典型内陆水体有色可溶性有机物遥感反演
发布时间：2018-10-13 19:18
【摘要】：有色溶解有机物(Chromophoric Dissolved Organic Matter,简称CDOM),也称黄色物质(Yellow Substance),是一类广泛分布于自然水体中的溶解有机物,是一种重要的水质参数,与悬浮物、浮游植物同属于水色遥感的主要研究对象。遥感技术的应用促进了大尺度时间和空间范围的水环境变化研究的开展。相对于悬浮物和叶绿素a这两种水质参数而言,CDOM的遥感反演研究相对较少,并且研究区多是选择光学性质较简单的海洋水体。光学性质较复杂的近海和内陆水体CDOM的遥感反演研究相对较少。本文选取官厅水库和太湖两个典型内陆水体为研究区,以CDOM的吸收系数为浓度指标,开展CDOM遥感反演研究。本文的主要创新点如下:(1)结合QAA_V4、QAA_V5两个QAA改进版本和QAA-CDOM方法,创新性的提出了QAA(V4)-CDOM,QAA(V5)-CDOM两个方法,用于CDOM遥感反演。(2)依据光谱特征将太湖和官厅水库水面光谱数据分为两类,分别用QAA(V4)-CDOM和QAA(V5)-CDOM方法反演。在一定程度上解决了反演方法的季节性和区域性的限制。本文的主要内容及结论如下:(1)本文用QAA-CDOM、QAA-E、董强提出的方法(本文中称其为QAA-FOC)以及本文提出的QAA(V4)-CDOM,QAA(V5)-CDOM方法,共五种半解析方法用于CDOM反演。确定了官厅水库用QAA(V4)-CDOM方法反演效果最好。对于太湖,QAA(V5)-CDOM方法反演结果精度最好,但仍有待提高。最终对太湖220个采样点光谱数据分为了V4、V5两类,分别用QAA(V4)-CDOM和QAA(V5)-CDOM方法进行反演。分类反演后,较分类前反演精度得到了提升。(2)按照同样的方法,对官厅水库的60个采样点进行分类。综合官厅水库和太湖两个研究区,分析两类数据任两个波段比值与CDOM的相关性及高光谱数据的波段设置后,分别选定用Rrs(665)/Rrs(443)和Rrs(620)/Rrs(443)两个波段比值,建立了基于水面光谱数据的经验反演模型,反演结果的平均相对误差分别为12.1%和18.8%,均方根误差RMSE分别为0.157 m-1和0.192 m-1。(3)分别按季节、研究区和V4、V5类,分别逐波段分析了遥感反射率和CDOM的相关性,并建立了相应的单波段CDOM反演经验模型。结果显示,单个研究区春季和冬季的模型表现最好。夏季和秋季由于受浮游植物的干扰,反演效果不理想。综合了不同研究区和不同季节的数据的反演模型效果不理想。由于水体区域性、季节性的差异影响,用单一波段建立模型反演CDOM是很困难的。(4)将分类反演的半解析方法和分类建立的基于波段比值的经验反演模型,应用于官厅水库CHRIS和太湖MERIS高光谱数据的CDOM反演。官厅水库没有同步实测数据进行反演精度评定,仅对比了半解析方法和经验方法反演的结果,两种方法的反演结果分布规律统一。太湖有75个准同步点,用于精度检验,检验结果显示,反演结果精度尚可。太湖五次实验覆盖了春夏秋冬四个季节,其中春、冬两个季节反演结果较好,夏、秋两个季节反演结果精度仍有待提升。
[Abstract]:(Chromophoric Dissolved Organic Matter, also called yellow substance (Yellow Substance), is a kind of dissolved organic matter widely distributed in natural water. It is an important water quality parameter, and also belongs to the main research object of water color remote sensing along with suspended substance and phytoplankton. The application of remote sensing technology promotes the research of water environment change in time and space. Compared with the suspended solids and chlorophyll a, the remote sensing inversion of CDOM is relatively few, and the study area is mostly ocean water with simple optical properties. Remote sensing inversion of CDOM in offshore and inland waters with complex optical properties is relatively rare. In this paper, two typical inland water bodies of Guanting Reservoir and Taihu Lake are selected as the study areas, and the absorption coefficient of CDOM is taken as the concentration index to carry out the CDOM remote sensing inversion study. The main innovations of this paper are as follows: (1) combining the two improved versions of QAA and QAA-CDOM method of QAA_V4,QAA_V5, two methods of QAA (V4) -CDOM,QAA (V5) -CDOM are innovatively proposed for CDOM remote sensing inversion. (2) according to the spectral characteristics, the spectral data of Taihu Lake and Guanting Reservoir are classified into two categories. QAA (V 4)-CDOM and QAA (V 5)-CDOM methods were used to inverse. To some extent, the seasonal and regional limitations of the inversion method are solved. The main contents and conclusions of this paper are as follows: (1) in this paper, five semi-analytical methods are used for CDOM inversion using the method proposed by QAA-CDOM,QAA-E, Dong Qiang (referred to in this paper as QAA-FOC) and the QAA (V4) -CDOM,QAA (V5) -CDOM method proposed in this paper. It is determined that QAA (V 4)-CDOM method is the best inversion method for Guanting Reservoir. For Taihu Lake, QAA (V 5)-CDOM method has the best inversion accuracy, but it still needs to be improved. Finally, the spectral data of 220 sampling points in Taihu Lake are divided into two categories: V4 (V4)-CDOM and QAA (V5)-CDOM. The data are retrieved by QAA (V4)-CDOM and QAA (V5)-CDOM respectively. After classified inversion, the accuracy of inversion is improved. (2) according to the same method, 60 sampling points in Guanting Reservoir are classified. After analyzing the correlation between the ratio of two bands and CDOM and the band setting of hyperspectral data in Guanting Reservoir and Taihu Lake, the ratios of Rrs (665) / Rrs (443) and Rrs (620) / Rrs (443) were selected. An empirical inversion model based on water surface spectral data is established. The average relative error of the inversion results is 12.1% and 18.8% respectively, and the root mean square error (RMSE) is 0.157 m-1 and 0.192 m ~ (-1) respectively. (3) according to season, study area and V _ 4 / V _ 5, respectively, The correlation between remote sensing reflectivity and CDOM is analyzed, and the corresponding empirical model of single band CDOM inversion is established. The results showed that the model performed best in spring and winter. Because of phytoplankton interference in summer and autumn, the inversion effect is not ideal. The inversion model which synthesizes the data of different research areas and different seasons is not satisfactory. Because of the influence of regional and seasonal differences of water body, it is difficult to establish a model for inversion of CDOM by using a single band model. (4) the semi-analytical method of classification inversion and the empirical inversion model based on band ratio are established. It is applied to CDOM inversion of CHRIS and MERIS hyperspectral data of Guanting Reservoir. The inversion accuracy of Guanting Reservoir is evaluated without synchronous measured data. Only the semi-analytical method and the empirical method are compared. The distribution of the inversion results of the two methods is uniform. There are 75 quasi-synchronous points in Taihu Lake, which are used for accuracy test. The five experiments of Taihu Lake cover four seasons of spring, summer, autumn and winter, among which the inversion results of spring and winter are better, and the accuracy of inversion results in summer and autumn still need to be improved.
【学位授予单位】：西安科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X87
本文编号：2269649
[Abstract]:(Chromophoric Dissolved Organic Matter, also called yellow substance (Yellow Substance), is a kind of dissolved organic matter widely distributed in natural water. It is an important water quality parameter, and also belongs to the main research object of water color remote sensing along with suspended substance and phytoplankton. The application of remote sensing technology promotes the research of water environment change in time and space. Compared with the suspended solids and chlorophyll a, the remote sensing inversion of CDOM is relatively few, and the study area is mostly ocean water with simple optical properties. Remote sensing inversion of CDOM in offshore and inland waters with complex optical properties is relatively rare. In this paper, two typical inland water bodies of Guanting Reservoir and Taihu Lake are selected as the study areas, and the absorption coefficient of CDOM is taken as the concentration index to carry out the CDOM remote sensing inversion study. The main innovations of this paper are as follows: (1) combining the two improved versions of QAA and QAA-CDOM method of QAA_V4,QAA_V5, two methods of QAA (V4) -CDOM,QAA (V5) -CDOM are innovatively proposed for CDOM remote sensing inversion. (2) according to the spectral characteristics, the spectral data of Taihu Lake and Guanting Reservoir are classified into two categories. QAA (V 4)-CDOM and QAA (V 5)-CDOM methods were used to inverse. To some extent, the seasonal and regional limitations of the inversion method are solved. The main contents and conclusions of this paper are as follows: (1) in this paper, five semi-analytical methods are used for CDOM inversion using the method proposed by QAA-CDOM,QAA-E, Dong Qiang (referred to in this paper as QAA-FOC) and the QAA (V4) -CDOM,QAA (V5) -CDOM method proposed in this paper. It is determined that QAA (V 4)-CDOM method is the best inversion method for Guanting Reservoir. For Taihu Lake, QAA (V 5)-CDOM method has the best inversion accuracy, but it still needs to be improved. Finally, the spectral data of 220 sampling points in Taihu Lake are divided into two categories: V4 (V4)-CDOM and QAA (V5)-CDOM. The data are retrieved by QAA (V4)-CDOM and QAA (V5)-CDOM respectively. After classified inversion, the accuracy of inversion is improved. (2) according to the same method, 60 sampling points in Guanting Reservoir are classified. After analyzing the correlation between the ratio of two bands and CDOM and the band setting of hyperspectral data in Guanting Reservoir and Taihu Lake, the ratios of Rrs (665) / Rrs (443) and Rrs (620) / Rrs (443) were selected. An empirical inversion model based on water surface spectral data is established. The average relative error of the inversion results is 12.1% and 18.8% respectively, and the root mean square error (RMSE) is 0.157 m-1 and 0.192 m ~ (-1) respectively. (3) according to season, study area and V _ 4 / V _ 5, respectively, The correlation between remote sensing reflectivity and CDOM is analyzed, and the corresponding empirical model of single band CDOM inversion is established. The results showed that the model performed best in spring and winter. Because of phytoplankton interference in summer and autumn, the inversion effect is not ideal. The inversion model which synthesizes the data of different research areas and different seasons is not satisfactory. Because of the influence of regional and seasonal differences of water body, it is difficult to establish a model for inversion of CDOM by using a single band model. (4) the semi-analytical method of classification inversion and the empirical inversion model based on band ratio are established. It is applied to CDOM inversion of CHRIS and MERIS hyperspectral data of Guanting Reservoir. The inversion accuracy of Guanting Reservoir is evaluated without synchronous measured data. Only the semi-analytical method and the empirical method are compared. The distribution of the inversion results of the two methods is uniform. There are 75 quasi-synchronous points in Taihu Lake, which are used for accuracy test. The five experiments of Taihu Lake cover four seasons of spring, summer, autumn and winter, among which the inversion results of spring and winter are better, and the accuracy of inversion results in summer and autumn still need to be improved.
【学位授予单位】：西安科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X87
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