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胡耀躲, 窦同宇, 杨 波.基于GOCI影像反演湖泊悬浮物和叶绿素a含量的研究述评水资源与水工程学报[J].,2017,28(2):26-32
基于GOCI影像反演湖泊悬浮物和叶绿素a含量的研究述评
A review of research on retrieving the concentration of suspended particulate matter and chlorophyll a in lake based on GOCI images
  
DOI:10.11705/j.issn.1672-643X.2017.02.05
中文关键词:  湖泊  GOCI影像  反演  叶绿素a  悬浮颗粒物
英文关键词:lake  GOCI(Geostationary Ocean Color Imager)  retrieving  Chlorophyll a  suspended particulate matter
基金项目:国家自然科学基金项目(41171342、41325001); 湖南省水利厅专项项目
作者单位
胡耀躲, 窦同宇, 杨 波 (湖南师范大学 资源与环境科学学院 湖南 长沙 410006) 
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中文摘要:
      悬浮颗粒物和叶绿素a是两个重要的湖泊水质参数,常用来衡量湖泊的富营养化程度。阐述了基于GOCI数据的湖泊悬浮颗粒物和叶绿素a浓度反演的研究现状,分析了几种大气校正方法对于GOCI数据的适宜性,发现基于6S模型的大气校正取得的效果最好。对比了GOCI的几种用于叶绿素a和悬浮颗粒物反演的模型,发现基于经验方法的反演虽然简单易行,但缺乏物理依据;基于分析方法的反演机制明确,但较难实现;基于半分析方法的反演是统计水质参数的光谱特征,建立遥感数据的波段组合与水质参数值之间的定量关系,进而估算水质参数含量,此方法较易实现且有一定物理意义。最后,通过总结现状,对利用GOCI反演水体指标的发展提出了一些自己的见解。
英文摘要:
      The suspended particulate matter and chlorophyll-a, two important parameters of lake water quality, are often used to measure lake eutrophication extent. This paper introduced the research progress of estimating the concentration of suspended particulate matter and chlorophyll-a in lakes based on GOCI images, analyzed the suitability of several atmospheric correction methods for GOCI data, and found that the atmospheric correction based on 6S model had the best effect. Several inversion models of GOCI for chlorophyll a and suspended particulate matter were compared. The results showed that the inversion based on empirical method was simple and easy to implement, but it was lack of physical basis; the inversion based on the analysis method had clear mechanism , but was difficult to realize; the inversion based on semi-analysis method was to do the statistics for the spectral features of water quality parameters, to establish a quantitative relationship between water quality parameters and band combination of remote sensing data values, and then estimate the content of water quality parameters. This method was easy to realize and had certain physical meanings. Finally, the status quo was summarized and some own opinions about the development of the water indicators retrievals from GOCI data were put forward.
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