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南黄海金潮的遥感监测及时空分布特征研究

郑龙啸 吴孟泉 赵杰 王东亮 周敏 赵连杰

郑龙啸,吴孟泉,赵杰,等. 南黄海金潮的遥感监测及时空分布特征研究[J]. 海洋学报,2022,44(5):12–24 doi: 10.12284/hyxb2022095
引用本文: 郑龙啸,吴孟泉,赵杰,等. 南黄海金潮的遥感监测及时空分布特征研究[J]. 海洋学报,2022,44(5):12–24 doi: 10.12284/hyxb2022095
Zheng Longxiao,Wu Mengquan,Zhao Jie, et al. Remote sensing monitoring and temporal and spatial distribution characteristics of gold tide in the South Yellow Sea[J]. Haiyang Xuebao,2022, 44(5):12–24 doi: 10.12284/hyxb2022095
Citation: Zheng Longxiao,Wu Mengquan,Zhao Jie, et al. Remote sensing monitoring and temporal and spatial distribution characteristics of gold tide in the South Yellow Sea[J]. Haiyang Xuebao,2022, 44(5):12–24 doi: 10.12284/hyxb2022095

南黄海金潮的遥感监测及时空分布特征研究

doi: 10.12284/hyxb2022095
基金项目: 国家自然科学基金(42071385);山东省自然科学基金(ZR2019MD041,ZR2015DM015);山东省海上航天装备技术创新中心(鲁东大学)开放课题基金(HHCXZX-2021-12)。
详细信息
    作者简介:

    郑龙啸(1998-) ,男,山东省日照市人,主要从事海洋环境遥感、土地利用变化、空间分析与3S 应用方向研究。E-mail: zlxld123@163.com

    通讯作者:

    吴孟泉(1975-),男,山东省临沂市人,教授,博士,主要从事海洋环境遥感、空间分析及3S 应用方向研究。 E-mail: ld_wmq@ldu.edu.cn

  • 中图分类号: X87;X834

Remote sensing monitoring and temporal and spatial distribution characteristics of gold tide in the South Yellow Sea

  • 摘要: 近年来海洋生态灾害频发,大量漂浮藻类聚集在海面和近岸海域,给沿岸城市的经济活动和生态健康带来了严重危害。本研究利用HY-1C、GF-1和HJ-1A/1B卫星遥感影像对南黄海海域2016–2020年4–6月份的马尾藻进行了信息提取和生长阶段的划分,并通过MODIS海温数据、光合有效辐射数据和海面风场数据来探究环境因子对马尾藻时空分布的影响。结果表明:(1)从时间上看马尾藻集中在每年的4–6月份暴发,2017年马尾藻的影响范围最大,其余年份较小;从空间上看马尾藻最早在长江入海口东北部远海被监测到,在35°~36°N附近海域消失;(2)从生长速率上看,马尾藻的生长阶段可以划分为“发展–暴发–消亡”3个阶段;(3)在不同的生长阶段,海水温度和光合有效辐射对马尾藻具有不同程度的影响,较高的海表温度和光合有效辐射导致2017年面积高于往年;在东南风的作用下,马尾藻呈从东南向西北漂移的趋势,这说明了马尾藻的时空特征受到多种环境因子的影响。
  • 图  1  研究区范围(底图为几何校正后的 HY-1C影像)

    a, b. 研究区;c. 漂浮的马尾藻;d. 实测光谱曲线

    Fig.  1  Study area (the map is HY-1C geometric correction image)

    a, b. Study area; c. the floating Sargassum; d. the spectral curve

    图  2  数据处理流程

    Fig.  2  Flow chart of data processing

    图  3  HY-1C卫星和GF-1卫星真彩色影像

    波段组合为R:3,G:2,B:1,A和B表示浒苔,C和D表示马尾藻,a、b、c、d和e是随机选取的样本区域

    Fig.  3  HY-1C satellite and GF-1 satellite true color images

    Band combination is R:3, G:2, B:1. A and B represent Ulva prolifera, C and D represent Sargassum. a, b, c, d and e are randomly selected sample areas

    图  4  浒苔(a)、马尾藻(b)和海水(c)VB-FAH数值分布

    Fig.  4  Distribution of VB-FAH values for Ulva prolifera (a), Sargassum (b) and seawater (c)

    图  5  2016−2020年马尾藻覆盖面积

    Fig.  5  Coverage area of Sargassum in 2016−2020

    图  6  2016−2020年马尾藻时空分布(a−e)及漂移路径(f)

    Fig.  6  Temporal and spatial distribution (a−e) and drift paths (f) of Sargassum in 2016−2020

    图  7  南黄海2016−2020年马尾藻最大日覆盖面积

    Fig.  7  Maximum daily coverage area of Sargassum in the South Yellow Sea in 2016−2020

    图  8  2016−2020年马尾藻覆盖面积和增长率

    Fig.  8  Cover area and growth rate of Sargassum in 2016−2020

    图  9  海表温度(SST)对不同阶段马尾藻的影响

    Fig.  9  Effects of sea surface temperature on Sargassum in different stages

    图  10  黄海2016−2020年4–6月海温异常(SSTA)

    Fig.  10  Sea surface temperature anomaly (SSTA) in the Yellow Sea from April to June in 2016−2020

    图  11  光合有效辐射(PAR)对不同阶段马尾藻的影响

    Fig.  11  Effects of photosynthetically active radiation on Sargassum in different stages

    图  12  黄海2016−2020年4−6月光合有效辐射异常(PARA)

    Fig.  12  Photosynthetically active radiation anomaly (PARA) in the Yellow Sea from April to June in 2016−2020

    图  13  2016−2020年南黄海4−6月海面风场

    Fig.  13  Sea surface wind field of the South Yellow Sea from April to June in 2016−2020

    表  1  HY-1C、GF-1和HJ-1A/1B卫星影像日期

    Tab.  1  The image date of HY-1C, GF-1 and HJ-1A/1B satellite

    HY-1C日期HJ-1A/1B日期GF-1日期
    2016年5月28日5月11日,5月17日,5月19日,6月1日,6月13日
    2017年5月21日4月29日,5月7日,5月1日,5月14日,5月18日,5月27日,6月9日
    2018年5月25日,5月31日4月28日,5月10日,5月14日,5月23日
    2019年5月7日,5月23日5月16日5月3日,5月31日,6月3日
    2020年5月15日,5月18日,6月8日4月24日,6月3日
    注:−代表无数据。
    下载: 导出CSV
  • [1] Gower J, Young E, King S. Satellite images suggest a new Sargassum source region in 2011[J]. Remote Sensing Letters, 2013, 4(8): 764−773. doi: 10.1080/2150704X.2013.796433
    [2] 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. doi: 10.3964/j.issn.1000-0593(2014)05-1312-07

    Wu Mengquan, Guo Hao, Zhang Anding, 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. doi: 10.3964/j.issn.1000-0593(2014)05-1312-07
    [3] 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. doi: 10.11693/hyhz20180400093

    Zhang Guangzong, Wu Mengquan, Sun Xiao, 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. doi: 10.11693/hyhz20180400093
    [4] Yuan Chunying, Yang Shuo, Wang Yue, et al. Effect of temperature on the growth and biochemical composition of Sargassum muticum[J]. Advanced Materials Research, 2014, 989−994: 747−750. doi: 10.4028/www.scientific.net/AMR.989-994.747
    [5] Smetacek V, Zingone A. Green and golden seaweed tides on the rise[J]. Nature, 2013, 504(7478): 84−88. doi: 10.1038/nature12860
    [6] Liu Jinlin, Xia Jing, Zhuang Minmin, et al. Golden seaweed tides accumulated in Pyropia aquaculture areas are becoming a normal phenomenon in the Yellow Sea of China[J]. Science of the Total Environment, 2021, 774: 145726. doi: 10.1016/j.scitotenv.2021.145726
    [7] Sudhakar K, Mamat R, Samykano M, et al. An overview of marine macroalgae as bioresource[J]. Renewable and Sustainable Energy Reviews, 2018, 91: 165−179. doi: 10.1016/j.rser.2018.03.100
    [8] Chen Yanlong, Wan Jianhua, Zhang Jie, et al. Spatial-temporal distribution of golden tide based on high-resolution satellite remote sensing in the South Yellow Sea[J]. Journal of Coastal Research, 2019, 90(SI): 221−227.
    [9] Cuevas E, Uribe-Martínez A, de los Ángeles Liceaga-Correa M. A satellite remote-sensing multi-index approach to discriminate pelagic Sargassum in the waters of the Yucatan Peninsula, Mexico[J]. International Journal of Remote Sensing, 2018, 39(11): 3608−3627. doi: 10.1080/01431161.2018.1447162
    [10] Gower J F R, King S A. Distribution of floating Sargassum in the Gulf of Mexico and the Atlantic Ocean mapped using MERIS[J]. International Journal of Remote Sensing, 2011, 32(7): 1917−1929. doi: 10.1080/01431161003639660
    [11] Xing Qianguo, Guo Ruihong, Wu Lingling, et al. High-resolution satellite observations of a new hazard of golden tides caused by floating Sargassum in winter in the Yellow Sea[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(10): 1815−1819. doi: 10.1109/LGRS.2017.2737079
    [12] Xiao Jie, Fan Shiliang, Wang Zongling, et al. Decadal characteristics of the floating Ulva and Sargassum in the Subei Shoal, Yellow Sea[J]. Acta Oceanologica Sinica, 2020, 39(10): 1−10. doi: 10.1007/s13131-020-1655-4
    [13] 孔凡洲, 姜鹏, 魏传杰, 等. 2017年春、夏季黄海35°N共发的绿潮、金潮和赤潮[J]. 海洋与湖沼, 2018, 49(5): 1021−1030. doi: 10.11693/hyhz20180400082

    Kong Fanzhou, Jiang Peng, Wei Chuanjie, et al. Co-occurence of green tide, golden tide and red tides along the 35°N transect in the Yellow Sea during spring and summer in 2017[J]. Oceanologia et Limnologia Sinica, 2018, 49(5): 1021−1030. doi: 10.11693/hyhz20180400082
    [14] 李雪娜, 韩震, 刘贤博, 等. 浒苔和马尾藻的生消与海表面温度的相互影响研究[J]. 海洋湖沼通报, 2016(5): 125−130.

    Li Xuena, Han Zhen, Liu Xianbo, et al. A study of the relationship between the processes of enteromorpha and sargassum and sea surface temperature[J]. Transactions of Oceanology and Limnology, 2016(5): 125−130.
    [15] 王宁, 曹丛华, 黄娟, 等. 浒苔和马尾藻遥感区分方法在业务监测中的应用研究[J]. 海洋预报, 2019, 36(4): 68−75. doi: 10.11737/j.issn.1003-0239.2019.04.009

    Wang Ning, Cao Conghua, Huang Juan, et al. Application research of enteromorpha and sargassum distinguishing method in operational monitoring[J]. Marine Forecasts, 2019, 36(4): 68−75. doi: 10.11737/j.issn.1003-0239.2019.04.009
    [16] Sun Deyong, Chen Ying, Wang Shengqiang, et al. Using Landsat 8 OLI data to differentiate Sargassum and Ulva prolifera blooms in the South Yellow Sea[J]. International Journal of Applied Earth Observation and Geoinformation, 2021, 98: 102302. doi: 10.1016/j.jag.2021.102302
    [17] 金松, 韩震, 刘瑜. 一种区分浒苔和马尾藻的遥感方法[J]. 遥感信息, 2016, 31(2): 44−48. doi: 10.3969/j.issn.1000-3177.2016.02.008

    Jin Song, Han Zhen, Liu Yu. A remote sensing method for discriminating Ulva prolifera and Sargassum[J]. Remote Sensing Information, 2016, 31(2): 44−48. doi: 10.3969/j.issn.1000-3177.2016.02.008
    [18] 孙晓, 吴孟泉, 何福红, 等. 2015年黄海海域浒苔时空分布及台风“灿鸿”影响研究[J]. 遥感技术与应用, 2017, 32(5): 921−930.

    Sun Xiao, Wu Mengquan, He Fuhong, et al. Temporal and spatial distribution of Ulva. prolifera in the Yellow Sea and influence of typhoon “CHAN-HOM” in 2015[J]. Remote Sensing Technology and Application, 2017, 32(5): 921−930.
    [19] Sun Xiao, Wu Mengquan, Xing Qianguo, et al. Spatio-temporal patterns of Ulva prolifera blooms and the corresponding influence on chlorophyll-a concentration in the Southern Yellow Sea, China[J]. Science of the Total Environment, 2018, 640−641: 807−820. doi: 10.1016/j.scitotenv.2018.05.378
    [20] Zhou Yuping, Tan Liju, Pang Qiuting, et al. Influence of nutrients pollution on the growth and organic matter output of Ulva prolifera in the southern Yellow Sea, China[J]. Marine Pollution Bulletin, 2015, 95(1): 107−114. doi: 10.1016/j.marpolbul.2015.04.034
    [21] Zhang Haibo, Wang Guoshan, Zhang Chuansong, et al. Characterization of the development stages and roles of nutrients and other environmental factors in green tides in the Southern Yellow Sea, China[J]. Harmful Algae, 2020, 98: 101893. doi: 10.1016/j.hal.2020.101893
    [22] Keesing J K, Liu Dongyan, Fearns P, et al. Inter-and intra-annual patterns of Ulva prolifera green tides in the Yellow Sea during 2007–2009, their origin and relationship to the expansion of coastal seaweed aquaculture in China[J]. Marine Pollution Bulletin, 2011, 62(6): 1169−1182. doi: 10.1016/j.marpolbul.2011.03.040
    [23] Xu Fan, Tao Jianfeng, Zhou Zeng, et al. Mechanisms underlying the regional morphological differences between the northern and southern radial sand ridges along the Jiangsu Coast, China[J]. Marine Geology, 2016, 371: 1−17. doi: 10.1016/j.margeo.2015.10.019
    [24] Zheng Longxiao, Wu Mengquan, Zhou Min, et al. Spatiotemporal distribution and influencing factors of Ulva prolifera and Sargassum and their coexistence in the South Yellow Sea, China[J]. Journal of Oceanology and Limnology, 2021, 40(3): 1070−1084.
    [25] Strong A E, McClain E P. Improved ocean surface temperatures from space—comparisons with drifting buoys[J]. Bulletin of the American Meteorological Society, 1984, 65(2): 138−142. doi: 10.1175/1520-0477(1984)065<0138:IOSTFS>2.0.CO;2
    [26] Van Laake P E, Sanchez-Azofeifa G A. Simplified atmospheric radiative transfer modelling for estimating incident PAR using MODIS atmosphere products[J]. Remote Sensing of Environment, 2004, 91(1): 98−113. doi: 10.1016/j.rse.2004.03.002
    [27] Van Laake P E, Sanchez-Azofeifa G A. Mapping PAR using MODIS atmosphere products[J]. Remote Sensing of Environment, 2005, 94(4): 554−563. doi: 10.1016/j.rse.2004.11.011
    [28] 袁超, 张靖宇, 肖洁, 等. 基于哨兵2号卫星遥感影像的2018年苏北浅滩漂浮绿藻时空分布特征研究[J]. 海洋学报, 2020, 42(8): 12−20.

    Yuan Chao, Zhang Jingyu, Xiao Jie, et al. The spatial and temporal distribution of floating green algae in the Subei Shoal in 2018 retrieved by Sentinel-2 images[J]. Haiyang Xuebao, 2020, 42(8): 12−20.
    [29] Hu Chuanmin, Feng Lian, Hardy R F, et al. Spectral and spatial requirements of remote measurements of pelagic Sargassum macroalgae[J]. Remote Sensing of Environment, 2015, 167: 229−246. doi: 10.1016/j.rse.2015.05.022
    [30] Xing Qianguo, Hu Chuanmin. Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and Landsat data: application of a virtual baseline reflectance height technique[J]. Remote sensing of Environment, 2016, 178: 113−126. doi: 10.1016/j.rse.2016.02.065
    [31] Keesing J K, Liu Dongyan, Shi Yajun, et al. Abiotic factors influencing biomass accumulation of green tide causing Ulva spp. on Pyropia culture rafts in the Yellow Sea, China[J]. Marine Pollution Bulletin, 2016, 105(1): 88−97. doi: 10.1016/j.marpolbul.2016.02.051
    [32] Zhang Jianheng, Kim J K, Yarish C, et al. The expansion of Ulva prolifera O. F. Müller macroalgal blooms in the Yellow Sea, PR China, through asexual reproduction[J]. Marine Pollution Bulletin, 2016, 104(1/2): 101−106.
    [33] Zhang Guangzong, Wu Mengquan, Zhang Anding, et al. Influence of sea surface temperature on outbreak of Ulva prolifera in the Southern Yellow Sea, China[J]. Chinese Geographical Science, 2020, 30(4): 631−642. doi: 10.1007/s11769-020-1129-9
    [34] Song Wei, Peng Keqin, Xiao Jie, et al. Effects of temperature on the germination of green algae micro-propagules in coastal waters of the Subei Shoal, China[J]. Estuarine, Coastal and Shelf Science, 2015, 163: 63−68. doi: 10.1016/j.ecss.2014.08.007
    [35] Graba-Landry A C, Loffler Z, McClure E C, et al. Impaired growth and survival of tropical macroalgae (Sargassum spp. ) at elevated temperatures[J]. Coral Reefs, 2020, 39(2): 475−486. doi: 10.1007/s00338-020-01909-7
    [36] 伍玉梅, 徐兆礼, 樊伟, 等. 1985−2005年东海海表温度时空变化特征分析[J]. 海洋学报, 2011, 33(6): 9−18.

    Wu Yumei, Xu Zhaoli, Fan Wei, et al. Change of sea surface temperature in East China Sea during 1985−2005[J]. Haiyang Xuebao, 2011, 33(6): 9−18.
    [37] Wu Hailong, Feng Jingchi, Li Xinshu, et al. Effects of increased CO2 and temperature on the physiological characteristics of the golden tide blooming macroalgae Sargassum horneri in the Yellow Sea, China[J]. Marine Pollution Bulletin, 2019, 146: 639−644. doi: 10.1016/j.marpolbul.2019.07.025
    [38] Gao Guang, Clare A S, Rose C, et al. Intrinsic and extrinsic control of reproduction in the green tide-forming alga, Ulva rigida[J]. Environmental and Experimental Botany, 2017, 139: 14−22. doi: 10.1016/j.envexpbot.2017.03.016
    [39] Kim J, Park J H, Lee T H. Sensitivity analysis of steel buildings subjected to column loss[J]. Engineering Structures, 2011, 33(2): 421−432. doi: 10.1016/j.engstruct.2010.10.025
    [40] Xing Qianguo, Hu Chuanmin, Tang Danling, et al. World’s largest macroalgal blooms altered phytoplankton biomass in summer in the Yellow Sea: satellite observations[J]. Remote Sensing, 2015, 7(9): 12297−12313. doi: 10.3390/rs70912297
    [41] Qiao Fangli, Wang Guansuo, Lü Xingang, et al. Drift characteristics of green macroalgae in the Yellow Sea in 2008 and 2010[J]. Chinese Science Bulletin, 2011, 56(21): 2236−2242. doi: 10.1007/s11434-011-4551-7
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  • 收稿日期:  2021-05-27
  • 修回日期:  2021-09-08
  • 网络出版日期:  2022-06-15
  • 刊出日期:  2022-06-15

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