基于GOCI影像的长江口及其邻近海域CDOM遥感反演及其日内变化研究
发布时间：2019-04-22 19:41
【摘要】：采用静止轨道海洋水色卫星(GOCI)数据对长江口及其邻近海域有色溶解有机物(CDOM)反演。以QAA-CDOM算法为基础,根据实测数据,利用BP神经网络模型来拟合QAA-CDOM算法中需要针对长江口水体进行优化的悬浮颗粒后向散射系数bbp与吸收系数ap的关系,从而准确估算CDOM的浓度。结果表明,反演结果准确度较高,平均相对误差为0.35。基于GOCI日内连续成像的优势,选取2014年3月15日8景GOCI影像,利用优化后的QAA-CDOM-BP算法,对长江口及其邻近海域CDOM的日内变化进行反演和分析,得到的变化规律如下:长江口及其邻近海域的CDOM日变化主要受潮流、长江径流等共同影响。长江口内CDOM浓度在涨潮期高于退潮期,由于受长江冲淡水的作用,CDOM从口外往外海区呈现逐渐递减趋势。
[Abstract]:The geostationary orbit ocean color satellite (GOCI) data are used to retrieve the colored dissolved organic matter (CDOM) in the Yangtze Estuary and its adjacent waters. Based on the QAA-CDOM algorithm and according to the measured data, the BP neural network model is used to fit the relationship between the backscattering coefficient (bbp) and the absorption coefficient (ap) of suspended particles which need to be optimized for the Yangtze Estuary water body in the QAA-CDOM algorithm. Thus, the concentration of CDOM is estimated accurately. The results show that the accuracy of the inversion results is high, and the average relative error is 0.35. Based on the advantage of GOCI intraday continuous imaging, 8 GOCI images of March 15, 2014 were selected, and the intra-day variation of CDOM in the Yangtze Estuary and its adjacent waters was inversed and analyzed by using the optimized QAA-CDOM-BP algorithm. The rule of variation is as follows: the daily variation of CDOM in the Yangtze Estuary and its adjacent waters is mainly influenced by tidal current and runoff of the Yangtze River. The concentration of CDOM in the estuary of the Yangtze River is higher than that in the ebb stage. Due to the effect of the fresh water from the Yangtze River, the concentration of CDOM decreases gradually from the mouth to the outer sea area.
【作者单位】： 浙江大学海洋学院海岛海岸带研究所;
【基金】：国家自然科学基金面上项目(41471346) 国家自然科学青年基金项目(41401404) 海洋公益性行业科研专项经费项目(201005030-06)
【分类号】：P715.7;P734
[Abstract]:The geostationary orbit ocean color satellite (GOCI) data are used to retrieve the colored dissolved organic matter (CDOM) in the Yangtze Estuary and its adjacent waters. Based on the QAA-CDOM algorithm and according to the measured data, the BP neural network model is used to fit the relationship between the backscattering coefficient (bbp) and the absorption coefficient (ap) of suspended particles which need to be optimized for the Yangtze Estuary water body in the QAA-CDOM algorithm. Thus, the concentration of CDOM is estimated accurately. The results show that the accuracy of the inversion results is high, and the average relative error is 0.35. Based on the advantage of GOCI intraday continuous imaging, 8 GOCI images of March 15, 2014 were selected, and the intra-day variation of CDOM in the Yangtze Estuary and its adjacent waters was inversed and analyzed by using the optimized QAA-CDOM-BP algorithm. The rule of variation is as follows: the daily variation of CDOM in the Yangtze Estuary and its adjacent waters is mainly influenced by tidal current and runoff of the Yangtze River. The concentration of CDOM in the estuary of the Yangtze River is higher than that in the ebb stage. Due to the effect of the fresh water from the Yangtze River, the concentration of CDOM decreases gradually from the mouth to the outer sea area.
【作者单位】： 浙江大学海洋学院海岛海岸带研究所;
【基金】：国家自然科学基金面上项目(41471346) 国家自然科学青年基金项目(41401404) 海洋公益性行业科研专项经费项目(201005030-06)
【分类号】：P715.7;P734
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