Wang Meng, Zheng Wei, Li Feng. Application of Himawari-8 data to enteromorpha prolifera dynamically monitoring in the Yellow Sea. J Appl Meteor Sci, 2017, 28(6): 714-723. DOI:  10.11898/1001-7313.20170607.
Citation: Wang Meng, Zheng Wei, Li Feng. Application of Himawari-8 data to enteromorpha prolifera dynamically monitoring in the Yellow Sea. J Appl Meteor Sci, 2017, 28(6): 714-723. DOI:  10.11898/1001-7313.20170607.

Application of Himawari-8 Data to Enteromorpha Prolifera Dynamically Monitoring in the Yellow Sea

DOI: 10.11898/1001-7313.20170607
  • Received Date: 2017-06-12
  • Rev Recd Date: 2017-10-23
  • Publish Date: 2017-11-30
  • As a new generation geostationary meteorological satellite, Himawari-8 can provide measurements dynamically monitoring of Enteromorpha prolifera, with its high temporal-spatial resolution. According to the normalized differential vegetation index NDVI, by studying reflection characteristics of enteromorpha, a method using Himawari-8 data is proposed for enteromorpha information detection, drift speed and intensity estimation. Using the above methods, the outbreak processes of enteromorpha prolifera in the Yellow Sea from May to July in 2016 are monitored including the appearing time, location, areas, intensity, range of influence, drift path and drift speed. Results show that the enteromorpha are detected firstly on 19 May 2016 in the Yellow Sea and areas are relatively small. It outbreaks in mid and late June with its continuous growth, and areas, range of influence and intensity all reach the maximum in this period. The enteromorpha enters recession period in early July near the coast of Shandong Province, the Yellow Sea, such as Qingdao, Yantai, Weihai and so on.The calculation shows that enteromorpha intensity changes with time, and multi-temporal enteromorpha intensity are accumulated into enteromorpha intensity synthetic product. The multi-temporal enteromorpha intensity synthetic product shows that enteromorpha intensity covers more in the central Yellow Sea and the east of Yantai waters, and less in initial position. The moving path of enteromorpha from appearance to disappearance shows that the drift path of enteromorpha is from the southeast open sea to the northwest offshore, and the average daily drift speed changes constantly.Dynamic changes of enteromorpha are closely related to the environmental hydro meteorological conditions, such as temperature, wind speed and direction. The suitable temperature is the basis for enteromorpha's growth and development. In late May, enteromorpha growth are detected near the northern coast of Jiangsu Province firstly, where the temperature is stably 20℃. And then in early June, enteromorpha area increases rapidly with the increasing temperature, and then outbreaks in mid-June when the temperature reaches 20℃ in east of Shandong Peninsula sea. In early July, the average temperature of the Yellow Sea is above 25℃, making the enteromorpha decay and disappear gradually. It shows that dominant wind direction is the main driving force of enteromorpha drift, the calculation shows that enteromorpha drifts northward with large and steady south wind from May to July in 2016, and finally arrive in Weihai coast, and the moving direction is in line with the wind.
  • Fig. 1  Enteromorpha monitoring images of the Yellow Sea in 2016

    Fig. 2  Enteromorpha distribution of the Yellow Sea in 2016

    Fig. 3  Enteromorpha intensity of the Yellow Sea in 2016

    Fig. 4  Enteromorpha composed intensity of the Yellow Sea from 19 May to 18 Jul in 2016

    Fig. 5  Enteromorpha drift path of the Yellow Sea in 2016

    Fig. 6  Temperature of the Yellow Sea observed by meteorological stations

    Fig. 7  Wind direction of Station 1(a) and Station 2(b) in 2016

    Table  1  Channel parameters of Himawari-8/AHI

    通道 中心波长/μm 空间分辨率/km
    1 0.46 1
    2 0.51 1
    3 0.64 0.5
    4 0.86 1
    5 1.6 2
    6 2.3 2
    7 3.9 2
    8 6.2 2
    9 7.0 2
    10 7.3 2
    11 8.6 2
    12 9.6 2
    13 10.4 2
    14 11.2 2
    15 12.3 2
    16 13.3 2
    DownLoad: Download CSV

    Table  2  Channel parameters of FY-3B/MERSI

    通道 波长范围/μm 空间分辨率/m
    1 0.45~0.50 250
    2 0.53~0.58 250
    3 0.63~0.66 250
    4 0.84~0.89 250
    5 10.50~12.50 250
    DownLoad: Download CSV

    Table  3  Channel parameters of GF-1/WFV

    通道 波长范围/μm 空间分辨率/m
    1 0.45~0.52 16
    2 0.52~0.59 16
    3 0.63~0.69 16
    4 0.77~0.89 16
    DownLoad: Download CSV

    Table  4  Enteromorpha areas in 2016

    时间 分布面积/km2 影响面积/km2
    05-19 128 3000
    05-25 600 7200
    06-01 1107 12000
    06-06 1306 12500
    06-09 1860 17000
    06-13 2780 23500
    06-17 3023 38000
    06-25 2980 37000
    07-02 1908 24800
    07-14 1340 17600
    07-18 130 3100
    DownLoad: Download CSV

    Table  5  Enteromorpha drift speed in 2016

    日期 漂移重心距青岛海岸距离/km V/(km·d-1)
    05-19 246
    05-25 226 3.3
    06-01 208 3.0
    06-06 120 17.6
    06-17 134 -1.3
    06-25 78 7
    07-02 96 -2.6
    07-14 82 1.2
    DownLoad: Download CSV
  • [1]
    张金荣, 唐旭利, 李国强.浒苔化学成分研究.中国海洋大学学报, 2010, 40(5):93-95. http://d.wanfangdata.com.cn/Periodical/qdhydxxb201005022
    [2]
    Zhao J, Jiang P, Liu Z Y, et al.Genetic variation of Ulva (Enteromorpha) prolifera (Ulvales, Chlorophyta)-the causative species of the green tides in the Yellow Sea, China.J Appl Phycol, 2011, 23:227-233. doi:  10.1007/s10811-010-9563-1
    [3]
    Cho M, Yang C, Kim S M, et al.Molecular characterization and biological activities of watersoluble sulfated polysaccharides from Enteromorpha prolifera.Food Science and Biotechnology, 2010, 19(2):525-533. doi:  10.1007/s10068-010-0073-3
    [4]
    张春桂, 曾银东, 马治国.基于模糊评价的福建沿海水质卫星遥感监测模型.应用气象学报, 2016, 27(1):112-122. doi:  10.11898/1001-7313.20160112
    [5]
    李三妹, 李亚军, 董海鹰, 等.浅析卫星遥感在黄海浒苔监测中的应用.应用气象学报, 2010, 21(1):76-82. doi:  10.11898/1001-7313.20100110
    [6]
    刘振宇, 江涛.基于MODIS数据的浒苔信息提取方法研究.测绘科学, 2008, 33(增刊Ⅰ):113-114. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=chkd2008s1046&dbname=CJFD&dbcode=CJFQ
    [7]
    Huo Y Z, Zhang J H, Chen L P, et al.Green algae blooms caused by Ulva prolifera in the southern Yellow Sea:Identification of the original bloom location and evaluation of biological processes occurring during the early northward floating period.Limnology & Oceanography, 2013, 58(6):2206-2218.
    [8]
    Lee C K, Park T G.Monitoring and trends in harmful algal blooms and red tides in Korean coastal waters, with emphasis on Cochlodinium polykrikoides.Harmful Algae, 2013, 30:3-14. doi:  10.1016/j.hal.2013.10.002
    [9]
    蒋兴伟, 邹亚荣, 王华, 等.基于SAR快速提取浒苔信息应用研究.海洋学报, 2009, 31(2):63-68. http://d.wanfangdata.com.cn/Periodical/hyxb200902009
    [10]
    薛瑞, 吴孟泉, 刘杨, 等.基于HJ-1A/1B的2014年黄海海域浒苔灾害时空分布.海洋科学, 2016, 40(7):115-123. doi:  10.11759/hykx20150911002
    [11]
    贾丽莉, 张安定, 吴孟泉.基于MODIS的2013年黄海海域浒苔灾害的时空分布.鲁东大学学报(自然科学版), 2015, 31(2):172-177. http://d.wanfangdata.com.cn/Periodical/ytsfxyxb201502015
    [12]
    张苏平, 刘应辰, 张广泉, 等.基于遥感资料的2008年黄海绿潮浒苔水文气象条件分析.中国海洋大学学报, 2009, 39(5):870-876. http://d.wanfangdata.com.cn/Periodical/qdhydxxb200905007
    [13]
    张春桂, 曾银东, 张星, 等.海洋叶绿素a浓度反演及其在赤潮监测中的应用.应用气象学报, 2007, 18(6):821-830. doi:  10.11898/1001-7313.200706124
    [14]
    荀尚培, 翟武全, 范伟.巢湖水体叶绿索a浓度反演模型.应用气象学报, 2009, 20(1):95-99. doi:  10.11898/1001-7313.20090112
    [15]
    王国伟, 李继龙, 杨文波, 等.利用MODIS和RADARSAT数据对浒苔的监测研究.海洋湖沼通报, 2010(4):1-8. http://d.wanfangdata.com.cn/Periodical/hyhztb201004001
    [16]
    李云波, 张永刚, 唐海川, 等.基于海气通量算法的海上蒸发波导诊断模型.应用气象学报, 2009, 20(5):628-633. doi:  10.11898/1001-7313.20090515
    [17]
    李颖, 梁刚, 于水明, 等.监测浒苔灾害的微波遥感数据选取.海洋环境科学, 2011, 30(5):739-742. http://d.wanfangdata.com.cn/Periodical/hyhjkx201105031
    [18]
    韩秀珍, 吴朝阳, 郑伟, 等.基于水面实测光谱的太湖蓝藻卫星遥感研究.应用气象学报, 2010, 21(6):724-731. doi:  10.11898/1001-7313.20100609
    [19]
    樊彦国, 白羽, 陈潘潘, 等.青岛近海浒苔光谱特征研究.海洋科学, 2015, 39(4):87-91. doi:  10.11759/hykx20130715003
    [20]
    陈怀亮, 刘玉洁, 杜子璇, 等.黄淮海地区植被生长季变化及其气候变化响应.应用气象学报, 2011, 22(4):437-444. doi:  10.11898/1001-7313.20110406
    [21]
    Hu C M.A novel ocean color index to detect floating algae in the global ocean.Remote Sens Environ, 2009, 113(10):2118-2129. doi:  10.1016/j.rse.2009.05.012
    [22]
    何进, 邵红兵, 刘东艳.不同温度与营养盐条件对浒苔(Ulva prolifera)和肠浒苔(Ulva intestinalis)的生长影响.海洋通报, 2013, 32(5):573-580. doi:  10.11840/j.issn.1001-6392.2013.05.015
    [23]
    李瑞香, 吴晓文, 韦钦胜, 等.不同营养盐条件下浒苔的生长.海洋科学进展, 2009, 27(2):211-216. http://d.wanfangdata.com.cn/Periodical/hbhhy200902011
    [24]
    王建伟, 闫斌伦, 林阿朋, 等.浒苔(Enteromorpha prolifera)生长及孢子释放的生态因子研究.海洋通报, 2007, 26(2):60-65. http://d.wanfangdata.com.cn/Periodical/hytb200702009
    [25]
    衣立, 张苏平, 殷玉齐, 等.2009年黄海绿潮浒苔爆发与漂移的水文气象环境.中国海洋大学学报, 2010, 40(10):15-23. http://d.wanfangdata.com.cn/Periodical/qdhydxxb201010003
    [26]
    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.光谱学与光谱分析, 2014, 34(5):1312-1328. http://d.wanfangdata.com.cn/Periodical/gpxygpfx201405038
    [27]
    Yamaguchi H, Mizushima K, Sakamoto S, et al.Effects of temperature, salinity and irradiance on growth of the novel red tide flagellate Chattonella ovate (Raphidophyceae).Harmful Algae, 2010, 9(4):398-401. doi:  10.1016/j.hal.2010.02.001
    [28]
    Song W, Peng K, Xiao J, et al.Effects of temperature on the germination of green algae micro-propagules in coastal waters of the Subei Shoal, China.Estuarine Coastal & Shelf Science, 2015, 163:63-68. http://www.sciencedirect.com/science/article/pii/S0272771414002224
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    • Received : 2017-06-12
    • Accepted : 2017-10-23
    • Published : 2017-11-30

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