琼, 王法景. 基于GOCI数据的2015年黄海海域绿潮监测及时空变化分析[J]. 测绘工程, 2018, 27(1): 52-58. SHENG H, GUO J Q, WANG F J. Monitoring of green algae and analysis of spatial-temporal changes based on GOCI image data in Yellow Sea in 2015[J]. Engineering of Surveying and Mapping, 2018, 27(1): 52-58.
[7] 张广宗, 吴孟泉, 孙晓, 等. 南黄海浒苔漂移轨迹年际变化规律及驱动因素[J]. 海洋与湖沼, 2018, 49(5): 1084-1093. ZHANG G Z, WU M Q, SUN X, et al. The inter-annual drift and driven force of Ulva prolifera bloom in the Southern Yellow Sea [J]. Oceanologia et Limnologia Sinica, 2018, 49(5): 1084-1093.
[8] 刘霜, 张洪亮, 刘旭东, 等. 2017年黄海绿潮特点及绿潮灾害防控新挑战[J]. 海岸工程, 2018, 37(4): 62-70. LIU S, ZHANG H L, LIU X D, et al. Green tide characteristics in the Yellow Sea in 2017 and new challenges in prevention and control of green tide disaster[J]. Coastal Engineering, 2018, 37(4): 62-70.
[9] 沈亚峰, 刘建强, 丁静, 等. 海洋一号C星光学载荷对海面溢油的识别能力分析[J]. 遥感学报, 2020, 24(8): 933-944. SHEN Y F, LIU J Q, DING J, et al. HY-1C COCTS and CZI observation of marine oil spills in the South China Sea[J]. Journal of Remote Sensing, 2020, 24(8): 933-944.
[10] 韩君君, 黄惠明, 张薇娜, 等. 2018年黄海浒苔分布特征及动力机制分析[J]. 海洋科学, 2020, 44(6): 37-44. HAN J J, HUANG H M, ZHANG W N, et al. Distribution characteristics and dynamic mechanism of Enteromorpha prolifera in the Yellow Sea in 2018[J]. Marine Sciences, 2020, 44(6): 37-44.
[11] 陈莹, 孙德勇, 张海龙, 等. 结合GOCI数据的黄海绿潮遥感监测及漂移轨迹研究[J]. 光学学报, 2020, 40(3): 7-19. CHEN Y, SUN D Y, ZHANG H L, et al. Remote-sensing monitoring of green tide and its drifting trajectories in Yellow Sea based on observation data of geostationary ocean color imager[J]. Acta Optica Sinica, 2020, 40(3): 7-19.
[12] 王宁, 黄娟, 崔廷伟, 等. 基于MODIS数据的5种植被指数对不同生长阶段绿潮的探测能力对比及应用[J]. 激光生物学报, 2014, 23(6): 590-595. WANG N, HUANG J, CUI T W, et al. Capability comparison of 5 vegetation indices for detecting the green tide in different development phases and the application[J]. Acta Laser Biology Sinica, 2014, 23(6): 590-595.

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