我国农村地区存在大量分散式水体，水体规模较小，流动性与自净能力较差，受周边环境因素的影响，极易形成“黑臭”水体。传统的监测方法难以准确捕捉这些黑臭水体，而卫星遥感技术具有监测范围广、精度高、速度快的优势，已经在水生生态保护、水体污染控制与治理、水环境灾害监测和预警等方面得到广泛应用。随着高分遥感技术的发展，大量的高空间分辨率遥感数据为分散式黑臭水体的识别与监测提供了有力的数据保障。

基于此，本文以东营市农村黑臭水体为研究对象，利用野外实测水体数据和多源高分遥感影像数据，分析了分散式黑臭水体与一般水体的水质参数差异及遥感反射率差异，构建了基于特征波段组合（NDBWI指数、DBWI指数、SBWI指数）、饱和度指标和色度指标的黑臭水体遥感识别算法，对各种算法的识别精度与适用性进行分析，选择出DBWI指数法为最优算法，使用该方法对东营市进行农村黑臭水体遥感识别，得到东营市农村黑臭水体遥感识别清单与东营市各区县的农村黑臭水体空间分布图，继而分析了东营市农村黑臭水体的空间分布特征，总结了东营市农村黑臭水体的形成原因，并且有针对性地提出了治理措施。论文主要得出以下结论：

（1）分散式黑臭水体与正常水体的差异

在水质参数方面，分散式黑臭水体与一般水体在总氮浓度、硫化物浓度、溶解性有机碳浓度和无机悬浮物浓度这4个方面差异较大。其中，黑臭水体的总氮浓度均值比一般水体的高约1.7倍，黑臭水体的硫化物浓度均值是一般水体的4倍左右，黑臭水体中的溶解性有机碳浓度均值是一般水体均值的1.5倍，黑臭水体中的无机悬浮物浓度是一般水体的1.2倍左右。

在遥感反射率方面，分散式黑臭水体在400-900nm波段遥感反射率整体低于0.03sr^-1，和正常水体平均遥感反射率相差较大。分散式黑臭水体遥感反射率在550-700nm范围内整体走势平缓，虽然具有波动变化，但是峰谷不突出。可以利用567nm、630nm、676nm、695nm等特征波段组合，对黑臭水体与一般水体进行区分。

（2）分散式黑臭水体遥感识别算法建模及筛选

基于特征波段组合构建的归一化黑臭水体指数（NDBWI）、黑臭水体差值指数（DBWI）和黑臭水体斜率指数（SBWI）三种指数的划分阈值分别为0.17、0.0045和0.0023，基于饱和度指标算法和色度指标算法的划分阈值分别为0.11和9.7°。其中，黑臭水体差值指数（DBWI）对建模样点和验证样点的黑臭情况判断最为准确，具有最高的精度和适用性，是本研究的最优识别算法。

（3）东营市农村黑臭水体空间分布特征

整个东营市范围内，农村黑臭水体主要集中在西部和中部内陆地区，东部沿海地区相对较少。主要由于西部和中部地区河网水系较少，且农村数量与农村人口数量较多，农业污染与生活污染较为严重。从各区县的情况来看，广饶县农村水环境状况最好，污染程度最轻，黑臭水体总面积为814.7m²，仅占全市黑臭水体总面积的1.1%。主要由于广饶县的农村水环境保护与防治工作开展的较好；河口区的农村黑臭现象最严重，黑臭水体总面积为23030.2m²，占研究区内黑臭水体总面积的30.1%。主要由于畜禽养殖业污染和工业污染问题突出。

There are a large number of dispersed water bodies in rural areas of China. The water bodies are small in scale and poor in mobility and self-purification. Affected by surrounding environmental factors, black and odorous water bodies are easily formed. Traditional monitoring methods are difficult to accurately capture these black and odorous water bodies. Conversely, remote sensing technology has the advantages of wide monitoring range, high precision, and fast speed. It has been widely used in aquatic ecological protection, water pollution control and management, water environment disaster monitoring and early warning. With the development of high-resolution remote sensing technology, a large amount of high spatial resolution remote sensing data provides a powerful data guarantee for the identification and monitoring of dispersed black and odorous water bodies.

This study focused on the rural black and odorous water bodies in Dongying City. Based on the field measured water body data and multi-source high-resolution remote sensing image data, the study analyze the remote sensing reflectivity characteristics and water quality parameters of the rural black and odorous water bodies. It constructs the remote sensing recognition algorithm of black smelly water bodies based on the combination of characteristic band (NDBWI index, DBWI index, SBWI index), saturation and chromaticity index. And by analyzing the recognition accuracy and applicability of various algorithms, it selects the DBWI index method as the optimal algorithm. Applying this algorithm to identify rural black and odorous water bodies in Dongying City by remote sensing recognition, we can obtain the remote sensing recognition list of rural black and odorous water bodies in Dongying City and the spatial distribution map of rural black and odorous water bodies in each districts and counties of Dongying City. Following that, we analyzed the spatial distribution characteristics of rural black and odorous water bodies in Dongying City. The study mainly draws the following conclusions:

(1) Differences between dispersed black and odorous water bodies and general water bodies

In terms of water quality parameters, dispersed black and odorous water bodies differ from general water bodies in four aspects: total nitrogen concentration, sulfide concentration, dissolved organic carbon concentration and inorganic suspended matter concentration. Among them, the average total nitrogen concentration of black and odorous water bodies is about 1.7 times higher than that of general ones. The average sulfide concentration of black and odorous water bodies is about 4 times that of general ones. The concentration of inorganic suspended solids in black and odorous water bodies is about 1.2 times that of general ones.

As for remote sensing reflectance, the remote sensing reflectance value of dispersed black and odorous water in the 400-900nm band is lower than 0.03sr^-1 as a whole, which is quite different from the average remote sensing reflectance of general water bodies. The remote sensing reflectivity of rural black and odorous waters tends to be gentle in the range of 550-700nm. Although there are fluctuations, the peaks and valleys are not prominent. The combination of characteristic bands such as 567nm, 630nm, 676nm, and 695nm can be used to distinguish black and odorous water bodies from general water bodies.

(2) Modeling and screening of remote sensing recognition algorithm for dispersed black and odorous water

The division thresholds of NDBWI (Normalized Difference Black-odorous Water Index) based on the combination of characteristic bands, DBWI (Difference of Black-odorous Water Index) and SBWI (Slope of Black-odorous Water Index) are 0.17, 0.0045 and 0.0023. The division thresholds based on the saturation index algorithm and the chromaticity index algorithm are 0.11 and 9.7°. Among them, the DBWI (Difference of Black-odorous Water Index) is the most accurate and has the highest accuracy and applicability for judging the black odorous condition of the modeling and validation sample points, which is the optimal recognition algorithm in this study.

(3) Spatial distribution characteristics of rural black and odorous water bodies in Dongying City

Within the scope of Dongying City, rural black and odorous water bodies are mainly concentrated in the western and central inland areas, while the eastern coastal areas are relatively few, which mainly due to the fact that there are less river networks in the western and central regions, and the number of rural areas and rural populations are large, agricultural pollution and domestic pollution are more serious. Judging from the situation of various districts and counties, Guangrao County has the best rural water environment condition and the lightest pollution level, with a total area of 814.7m² of black odorous water bodies, accounting for only 1.1% black odorous water bodies in the city. The main reason is that the rural water environmental protection and prevention work in Guangrao County has been well carried out; the black and odor phenomenon in rural areas in Hekou District is the most serious, with a total area of 2,3030.2m², accounting for 30.1% black and odorous water bodies in the study area, which is mainly due to the prominent problems of livestock and poultry farming pollution and industrial pollution.