中国东部近岸海域光学遥感机理及其在全球变化中的应用
发布时间：2018-09-05 09:49
【摘要】：本文以渤黄东海为研究区域，以2003-2012年渤黄东海现场数据和NOMAD数据集为基础，深入地分析与探讨了渤黄东海浑浊水体大气校正模型、系数与散射系数反演模型、叶绿素a和悬浮物浓度反演模型、以及漫衰减系数反演模型；以1997-2013年SeaWiFS与MODIS卫星的月平均遥感反射率观测数据为基础，利用本文构建的遥感模型反演获得了全球海洋与渤黄东海关键生物光学要素时空信息，并系统性地探讨了渤黄东海关键生物光学要素遥感反演及时空变化。其主要结论如下： (1)构建了适用于渤黄东海复杂光学特性的高精度大气校正模型。一方面，基于交叉定标的短波红外大气校正模型利用了5×5窗口平均的方法，降低短波红外随机误差对遥感反射率反演精度的影响，同时利用短波红外和近红外波段交叉定标的方法，降低短波红外系统误差对遥感反射率反演精度的影响；另一方面，针对1240nm波段的黑体假设在非常浑浊的水体中失效，，本文利用线性模型修复了1640nm波段数据的条带，并构建了16402130nm波段组合的大气校正模型。结合实测遥感反射率数据可知，两种大气校正模型在遥感反射率精度方面较传感器短波红外大气校正模型具有很大的改进。 (2)构建了适用于渤黄东海海水漫衰减系数反演的半分析模型。本文利用二流辐射传输原理，构建了海水漫衰减系数与吸收系数和遥感反射率之间的关系，并结合双波段半分析方法，最终确定了海水漫衰减系数与遥感反射率之间的关系。通过与渤黄东海实测数据对比可知，该模型较传统模型精度提高了12%以上。 (3)构建了适用于渤黄东海悬浮物浓度、叶绿素a浓度、吸收与散射系数、及海水漫衰减系数等关键生物光学要素反演的高精度神经模型。本文利用分析方法构建生物光学要素反演的概念模型，然后利用神经网络技术拟合概念模型中输入和输出参数之间的关系。利用全球实测大数据集评估半分析与神经网络耦合模型的稳定性和可靠性可知，与传统神经网络模型和半分析模型比较，该模型在关键生物光学要素的反演方面具有更高的可靠性度，且适用的区域也更广。 (4)1997-2013年期间渤黄东海关键生物光学要素的时空变化趋势及其与全球变化的关系。受陆源和海陆相互作用的影响，各要素在渤黄东海呈近岸高，远岸地的分布格局。自1997年以来全球平均气温仍然以0.001℃mn-1速度升高，并导致全球海域叶绿素a浓度也逐年降低。作为全球海洋悬浮物的重要供给区域，渤黄东海叶绿素a与悬浮物浓度和全球叶绿素a和悬浮物浓度具有较高的时空相关性。
[Abstract]:Based on the field data and NOMAD data set from 2003 to 2012, the atmospheric correction model, the inversion model of coefficient and scattering coefficient of turbid water in the Bohai Sea, Yellow Sea and East China Sea are analyzed and discussed in this paper. Chlorophyll a and suspended matter concentration inversion models, as well as diffuse attenuation coefficient inversion models; based on monthly average remote sensing reflectance observations from SeaWiFS and MODIS satellites for 1997-2013, The spatiotemporal information of the key biological optical elements in the global ocean and the Bohai Sea and the Yellow Sea and the East China Sea are obtained by using the remote sensing model constructed in this paper. The remote sensing inversion and the temporal and spatial variations of the key biological optical elements in the Bohai Sea, the Yellow Sea and the East China Sea are systematically discussed. The main conclusions are as follows: (1) A high-precision atmospheric correction model for complex optical properties of the Bohai Sea, Yellow Sea and East China Sea is constructed. On the one hand, the short-wave infrared atmospheric correction model based on cross-calibration uses the method of 5 脳 5 window average to reduce the influence of the random error of short-wave infrared on the retrieval accuracy of remote sensing reflectivity. At the same time, the short-wave infrared and near-infrared band cross-calibration method is used to reduce the influence of the short-wave infrared system error on the precision of remote sensing reflectivity inversion. On the other hand, the blackbody hypothesis in 1240nm band is invalid in very cloudy water. In this paper, the linear model is used to repair the bands of 1640nm band data, and the atmospheric correction model of 16402130nm band combination is constructed. Combined with the measured data of remote sensing reflectivity, The two atmospheric correction models improve the precision of remote sensing reflectance greatly compared with the sensor short-wave infrared atmospheric correction model. (2) A semi-analytical model suitable for inversion of diffuse attenuation coefficient of sea water in the Bohai Sea, Yellow Sea and East China Sea is constructed. In this paper, the relationship between diffuse attenuation coefficient and absorption coefficient and remote sensing reflectivity of seawater is established by using the principle of two-stream radiation transfer. The relationship between diffuse attenuation coefficient and remote sensing reflectivity is finally determined with the method of two-band half-analysis. Compared with the measured data of the Bohai Sea, the Yellow Sea and the East China Sea, the accuracy of the model is improved by more than 12%. (3) the concentration of suspended matter, the concentration of chlorophyll a, the absorption and the scattering coefficient of suspended matter in the Bohai Sea, the Yellow Sea and the East China Sea are constructed. High precision neural model for inversion of key biological optical elements such as diffuse attenuation coefficient of seawater. In this paper, the analytical method is used to construct the conceptual model of bio-optical element inversion, and then the neural network technique is used to fit the relationship between the input and output parameters in the conceptual model. The stability and reliability of the coupling model of semi-analysis and neural network are evaluated by using the global measured big data set, which is compared with the traditional neural network model and the semi-analytical model. The model has a higher reliability in the inversion of key biological optical elements and has a wider range of applications. (4) the temporal and spatial trends of key biological optical elements in the Bohai Sea, the Yellow Sea and the East China Sea during 1997-2013 and their relationship with global changes. Influenced by the interaction between land source and sea and land, the distribution pattern of each element in the Bohai Sea, the Yellow Sea and the East China Sea is near shore high and far shore. Since 1997, the global average temperature has increased at the rate of 0.001 鈩
本文编号：2223919
[Abstract]:Based on the field data and NOMAD data set from 2003 to 2012, the atmospheric correction model, the inversion model of coefficient and scattering coefficient of turbid water in the Bohai Sea, Yellow Sea and East China Sea are analyzed and discussed in this paper. Chlorophyll a and suspended matter concentration inversion models, as well as diffuse attenuation coefficient inversion models; based on monthly average remote sensing reflectance observations from SeaWiFS and MODIS satellites for 1997-2013, The spatiotemporal information of the key biological optical elements in the global ocean and the Bohai Sea and the Yellow Sea and the East China Sea are obtained by using the remote sensing model constructed in this paper. The remote sensing inversion and the temporal and spatial variations of the key biological optical elements in the Bohai Sea, the Yellow Sea and the East China Sea are systematically discussed. The main conclusions are as follows: (1) A high-precision atmospheric correction model for complex optical properties of the Bohai Sea, Yellow Sea and East China Sea is constructed. On the one hand, the short-wave infrared atmospheric correction model based on cross-calibration uses the method of 5 脳 5 window average to reduce the influence of the random error of short-wave infrared on the retrieval accuracy of remote sensing reflectivity. At the same time, the short-wave infrared and near-infrared band cross-calibration method is used to reduce the influence of the short-wave infrared system error on the precision of remote sensing reflectivity inversion. On the other hand, the blackbody hypothesis in 1240nm band is invalid in very cloudy water. In this paper, the linear model is used to repair the bands of 1640nm band data, and the atmospheric correction model of 16402130nm band combination is constructed. Combined with the measured data of remote sensing reflectivity, The two atmospheric correction models improve the precision of remote sensing reflectance greatly compared with the sensor short-wave infrared atmospheric correction model. (2) A semi-analytical model suitable for inversion of diffuse attenuation coefficient of sea water in the Bohai Sea, Yellow Sea and East China Sea is constructed. In this paper, the relationship between diffuse attenuation coefficient and absorption coefficient and remote sensing reflectivity of seawater is established by using the principle of two-stream radiation transfer. The relationship between diffuse attenuation coefficient and remote sensing reflectivity is finally determined with the method of two-band half-analysis. Compared with the measured data of the Bohai Sea, the Yellow Sea and the East China Sea, the accuracy of the model is improved by more than 12%. (3) the concentration of suspended matter, the concentration of chlorophyll a, the absorption and the scattering coefficient of suspended matter in the Bohai Sea, the Yellow Sea and the East China Sea are constructed. High precision neural model for inversion of key biological optical elements such as diffuse attenuation coefficient of seawater. In this paper, the analytical method is used to construct the conceptual model of bio-optical element inversion, and then the neural network technique is used to fit the relationship between the input and output parameters in the conceptual model. The stability and reliability of the coupling model of semi-analysis and neural network are evaluated by using the global measured big data set, which is compared with the traditional neural network model and the semi-analytical model. The model has a higher reliability in the inversion of key biological optical elements and has a wider range of applications. (4) the temporal and spatial trends of key biological optical elements in the Bohai Sea, the Yellow Sea and the East China Sea during 1997-2013 and their relationship with global changes. Influenced by the interaction between land source and sea and land, the distribution pattern of each element in the Bohai Sea, the Yellow Sea and the East China Sea is near shore high and far shore. Since 1997, the global average temperature has increased at the rate of 0.001 鈩
本文编号：2223919
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