香港近海海域叶绿素a定量反演及时空变化分析

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Abstract This paper statistically analyzed the correlation between reflectance of different band combinations and chlorophyll-a concentration using HJ-1A/B satellite multispectral images and measured measurement from 2009 to 2019. The statistical regression analysis was performed between the band combination with the highest correlation selected as a characteristic variable and 2/3 of the total measured chlorophyll-a concentration data to build inversion models. Theses inversion models were evaluated using the rest of measured chlorophyll-a concentration data to determine the best remote sensing inversion model, which was utilized to calculate the chlorophyll-a concentration in coastal waters of Hong Kong from 2009 to 2019, and clarify the spatiotemporal characteristics of chlorophyll-a in the past 10 years. The results indicate that:The optimal band combination derived from HJ-1A/B multispectral data is the ratio of band 3and band 2 (B3/B2), which had the highest correlation with the chlorophyll-a concentration in Hong Kong's coastal waters. The correlation coefficient (r) is 0.893. The best inversion model is the e-exponential regression model (), the determination coefficient (R²) is 0.934, the root means square error (RMSE) is 0.255μg/L, and the relative average error (RPD) is 25%. The spatial distribution characteristics of chlorophyll-a concentration in Hong Kong's coastal waters is high in east and low in west, gradually decreasing from east to west in the past 10years. The average concentration of chlorophyll-a in the western waters are about 5μg/L lower than the in the eastern waters. The seasonal variation of chlorophyll-a concentration in 2017 was low in the spring, and high in the autumn, rising in the summer and dropping in the winter. The chlorophyll-a concentration is the highest in autumn, followed by summer and spring, lowest in winter.

Key words： chlorophyll a concentration HJ-1A/B satellite multispectral image quantitative inversion temporal and spatial distribution characteristics

Received: 23 October 2019

PACS:	X55
	X145
	X87

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	Articles by authors
	SUN Hong-liang
	HE Hong-chang
	FU Bo-lin
	WANG Shi-wen
	MA Rui-xue
	WU Ming-fu

Cite this article:

SUN Hong-liang,HE Hong-chang,FU Bo-lin等. Quantitative inversion and analysis of spatio-temporal changes of chlorophyll-a concentration in Hong Kong's coastal waters[J]. CHINA ENVIRONMENTAL SCIENCECE, 2020, 40(5): 2222-2229.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2020/V40/I5/2222

[1]	丛丕福,曲丽梅,王臣立,等.基于MODIS模拟的辽东湾叶绿素a的遥感反演模型[J]. 生态环境学报, 2009,18:2057-60. Cong P F, Qu L M, Wang L C, et al. Remote sensing inversion model of chlorophyll-a in Liaodong Bay based on MODIS Simulation[J]. Journal of Eco-Environment, 2009,18(6):2057-2060.
[2]	秦平,沈钺,牟冰,等.基于进化建模方法的HJ-1CCD黄海悬浮物和叶绿素a浓度遥感反演模型研究[J]. 海洋学报, 2014,36:142-9. Qin P, Shen Y, Mou B, et al. Remote sensing inversion model of HJ-1CCD yellow sea suspension and chlorophyll-a concentration based on evolutionary modeling method[J]. Acta Oceanica Sinica, 2014,36:142-9.
[3]	Sarangi R K. Remote sensing observations of ocean surface chlorophyll and temperature with the impact of cyclones and depressions over the bay of Bengal water[J]. Marine Geodesy, 2015, 39:53-76.
[4]	Yao J, Yang L, Shu Y, et al. Comparison of summer chlorophyll-a concentration in the South China Sea and the Arabian Sea using remote sensing data[J]. Acta Oceanologica Sinica, 2017,36:61-7.
[5]	Guimarães T, Voronezh M, Koste E, et al. An alternative method of spatial autocorrelation for chlorophyll detection in water bodies using Remote Sensing[J]. Sustainability, 2017,9:76:83.
[6]	郑高强,陈芸芝,汪小钦,等.基于HJ-1卫星CCD数据的厦门海域叶绿素a浓度反演[J]. 遥感技术与应用, 2015,30:235-41+84. Zheng G Q, Chen Y Z, Wang X Q, et al. Inversion of chlorophyll-a concentration in Xiamen Sea Area based on HJ-1satellite CCD data[J]. Remote Sensing Technology and Application, 2015,30:235-41+84.
[7]	罗建美,霍永伟,韩晓庆.基于HJ卫星的近岸Ⅱ类水体叶绿素a浓度定量遥感反演研究——以滦河口北部海域为例[J]. 海洋学报, 2017,39:117-29. Luo J M, Huo Y W, Han X Q. Quantitative remote sensing inversion of chlorophyll-a concentration in Nearshore II saters based on HJ Satellite——a case study of the Northern waters of the Weihe Estuary[J]. Acta Oceanica Sinica, 2017,39:117-29.
[8]	杨婷,张慧,王桥,等.基于HJ-1A卫星超光谱数据的太湖叶绿素a浓度及悬浮物浓度反演[J]. 环境科学, 2011,32:3207-14. Yang T, Zhang H, Wang Q, et al. Inversion of chlorophyll-a concentration and suspended solids concentration in Taihu Lake based on HJ-1A satellite hyperspectral data[J]. Environmental science, 2011, 32:3207-14.
[9]	陈莉琼,田礼乔,邱凤,等. HJ-1A/B卫星CCD影像的武汉市东湖水色三要素遥感研究[J]. 武汉大学学报(信息科学版), 2011,36:1280-3+335. Chen L Q, Tian L Q, Qiu F, et al. Three-element remote sensing study of East Lake color in Wuhan City based on HJ-1A/B Satellite CCD image[J]. Journal of Wuhan University (Information Science Edition), 2011,36:1280-3+335.
[10]	黄启会,贺中华,梁虹,等.基于HJ-1A CCD数据的湖泊叶绿素a浓度反演——以贵阳市百花湖为例[J]. 人民长江, 2019,50:66-72. Huang Q H, He Z H, Liang H, et al. Inversion of chlorophyll-a concentration in lakes based on HJ-1A CCD data:a case study of Baihua Lake in Guiyang City[J]. People's Yangtze River, 2019,50:66-72.
[11]	Menon H B, Adhikari A. Remote sensing of chlorophyll-a in case II Waters:a novel approach with improved accuracy over widely implemented turbid water indices[J]. Journal of Geophysical Research:Oceans, 2018,123:8138-58.
[12]	席红艳,张渊智,丘仲锋,等.基于半分析算法的香港邻近海域叶绿素a浓度反演[J]. 湖泊科学, 2009,21(2):199-206. Xi H Y, Zhang Z Y, Qiao Z F, et al. A semi-analytical algorithm to retrieve chlorophyll-a concentrations in the coastal region of Hong Kong and its vicinity[J]. Lake Sci., 2009, 21(2):199-206.
[13]	陈晓玲,李毓湘,李志林.香港海域叶绿素-a浓度的时空分布规律[J]. 地理学报, 2002,(4):422-428. Chen X L, Li S X, Li Z L. Spatio-temporal distribution of chlorophyll-a concentration in Hong Kang's coastal waters[J]. Acra Geographic Sinica, 2002,(4):422-428.
[14]	温新龙,景元书,李亚春,等.基于环境一号卫星数据的太湖叶绿素a浓度反演[J]. 环境科学与技术, 2014,37:149-53. Wen X L, Jing Y S, Li Y C, et al. Inversion of chlorophyll-a concentration in Taihu Lake based on Environmental satellite data[J]. Environmental Science and Technology, 2014,37:149-53.
[15]	Frankenberg C, O'Dell C, Berry J, et al. Prospects for chlorophyll fluorescence remote sensing from the orbiting carbon observatory-2[J]. Remote Sensing of Environment, 2014,147:1-12.
[16]	Ač A, Malenovský Z, Olejníčková J, Gallé A, et al. Meta-analysis assessing potential of steady-state chlorophyll fluorescence for remote sensing detection of plant water, temperature and nitrogen stress[J]. Remote Sensing of Environment, 2015,168:420-36.
[17]	赵文静,曹文熙,王桂芬,等.南海海域MODIS-Aqua叶绿素浓度产品的精度对比和区域性算法修正[J]. 光学精密工程, 2014,22:3081-90. Zhao W J, Cao W X, Wang G F, et al. Accuracy comparison and regional algorithm correction of MODIS-Aqua chlorophyll concentration products in the South China Sea[J]. Optics and Precision Engineering, 2014,22:3081-90.
[18]	旷达,韩秀珍,刘翔,等.基于环境一号卫星的太湖叶绿素a浓度提取[J]. 中国环境科学, 2010,30:1268-73. Kuang D, Han X Z, Liu X, et al. Extraction of chlorophyll-a concentration in Taihu Lake based on Environmental No.1satellite[J]. China Environmental Science, 2010,30:1268-73.
[19]	Loosen Y, Rebel KT, Karssenberg D, et al. Remote sensing of canopy nitrogen at regional scale in Mediterranean forests using the spaceborne MERIS Terrestrial Chlorophyll Index[J]. Biogeosciences, 2018,15:2723-42.
[20]	刘海香,张彩明.平面上离散数据点的二次曲线拟合[J]. 计算机辅助设计与图形学学报, 2004,16(11):1594-8. Liu H X, Zhang C M. Quadratic curve fitting of discrete data points on plane[J]. Journal of Computer-Aided Design & Computer Graphics, 2004,16(11):1594-8.
[21]	罗成汉,刘小山.曲线拟合法的Matlab实现[J]. 现代电子技术, 2003,26(20):16-17. Luo C H, Liu X S. Matlab implementation of curve fitting method[J]. modern electronic technology, 2003,26(20):16-17.
[22]	王光裕.参量回归与指数函数曲线拟合[J]. 河北工业大学学报, 2008,1991(3):96-102. Wang G Y. Curve fitting of parametric regression and exponential function[J]. Journal of Hebei University of Technology, 2008,1991(3):96-102.
[23]	Lin S, Qi J, Jones J R, Stevenson R J. Effects of sediments and colored dissolved organic matter on remote sensing of chlorophyll-a using Landsat TM/ETM+ over turbid waters[J]. International Journal of Remote Sensing, 2017,39:1421-40.
[24]	Xu X, Du H, Zhou G, et al. Remote estimation of canopy leaf area index and chlorophyll content in Moso bamboo (Phyllostachys edulis (Carrière) J. Houz.) forest using MODIS reflectance data[J]. Annals of Forest Science, 2018,75:82-9.
[25]	周正,何连,刘良明.基于HJ-1A/B CCD数据的东湖叶绿素a浓度反演可行性研究[J]. 测绘通报, 2011,3:11-14. Zhou Z, He L, Liu L M. Feasibility study on inversion of chlorophyll-a concentration in East Lake based on HJ-1A/B CCD data[J]. Bulletin of Surveying and Mapping, 2011,3:11-14.
[26]	Huang L, Zheng Y, Yu Q, et al. Remote estimation of colored dissolved organic matter and chlorophyll-a in Lake Huron using Sentinel-2measurements[J]. Journal of Applied Remote Sensing, 2017,11:24-29.
[27]	席红艳,张渊智,丘仲锋,等.基于半分析算法的香港邻近海域叶绿素a浓度反演[J]. 湖泊科学, 2009,21:199-206. Xi H Y, Zhang Y Z, Qiu Z F, et al. Inversion of Chlorophyll-a concentration in the adjacent sea area of Hong Kong based on semi-analytic algorithm[J]. Journal of Lake Science, 2009,21:199-206.
[28]	吴健生.基于HJ-1影像和环境变量的叶绿素a浓度反演——以深圳海域为例[J]. 海洋环境科学, 2018,37:424-31. Wu J S. Inversion of chlorophyll-a concentration based on HJ-1image and environmental variables——a case study of Shenzhen Sea Area[J]. Marine Environmental Science, 2018,37:424-31.