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Title:
渤海表面非光学活性水质参数MODIS遥感定量反演技术研究
Author: 于祥1,2
Degree Level: 博士
Issued Date: 2017-05
Degree Grantor: 中国科学院大学
Place of Degree Grantor: 北京
Supervisor: 刘欣
Keyword: 渤海,非光学活性水质参数,遥感定量反演,MODIS
Abstract: 渤海作为中国最北部的内海,受环渤海经济圈的发展影响,陆源污染物的输入造成海洋生态环境恶化,富营养化程度严重,赤潮等灾害频发,迫切需要获取宏观准确、周期性和时效性强的水质监测数据来了解渤海海水环境及其变化状况。传统的水文观测站、出海船舶实地测量方法,投入产出比低,受自然环境和天气状况等多种因素影响制约,无法获取大范围、周期性的观测数据,而遥感监测技术具有宏观性、时效性和周期性强等优势,且可提供多种格式的不同时间分辨率、空间分辨率、光谱分辨率和辐射分辨率的海洋观测数据,为海洋水质环境监测和保护提供了海量的数据支持,目前,海洋遥感发展迅猛,已形成了完整系统的海洋监测体系,在海洋物理遥感和海洋水色遥感方面已取得了很多成就。
本文针对目前海洋水质参数定量遥感集中于叶绿素、温度和黄色物质等光学活性水质参数,而对非光学活性水质参数研究很少的现状,依据出海航次调查数据和采集水样实验室测定数据,选取了营养盐浓度、碳组分浓度和盐度为研究对象,以遥感定量反演为目标,通过分析三类非光学活性水质参数的遥感反演机理,尝试建立营养盐浓度、碳组分浓度和盐度非光学活性水质参数定量反演模型,并对建成的反演模型在长时间序列上的适用性进行了分析和评价。
本文的主要研究内容为:(1)建立非光学活性水质参数遥感定量反演数据集。对出海航次采集水样进行实验室分析,获取其营养盐浓度、碳组分浓度和黄色物质(CDOM)浓度,利用ENVI遥感图像处理软件对下载MODIS遥感图像数据进行预处理,提取与出海航次时间上匹配的采样站位海水遥感反射率数据,建立营养盐浓度、碳组分浓度和盐度遥感定量反演数据集。(2)探索非光学活性水质参数遥感定量反演机理。分析非光学活性水质参数与MODIS波段反射率的相关性,探讨直接法在非光学活性水质参数遥感定量反演中的适用性;分析营养盐浓度与浊度之间、碳组分浓度与CDOM浓度之间、盐度与CDOM之间的相关性,探讨间接法在非光学活性水质参数遥感定量反演中的适用性;明确三类非光学活性水质参数遥感定量反演机理,设立合理的建模方案。(3)非光学活性水质参数遥感定量模型建立、精度验证和适用性评价。分析遥感反射率与实测反射率之间的等价关系,建立等价比值变量,利用与不同的非光学活性水质参数显著相关的波段比值,以多元逐步回归模拟反演不同营养盐浓度和不同碳组分浓度,以单变量回归模拟反演盐度,以独立数据集对反演模型进行精度验证,评价反演模型在长时间序列上的适用性。
研究结果表明:(1)渤海表面不同营养盐浓度与MODIS不同波段反射率之间相关性不同,差异明显,且相关性显著水平不足以建立稳健的定量反演模型;基于等价变换的遥感波段比值与营养盐浓度相关性显著性水平足够高,适用于渤海的营养盐浓度遥感定量反演;基于直接法和多元逐步回归拟合的渤海全区建模反演与渤海分区建模反演结果相似,即无论是渤海全区建模反演还是渤海分区建模反演,硝态氮和总无机氮总体反演精度均比较高,亚硝态氮、铵态氮和磷酸盐反演精度总体均比较低。(2)莱州湾表面不同碳组分浓度与MODIS不同波段反射率之间相关性不同,差异明显,且相关性显著水平不足以建立稳健的定量反演模型;基于等价变换的遥感波段比值与碳组分浓度相关性显著,适用于莱州湾的碳组分浓度遥感定量反演;基于直接法和多元逐步回归拟合的莱州湾碳组分浓度定量反演的精度很高,反演结果与事实相符。(3)渤海表面盐度与MODIS不同波段反射率之间相关性显著水平不足以建立稳健的定量反演模型;因渤海表面盐度与光学活性水质参数CDOM之间呈显著负相关关系,以CDOM为中间变量,利用间接法和单变量回归拟合进行渤海表面盐度反演的精度很高,反演算法简单直观,稳定性强,反演精度结果与事实相符,且适用于长时间序列的遥感定量反演。
本文的创新点主要表现在两个方面:(1)基于遥感反射率与实测反射率之间的等价关系,发展了遥感等价波段比值变量,解决了无实测海水光谱数据的问题,提高了建模精度。(2)探索了渤海表面营养盐浓度、碳组分浓度和盐度遥感定量反演机理,验证了三类非光学活性水质参数遥感定量反演的可行性。
综上所述,本研究从营养盐浓度、碳组分浓度和盐度三类非光学活性水质参数遥感定量反演机理分析出发,基于出海航次实测数据和水样实验室测定数据的分析处理,结合遥感图像处理流程,建立非光学活性水质参数遥感定量反演数据集,分析非光学活性水质参数与遥感波段反射率和波段比值之间的相关性,探索适用于不同水质参数的反演机理,设立合理可靠的定量反演方案,并对建成反演模型进行了适用性分析。研究结果可为完善海洋非光学活性水质参数遥感定量反演提供重要的科学依据,研究思路和方法可为以后相关研究提供支持。
 
English Abstract: The Chinese Bohai Sea, which located in the north of China, suffers from the development of the Bohai Economic Circle of China. Terrigenous input of pollutants induces marine ecological environment deterioration, serious eutrophication, red tides and other severe environment problems. A new monitoring technology is essential to gain accurate and cyclical seawater quality monitoring data. The current in situ techniques for measuring and monitoring seawater quality are time-consuming with a low input and output ratio. In situ measureent suffers from severe natural environment and bad weather conditions, and do not provide a synoptic view of a water body across the landscape. Fortunately, remote sensing provides the potential of gaining spatial and temporal coverage needed for seawater quality monitoring with the advantages of wide survey and frequent monitoring. It provides huge amounts data of multi-format with various resolutions. The marine remote sensing have developed rapidly, and formed a complete system of marine monitoring till now. A lot of achievements have been gained in the research area of marine physical remote sensing and ocean color remote sensing.
Remote sensing had been generally used to monitor seawater quality parameters, like temperature, chlorophyll-a, total suspended solids and colored dissolved organic matter (CDOM), etc. However, most of the remote sensing retrievals of water quality have focused on the indicators which have clearly characteristic wavelengths. Few studies have focused on non-optically active water quality parameters whose characteristic wavelengths remain controversial. This study attempted to carry out an experiment and test whether nutrients, carbon fractions and salinity can be potentially estimated by using remotely sensed data in the Chinese Bohai Sea. The objectives of this study were as follows: (1) to explore the retrieval mechanism of non-optically active water quality parameters based on remote sensing; (2) to develop inverse models to estimate non-optically active water quality parameters with sensitive remotely sensed variables; (3) to map the spatial distributions of non-optically active water quality parameters in the Chinese Bohai Sea with MODIS images, and (4) to evaluate the robustness of the developed retrieval models.
The main research content of this article was as follows: (1) to develop remote sensing inversion data set for non-optically active water quality parameters. The concentrations of nutrients, carbon fractions and colored dissolved organic matter (CDOM), were determined by laboratory analysis. The downloaded MODIS images were preprocessed by ENVI to seawater remote sensing reflectance of the sampling plots; (2) to explore the quantitative remote sensing inversion mechanisms for the non-optically active water quality parameters. The utility of direct method was evaluated based on the correlations between the MODIS reflectance of the sampling plots and the non-optically active water quality parameters concentrations. The utility of indirect method was evaluated based on the correlations between the nutrition concentrations and turbility, the carbon fraction concentrations and CDOM and the salinity and CDOM. Reasonable modeling scheme were selected based on the different inversion mechanisms for the three types of non-optically active water quality parameters; (3) to develop and validate the inversion models for the three types of non-optically active water quality parameters, and to evaluate the robustness of the developed models. The equivalence ratio variables were developed based on the equivalence relation between the remotely sensed data and the measured reflectance of the sampling plots. The inversion models of nutritions and carbon fractions were gained by multiple stepwise regression. However, the inversion models of salinity was gained by single variable regression. All the developed models were validated based on different independent data sets and the robustness of these models were also evaluated.
The yielded results showed that: (1) the correlations between different nutrient concentrations and MODIS reflectances were obviously different. The band ratios, which were developed based on the equivalent relation between the remotely sensed reflectance and the measured reflectance, meet the absence of the measured reflectance. The band ratios highlighted the reflectiviy difference of different bands, and improved the modeling accuracies; (2) the whole modeling inversion and the partition modeling inversion accuracy was roughly the same. The inversion accuracies of nitrate nitrogen and total dissolved inorganic nitrogen were higher than nitrate nitrogen, ammonium nitrogen and phosphate; (3) some equivalent band ratios were highly related to carbon fraction concentrations in the Laizhou Bay. The carbon fractions retrieval models were developed and validated, and the yielded results were reasonable; (4) the measured salinity was significantly related to CDOM. The salinity retrieval model was developed by using CDOM as proxy, and the yielded results were in accord with the fact. The developed retrieval model was credited as robustness and could be extended to map salinity during 2010 – 2014.
Characteristics and innovations of this paper were as follows: (1) several remote sensing equivalent band ratios were developed based on the the equivalent relation between the remotely sensed reflectance and the measured reflectance; (2) the inversion mechanism of three types of non-optically active water quality parameters were explored and remote sensing quantitative retrieval of three types of non-optically active water quality parameters were confirmed.
In conclusion, the study analyzed the inversion mechanism of the gived non-optically active water quality parameters based on the analysis of data acquisition and processing. Reasonable modeling schemes were operated in modelling, and the feasibility of non-optically active water quality parameters retrievals was confirmed. The yielded results provided scientific basis for remote sensing quantitative retrieval of non-optically active seawater quality parameters. In addition, the research ideas and methods provide support for future study in this area.
 
Content Type: 学位论文
URI: http://ir.yic.ac.cn/handle/133337/22010
Appears in Collections:中科院烟台海岸带研究所知识产出_学位论文

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description.institution: 1.中国科学院烟台海岸带研究所
2.中国科学院大学

Recommended Citation:
于祥. 渤海表面非光学活性水质参数MODIS遥感定量反演技术研究[D]. 北京. 中国科学院大学. 2017.
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