中国科学院遥感与数字地球研究所-高光谱遥感应用技术研究室

【作者】             李俊生                                                                                                                                              

【导师】             童庆禧；张兵；郑兰芬

【 学位年度 】    2007

【论文级别】      博士    

【关键词】          高光谱遥感，分析方法，太湖，表观光学量，固有光学量  

【Key words】   hyperspectral remote sensing; Taihu; analytical approach; apparent optical properties; inherent optical properties 

【中文摘要】    

随着内陆水质污染的日益严重，水质监测工作已经刻不容缓。遥感监测内陆水质具有监测范围广、速度快、成本低、便于长期动态监测等优势。但是，与海洋水色遥感相比，内陆水质遥感无论在专用遥感器的研发还是在算法模型的研究方面都明显落后。目前内陆水质遥感监测中经常使用的宽波段多光谱遥感数据无法精确捕捉内陆水体复杂多变的光谱特征，水质监测的精度往往不高。高光谱遥感技术的发展为内陆水质遥感监测带来了契机，同时也对传统的内陆水质监测方法提出了挑战。目前内陆水质遥感监测中经常使用的经验/半经验方法稳定性和普适性差，难以在不同区域和不同季节推广。而基于生物光学模型的分析方法具有明确的物理意义，结果更可靠，适用性更好。因此，研究基于高光谱遥感数据的内陆水质参数反演分析方法具有非常重要的意义。

        本文以太湖为研究区，在获取了四个季节的试验数据的基础上，开展了五个方面的研究工作：水体固有光学量测量及其时空分布规律分析、水体表观光学量测量及其光谱特征分析、生物光学模型和固有光学量反演、水质参数反演分析方法建立和检验、水质参数的高光谱遥感图像反演和填图。

        本文主要取得的研究成果是：分析了太湖水体固有光学量和单位固有光学量的时空分布规律，在此基础上构建了单位固有光学量数据库；定义了四种光谱指数，并基于这四种光谱指数建立了水草和水华的判别算法；建立了一种基于生物光学模型的计算悬浮物后向散射系数的非线性优化方法；在矩阵反演方法的理论基础上，推导了基于单位固有光学量数据库的非线性优化方法和代数方法，然后利用太湖四次试验数据进行了检验，结果表明叶绿素和悬浮物的反演结果比较好，对于太湖不同季节的遥感数据，悬浮物和叶绿素的最佳反演方法是不同的，而且反演方法中使用的最佳的波段组合也是不同的；设计了高光谱遥感图像反演内陆水质参数的流程图，建立了基于大气辐射传输模型6S的遥感反射率计算方法，利用航天高光谱遥感器CHRIS数据检验了本文建立的分析方法，获得了较好的结果。

       本文的这些研究成果为利用高光谱遥感数据监测内陆水质提供了机理和方法上的支持。

【Abstract】

With the deterioration of inland water pollution, monitoring inland water quality is becoming urgent. Monitoring water quality by remote sensing technology has the advantages of rapidness, wide coverage, low cost, and dynamic monitoring over a long period of time. However, monitoring inland water quality by remote sensing is far behind ocean color remote sensing in both development of remote sensors and monitoring approaches. The multi-spectral remote sensing data, which are often used to monitor inland water quality, can not catch the complicated and changeful spectral characteristics of inland waters accurately. Therefore, the accuracy of water quality monitoring from multi-spectral remote sensing data is quite limited. The development of hyperspectral remote sensing technique has provided much opportunity in monitoring inland water quality. Meanwhile, it has also brought challenge to traditional approaches of monitoring inland water quality. Empirical and semi-empirical approaches, which are often used in monitoring inland water quality, have low robustness, and are hard to be applied to different seasons and areas. In contrast, analytical approaches are based on bio-optical model, and have the advantages of definite physical meanings, higher robustness, and wider applicability. Therefore, it is of great significance to carry out the study on retrieval of inland water quality parameters from hyperspectral remote sensing data by analytical approach.

      Taihu Lake is selected as study area in this dissertation. Based on the experiment data acquired in Taihu Lake in four seasons, five aspects of researches are accomplished: 1) measure inherent optical properties and analyze their temporal and spatial distributing rules; 2) measure apparent optical properties and analyze their spectral characteristics; 3) build bio-optical model and retrieve inherent optical properties; 4) set up and validate analytical approaches to retrieve water qualtiy parameters; 5) retrieve water qualtiy parameters from hyperspectral remote sensing image.

    Main contributions of this dissertation can be concluded as follows:

1. Temporal and spatial distributing rules of inherent optical properties and specific inherent optical properties are analyzed for Taihu Lake, and on this basis, a specific inherent optical properties database is build up;

2. Four kinds of spectral indices are defined to classify water grass and algal bloom;

3. A nonlinear optimized method based on bio-optical model is proposed to calculate backscattering coefficient of suspended matter;

4. Based on the theory of matrix inversion approach, nonlinear optimized approach and algebra approach are set up, which take specific inherent optical properties as input parameters;

5. The three kinds of approaches, which are matrix inversion approach, nonlinear optimized approach and algebra approach, are tested by the four times of experiment data. The results show that retrieval accuracy of chloroyphyll-a and suspended matter concentrations are fairly good. For different seasons, the approaches to get best retrieval accuaracy of chloroyphyll-a and suspended matter are commonly not the same, and the bands combinations used in the approaches are also not the same;

6. A flow chart of retrieving water quality parameters from hyperspectral remote sensing images is designed, and a approach to calculate remote sensing reflectance is set up based on atmospheric radiant transfer model 6S. One CHRIS image is employed to test the analytical approach propsed in this dissertation, and the results are quite reasonable.

      All the contributions of this dissertation have provided theoretical and methodological support in monitoring inland water quality from hyperspectral remote sensing data.