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首页> 外文期刊>Aquatic ecosystem health & management >Deriving inherent optical property for highly turbid productive inland water from MERIS data by semi-analytical model: A case study in Taihu Lake, China
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Deriving inherent optical property for highly turbid productive inland water from MERIS data by semi-analytical model: A case study in Taihu Lake, China

机译:利用半解析模型从MERIS数据推论高浊度内陆生产水的固有光学特性:以中国太湖为例

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摘要

Remote estimation of inherent optical properties was greatly challenged by significant spatial-temporal variation and the extreme complexity of bio-optical properties in inland turbid water. The multiband quasi-analytical algorithm has advantages over traditional band ratio and semi-analytical algorithm in that it is based on the remote sensing reflectance model derived from radiative transfer equation and does not need the parameterization of absorption coefficients. An improved model, which used, was developed to retrieve inherent optical properties in high turbid inland water. As a first step, the backscattering coefficient at reference wavelength [b_(bp)(λ_0)] was retrieved directly by support vector machine optimization algorithm instead of step 2 in the quasi analytical algorithm for the high correlation between b_(bp)(λ_0) and remote sensing reflectance at the near-infrared wavelength. The second step, a semi-analytical support vector machine algorithm, was used to retrieve spectral shape of b_(bp)(λ) instead the step 4 in the quasi analytical algorithm. Part of field-measured dataset collected on November 2006, November 2007, November 2008 and April 2009 in Taihu Lake was used to train the support vector machine model, and the other part was used to test this algorithm. Results indicated that the mean square root of percentage between the derived and measured value of b_(bp)(532 nm) was less than 3.73% and root mean square percentage of a_p(442 nm) and a_p(532 nm) were 15.29% and 30.45%, respectively. Furthermore, the potential application of this algorithm to MERIS data was investigated by the reduced resolution MERIS satellite image. The result shows that satellite-derived data using the support vector machine model is consistent with in situ measured data. This study advances the semi-analytical model and broadens the application of MERIS data in highly turbid inland waters.
机译:内在浑浊水中显着的时空变化和生物光学特性的极端复杂性极大地挑战了固有光学特性的远程估计。多频带准分析算法基于传统的辐射比和半解析算法,其优点是基于辐射传递方程推导的遥感反射率模型,不需要对吸收系数进行参数化。开发了一种改进的模型,该模型用于检索高浊度内陆水中的固有光学特性。第一步,通过支持向量机优化算法而不是准分析算法中的步骤2直接获取参考波长[b_(bp)(λ_0)]上的反向散射系数,因为b_(bp)(λ_0)之间的相关性很高和近红外波长的遥感反射率。第二步是半分析支持向量机算法,用于检索b_(bp)(λ)的光谱形状,而不是准分析算法中的步骤4。分别于2006年11月,2007年11月,2008年11月和2009年4月在太湖采集的实测数据集的一部分用于训练支持向量机模型,另一部分用于测试该算法。结果表明,b_(bp)(532 nm)的导出值和测量值之间的百分比均方根小于3.73%,a_p(442 nm)和a_p(532 nm)的均方根百分比为15.29%,而分别为30.45%。此外,通过降低分辨率的MERIS卫星图像,研究了该算法在MERIS数据中的潜在应用。结果表明,使用支持向量机模型得到的卫星数据与现场实测数据一致。这项研究改进了半分析模型,并扩大了MERIS数据在高度浑浊的内陆水域中的应用。

著录项

  • 来源
    《Aquatic ecosystem health & management》 |2014年第3期|252-260|共9页
  • 作者单位

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China;

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China;

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China;

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China;

    College of Remote Sensing, Nanjing University of Information Science and Technology, Nanjing 210046, China;

    College of Marine Science, University of South Florida, Tampa, Florida, USA;

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    support vector machine; scattering and absorption coefficients; remote sensing reflectance;

    机译:支持向量机散射系数和吸收系数;遥感反射率;

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