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湖泊科学  2015 

一种基于MODIS影像可业务化运行的巢湖水体叶绿素a估算算法

DOI: 10.18307/2015.0620

Keywords: 业务化运行,叶绿素a,MODIS,经验正交函数,内陆水体,巢湖

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Abstract:

现有水色卫星主要是针对大洋清洁水体设计,内陆浑浊水体多数波段经常饱和;而发展可以业务化运行的内陆水体叶绿素a算法,为生产实践服务,一直是水色遥感的重点和难点之一.利用2013年巢湖星地同步数据(N=55),通过经验正交函数(empiricalorthogonalfunction,EOF)分析方法,选用MODIS唯一不饱和的4个波段(469、555、645、859nm)数据进行分解,然后回归建模;并使用第三方独立的巢湖实测数据(N=40)进行验证(R2=0.63,URMSE=85.46%).结果表明:该算法用于MODIS影像上,空间分布合理,季节差异明显,且在高悬浮物水体、不同气溶胶条件下均有很好的抗扰动性.实践证明EOF算法可以应用于业务化运行的内陆水体叶绿素a浓度估算,并对其他水色参数反演具有一定的借鉴意义.

References

[1]  王苏民, 窦鸿身. 中国湖泊志. 北京:科学出版社, 1998:230.
[2]  臧小平, 吴国平, 涂 敏. 长江流域湖泊水库水华防治对策. 人民长江, 2009, (9): 5-8.
[3]  Hu W, Jrgensen SE, Zhang F. A vertical-compressed three-dimensional ecological model in Lake Taihu, China. Ecological Modelling, 2006,190(3/4):367-398.
[4]  Hu C, Lee Z, Franz B.Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference. Journal of Geophysical Research, 2012,117(C1). DOI 10.1029/2011 JC 007395.
[5]  Schiller H, Doerffer R. Neural network for emulation of an inverse model operational derivation of Case Ⅱ water properties from MERIS data. International Journal of Remote Sensing, 1999,20(9): 1735-1746.
[6]  刘朝相, 宫兆宁, 赵文吉. 基于SVM模型的妫水河Chl.a浓度的遥感反演. 遥感技术与应用, 2014,29(3): 419-427.
[7]  Craig SE, Jones CT, Li WKW et al. Deriving optical metrics of coastal phytoplankton biomass from ocean colour. Remote Sensing of Environment, 2012, 119:72-83.
[8]  姜广甲, 周 琳, 马荣华等. 浑浊Ⅱ类水体Chl.a浓度遥感反演(Ⅱ): MERIS遥感数据的应用. 红外与毫米波学报, 2013, 32(4): 372-378.
[9]  马荣华, 孔维娟, 段洪涛等. 基于MODIS影像估测太湖蓝藻暴发期藻蓝素含量. 中国环境科学, 2009,29(3): 254-260.
[10]  Ma R, Tang J, Dai J.Bio-optical model with optimal parameter suitable for Taihu Lake in water colour remote sensing. International Journal of Remote Sensing, 2006, 27(19):4305-4328.
[11]  Cleveland JS, Weidemann AD. Quantifying absorption by aquatic particles: A multiply scattering correction for glass-fiber filters. Limnology and Oceanography, 1993, 38(6):1321-1327.
[12]  Duan H, Ma R, Hu C. Evaluation of remote sensing algorithms for cyanobacterial pigment retrievals during spring bloom formation in several lakes of East China. Remote Sensing of Environment, 2012,126:126-135.
[13]  Duan H, Feng L, Ma R et al. Variability of particulate organic carbon in inland waters observed from MODIS Aqua imagery. Environmental Research Letters, 2014,9(8):084011.
[14]  Le C, Hu C, English D et al. Climate-driven chlorophyll-a changes in a turbid estuary: Observations from satellites and implications for management. Remote Sensing of Environment, 2013,130:11-24.
[15]  Hu C, Chen Z, Clayton TD et al. Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: Initial results from Tampa Bay, FL. Remote Sensing of Environment, 2004,93(3):423-441.
[16]  Mueller JL. Ocean color spectra measured off the Oregon coast: characteristic vectors. Applied Optics, 1976,15(2): 394-402.
[17]  Barnes BB, Hu C, Cannizzaro JP et al. Estimation of diffuse attenuation of ultraviolet light in optically shallow Florida Keys waters from MODIS measurements. Remote Sensing of Environment, 2014, 140:519-532.
[18]  Hooker SB, Lazin G, Zibordi G et al. An evaluation of above-and in-water methods for determining water-leaving radiances. Journal of Atmospheric and Oceanic Technology, 2002,19(4): 486-515.
[19]  李宝慧. 浅谈复杂样本方差估计的一种方法——刀切法. 统计教育, 1998, (5):24.
[20]  Qi L, Hu C, Duan H et al. A novel MERIS algorithm to derive cyanobacterial phycocyanin pigment concentrations in a eutrophic lake: Theoretical basis and practical considerations. Remote Sensing of Environment, 2014, 154: 298-317.

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