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基于半分析模型的波段最优化组合反演混浊太湖水体叶绿素a
  • 期刊名称:湖泊科学
  • 时间:0
  • 页码:266-271
  • 语言:中文
  • 分类:X832[环境科学与工程—环境工程] S152.7[农业科学—土壤学;农业科学—农业基础科学]
  • 作者机构:[1]中国科学院遥感应用研究所遥感科学国家重点实验室,北京100101, [2]北京师范大学资源学院,北京100875, [3]中国科学院南京地理与湖泊研究所,南京210008
  • 相关基金:中国科学院知识创新工程重要方向项目(KZCX2-YW-313,KZCX3-SW-338)、国家自然科学基金重点项目(40730525)和国家自然科学基金项目(40671138)联合资助.
  • 相关项目:浅水湖泊中底质对遥感反射比的贡献——以太湖为试验区
中文摘要:

内陆水体叶绿素a浓度定量反演是水质遥感的热点与难点.本文基于对内陆水体叶绿素a、悬浮物、溶解有机物与水分子的光谱特征分析,从半分析生物光学模型出发,利用太湖实测的水面ASD高光谱遥感数据三波段组合,进行迭代优化,得到与叶绿素浓度密切相关而受悬浮物与黄色物质影响小的最优波段组合模型,反演精度较高,其决定系数和均方根误差分别为0.8358、3.816mg/m^3,该方法可以有效地反演高浓度悬浮物主导光学特性的水体叶绿素a浓度.

英文摘要:

Inversion of phytoplankton chlorophyll-a concentration of inland water body is hotspot and difficulty problem in water quality remote sensing. This paper provides a method to resolve this problem. Basing on the characteristic spectral analysis of chlorophyll-a, suspended matter, chromatic dissolved inorganic matter and pure water molecule in inland water body, the three-band model was spectrally tuned in accord with optical properties of Lake Taihu to optimize spectral bands combination for accurate chlorophyll-a concentration estimation. The remarkable linear relationship was established between analytically measured chlorophyll-a concentration and the three-band model. Depended on the favorable theory basis of the model developed, this method achieved good result with high determination coefficient 0.8358 and low root-mean-square error (3.816 mg/m^3), which was proved to be an useful tool to retrieval chlorophyll-a concentration in very turbid, hyper-eutrophic inland waters.

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