|Place of Conferral||中国科学院海洋研究所|
|Keyword||海阳 遥感反演 悬浮泥沙分布 图像融合|
本文选用2004-2017年不同时期的Landsat ETM+（Enhanced Thematic Mapper）/OLI(Operational Land Imager)影像，根据2014年海阳核电站附近多组同步实测数据，根据逐步回归分析法建立海阳海域表层悬浮泥沙浓度的多组经验反演模型，进行精度检验并对比分析悬浮泥沙的不同季节的年际分布特点。ETM+数据夏冬两季季反演模型精度分别为82%和77%，OLI数据反演模型的精度为86%，可以依据建立的模型分析研究区悬浮泥沙分布特征。
进一步结合GOCI（Geostationary Ocean Imager）数据，利用STARFM（Spatial and Temporal Adaptive Reflectance Fusion Model），生成OLI数据产品和GOCI数据产品的融合图像。GOCI原始数据反演精度为44%，融合图像将反演精度提升了到64%，该融合数据覆盖了研究区从高潮到低潮的完整变化，据此分析了研究区悬浮泥沙分布随潮流的变化结果。
Haiyang city, Shandong province, has made great efforts to develop the marine economy in recent years. Introducing a large number of industries with the help of the construction of Haiyang Harbor and Haiyang Nuclear Power Station, which are built near the sea. At the same time, the city develop the tourism and leisure vacation industry rely on the beautiful beach. However, the intensification of human activities will inevitably affect the change of suspended sediment in nearshore water, which will affect the environment. Secondly, the construction of the project will have a certain impact on the distribution of suspended sediment in the adjacent waters. Therefore, it is necessary to study the spatial and temporal distribution characteristics of suspended sediment in the sea area near Haiyang city. Remote sensing technology has unique advantages in marine environmental monitoring due to its characteristics of large span, long time, real-time synchronization and various scales. According to the characteristics of Haiyang sea area, the temporal and spatial distribution characteristics of suspended sediment in this area were studied by using remote sensing technology.
In this thesis, multiple inversion models of surface suspended sediment concentration are built by the measured data near Haiyang nuclear power plant in 2014. And theses creation processes are based on the stepwise regression analysis. Several sets of Landsat ETM+ (Enhanced Thematic Mapper) /OLI (Operational Land Imager) images during 2004-2017 were chosen to compare and analyze the spatial and temporal distribution pattern of suspended sediment based on these inversion models. The precision of the inversion model of ETM+ data in winter and summer is respectively 82% and 77%, and that of the OLI data inversion model is 86%, meeting the inversion requirements.
On the basis of GOCI (Geostationary Ocean Imager) data, the fusion images of OLI data products and GOCI data products were produced using STARFM (Spatial and Temporal Adaptive Reflectance Fusion Model). The original data inversion accuracy of GOCI is 44%, and the fusion image improves the inversion accuracy to 64%. The integrated data cover the whole change from high tide to low tide in the study area. The variation of suspended sediment distribution with tidal current is analyzed by the integrated data.
The results show that the distribution characteristics of suspended sediment in the study area are mainly influenced by both river sediment transport and marine dynamic conditions. Under the action of waves, the sediment in the Dingzi-bay was resuspended, which was transported along the tidal current, and the holistic trend was from west to east, which improved the overall suspended sediment concentration in the study area. At the same time, due to the change of seasonal weather conditions, the suspended sediment concentration in winter was higher than that in summer. However, from the perspective of long time series, the suspended sediment concentration in the study area is relatively stable before and after the construction, and the sea area in the study area has good stability. In a certain time span, remote sensing technology is used to carry out inversion analysis of suspended sediment distribution in the adjacent sea area of Haiyang city. Combined with image fusion technology and mathematical simulation results, the overall characteristics of the study area and the impact of human coastal engineering construction can be obtained, which better reveals the changes of the environment.
|王强. 基于遥感反演的海阳离岸海域悬浮泥沙时空分布特征研究[D]. 中国科学院海洋研究所. 中国科学院大学,2019.|
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