长江口最大浑浊带表层悬浮物浓度及粒径对水体光谱特性影响的研究
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摘要
长江口及邻近海域的悬浮泥沙浓度、分布和输移变化已经成为研究长江流域入海物质通量、物质循环、河口沙洲变化以及评价流域工程对河口影响的核心指标和评估河口地区后备土地资源发展的重要参数,是学术界、政府和产业界均十分关注的问题。传统单点,多点船测只能提供短期局部数据,空间分布不足,重复周期观测成本高,而遥感数据在空间覆盖,时间周期覆盖方面具有重要优势,利用遥感监测悬沙浓度具有重要意义。
本文以长江口最大浑浊带为研究区域,主要开展了以下工作：
1)现场数据获取与处理：采用定点观测的方式,获取了三个不同时段悬沙水体的光谱数据,并处理成遥感反射率曲线；同步采集水体表层水样,在实验室内测量水样的泥沙浓度及粒径分布数据；利用LISST-100x同步测量水体絮凝体数据。
2)分析水体光谱反射率的基本特征及其与悬沙浓度之间的关系,从理论方面解释了可见光波段及近红外波段对悬沙浓度敏感性不同的原因。以MODIS波段为参考,建立多种光谱反射率同悬沙浓度之间回归方程。围绕统计模型的精度及可靠性问题,进行了不同波段参数,不同数学关系式形式,不同时段以及现有文献中他人所建的反演方程的比较。
3)分析了悬沙粒径对光谱反射率的影响,理论分析解释了悬沙粒径对光谱反射率的影响,并结合实测数据对基本结论进行了验证；利用现有文献中的数学关系式形式,建立了同时考虑悬沙浓度及粒径的回归方程。进一步考虑了自然水体中的絮凝现象,初步讨论了絮凝体对光谱特征造成的影响。
取得的主要结论如下：
(1)近红外波段反射率与悬浮泥沙浓度具有很好的相关性,因而可用于悬浮泥沙浓度反演。反演模式中,以单波段,两波段比值和多波段组合为形式的参数中波段比值法因能有效减弱其他条件的影响(如光照,粒径等)而表现最好；模型形式上,多项式模型对数据的拟合度最高,但与指数模型及幂函数模型之间相差不大,基本处于同一水平。
(2)通过本文中不同时段的数据对比以及同现有文献中涉及到长江口的悬浮泥沙遥感反演模型进行对比发现,不同研究者建立的模型相互之间具有可比性,尤其在低悬沙浓度条件下,模型几乎趋于一致,说明以统计模型为基础的遥感反演模型在时空应用上可做一定的拓展。加强数据的对比研究是提高对统计模型应用上的可靠性认知的有效方式。
(3)泥沙粒径与光谱分析具有一定的相关性,但不能简单依此判定就是粒径对光谱的影响,因为泥沙粒径本身和泥沙浓度具有较好的相关性,而后者与光谱之间有着更好的回归关系,而通过理论分析表明,泥沙粒径分布主要是通过影响后向散射来对光谱反射率产生影响,细颗粒泥沙具有较大的后向散射而粗颗粒泥沙则具有较小的后向散射。
(4)野外数据分析表明：细粒径泥沙会增大光谱反射率,与理论分析一致；根据两个不同时期的数据分别建立悬沙浓度与要反射率之间的回归关系比较发现,样品数据集中泥沙粒径分布变化越小,建立的统计回归模型的R2值越高,模型拟合度越好。
(5)对已有的加入悬沙浓度和粒径的回归模式进行了检验,基本上表明,在统计基础上的加入粒径参数无助于提高模型精度,反而导致精度的下降。
(6)絮凝体粒径分布对悬沙水体光谱反射特征有着重要的影响,但是在利用悬沙的平均粒径,中值粒径以及絮凝体平均粒径分析其与光谱反射率之间的关系时,难以定量化表达粒径对光谱的影响。在将絮凝体平均粒径纳入统计模型之后,同样会导致模型精度的下降。
Suspended sediment concentration, spatial distribution and its transportation in the Yangtze River Estuary have become core indicators and important parameters in the researches of material fluxes, Material Cycle, changes of estuarine shoals, evaluation the impact of watershed projects on the estuary mouth and assessment of land resources in the Estuary. This has drawn the attention of academic circles, government departments and industry as well. Traditional single-point, multi-point measurement on board can only provide short-term partial data, lack of spatial distribution data and has a high cost, while remote sensing has an important advantage of covering large area and repeating observation in monitoring suspended sediment concentration.
In this paper, following tasks were mainly carried out in the turbidity maximum area of Yangtze River Estuary:
1) Field data acquisition and processing:Three in situ observations were performed at same site in the South Passage to collect spectral data, and surface water samples synchronously to measure sediment concentration and size distribution data in the laboratory. LISST-100x was used to measure floc particles as well..
2) Analysis of the spectral reflectance characteristics above water surface and the relationship between suspended sediment concentration and the spectral reflectance. Giving theoretical explanation for the different sensitivity of the suspended sediment concentration at visible band and near infrared band. Using MODIS bands as a reference to establish several regression equations between spectral reflectance and suspended sediment concentration. Focus on the accuracy and reliability of statistical models, compares inversion equations with different band parameters and mathematical relationships of different forms at different times, and found by other researchers.
3) Analysis the impact of suspended sediment particle size on the spectral reflectance characteristics and giving theoretical explanation and drawing the basic conclusion by analysis the measured data. The regression equations between spectral reflectance, the suspended sediment concentration and particle size was established, using of the mathematical relationships in literature. Further more, the impact of flocs on spectral characteristics was also considered and discussed.
The primary conclusions obtained are as follows:
1) Spectral reflectance at Near-infrared band has a good relation with suspended sediment concentration, which can be used for suspended sediment concentration inversion. Two-band ratio can effectively reduce the influence of other conditions (such as illumination, size, etc.) compare to parameters such as single band, and multi-band combination. For the model mathematical formulas, the polynomial model fit the data best, but without any excellence comparing to the exponential model and power model.
2) Through comparison of suspended sediment concentration inversion models founded by data from different periods and in the existing literature, it is found that models founded by different researchers are comparable, especially in a certain range of low suspended sediment concentration value indicating the statistical model is reliable. Strengthen the comparative study on the statistical models is an effective way to improve cognition of the reliability of the application.
3) There is some correlation between sediment grain size and spectrum, but it cannot certify the impact of particle size on the spectrum, because sediment particle size has a good correlation with suspended sediment concentration which also has a high correlation with the spectrum. Theoretical analysis shows that sediment particle size distribution mainly through the effect of scattering to impact on the spectral reflectance; fine sediments have a stronger backscatter than coarse sediment.
4) Field data showed that fine particle size would increase the spectral reflectance which was consistent with the theoretical analysis. Comparison of regression models founded using data from two different periods, it was found that the smaller the particle size distribution changes, the higher value the regression model R2 got.
5) By establishing regression models regression equations between spectral reflectance, the suspended sediment concentration and particle size, it showed that it could not help to improve model accuracy when particle size was included as an parameter, but lead to a decline in accuracy.
6) Grain size distribution of flocs particles had an important impact on water spectrum but it was difficult to express the effect quantitatively, when analysis by using suspended sediment mean diameter, median diameter and flocs mean diameter. When establish regression models regression equations between spectral reflectance, the suspended sediment concentration and flocs mean diameter, it also led to a decline in accuracy.
本文以长江口最大浑浊带为研究区域,主要开展了以下工作：
1)现场数据获取与处理：采用定点观测的方式,获取了三个不同时段悬沙水体的光谱数据,并处理成遥感反射率曲线；同步采集水体表层水样,在实验室内测量水样的泥沙浓度及粒径分布数据；利用LISST-100x同步测量水体絮凝体数据。
2)分析水体光谱反射率的基本特征及其与悬沙浓度之间的关系,从理论方面解释了可见光波段及近红外波段对悬沙浓度敏感性不同的原因。以MODIS波段为参考,建立多种光谱反射率同悬沙浓度之间回归方程。围绕统计模型的精度及可靠性问题,进行了不同波段参数,不同数学关系式形式,不同时段以及现有文献中他人所建的反演方程的比较。
3)分析了悬沙粒径对光谱反射率的影响,理论分析解释了悬沙粒径对光谱反射率的影响,并结合实测数据对基本结论进行了验证；利用现有文献中的数学关系式形式,建立了同时考虑悬沙浓度及粒径的回归方程。进一步考虑了自然水体中的絮凝现象,初步讨论了絮凝体对光谱特征造成的影响。
取得的主要结论如下：
(1)近红外波段反射率与悬浮泥沙浓度具有很好的相关性,因而可用于悬浮泥沙浓度反演。反演模式中,以单波段,两波段比值和多波段组合为形式的参数中波段比值法因能有效减弱其他条件的影响(如光照,粒径等)而表现最好；模型形式上,多项式模型对数据的拟合度最高,但与指数模型及幂函数模型之间相差不大,基本处于同一水平。
(2)通过本文中不同时段的数据对比以及同现有文献中涉及到长江口的悬浮泥沙遥感反演模型进行对比发现,不同研究者建立的模型相互之间具有可比性,尤其在低悬沙浓度条件下,模型几乎趋于一致,说明以统计模型为基础的遥感反演模型在时空应用上可做一定的拓展。加强数据的对比研究是提高对统计模型应用上的可靠性认知的有效方式。
(3)泥沙粒径与光谱分析具有一定的相关性,但不能简单依此判定就是粒径对光谱的影响,因为泥沙粒径本身和泥沙浓度具有较好的相关性,而后者与光谱之间有着更好的回归关系,而通过理论分析表明,泥沙粒径分布主要是通过影响后向散射来对光谱反射率产生影响,细颗粒泥沙具有较大的后向散射而粗颗粒泥沙则具有较小的后向散射。
(4)野外数据分析表明：细粒径泥沙会增大光谱反射率,与理论分析一致；根据两个不同时期的数据分别建立悬沙浓度与要反射率之间的回归关系比较发现,样品数据集中泥沙粒径分布变化越小,建立的统计回归模型的R2值越高,模型拟合度越好。
(5)对已有的加入悬沙浓度和粒径的回归模式进行了检验,基本上表明,在统计基础上的加入粒径参数无助于提高模型精度,反而导致精度的下降。
(6)絮凝体粒径分布对悬沙水体光谱反射特征有着重要的影响,但是在利用悬沙的平均粒径,中值粒径以及絮凝体平均粒径分析其与光谱反射率之间的关系时,难以定量化表达粒径对光谱的影响。在将絮凝体平均粒径纳入统计模型之后,同样会导致模型精度的下降。
Suspended sediment concentration, spatial distribution and its transportation in the Yangtze River Estuary have become core indicators and important parameters in the researches of material fluxes, Material Cycle, changes of estuarine shoals, evaluation the impact of watershed projects on the estuary mouth and assessment of land resources in the Estuary. This has drawn the attention of academic circles, government departments and industry as well. Traditional single-point, multi-point measurement on board can only provide short-term partial data, lack of spatial distribution data and has a high cost, while remote sensing has an important advantage of covering large area and repeating observation in monitoring suspended sediment concentration.
In this paper, following tasks were mainly carried out in the turbidity maximum area of Yangtze River Estuary:
1) Field data acquisition and processing:Three in situ observations were performed at same site in the South Passage to collect spectral data, and surface water samples synchronously to measure sediment concentration and size distribution data in the laboratory. LISST-100x was used to measure floc particles as well..
2) Analysis of the spectral reflectance characteristics above water surface and the relationship between suspended sediment concentration and the spectral reflectance. Giving theoretical explanation for the different sensitivity of the suspended sediment concentration at visible band and near infrared band. Using MODIS bands as a reference to establish several regression equations between spectral reflectance and suspended sediment concentration. Focus on the accuracy and reliability of statistical models, compares inversion equations with different band parameters and mathematical relationships of different forms at different times, and found by other researchers.
3) Analysis the impact of suspended sediment particle size on the spectral reflectance characteristics and giving theoretical explanation and drawing the basic conclusion by analysis the measured data. The regression equations between spectral reflectance, the suspended sediment concentration and particle size was established, using of the mathematical relationships in literature. Further more, the impact of flocs on spectral characteristics was also considered and discussed.
The primary conclusions obtained are as follows:
1) Spectral reflectance at Near-infrared band has a good relation with suspended sediment concentration, which can be used for suspended sediment concentration inversion. Two-band ratio can effectively reduce the influence of other conditions (such as illumination, size, etc.) compare to parameters such as single band, and multi-band combination. For the model mathematical formulas, the polynomial model fit the data best, but without any excellence comparing to the exponential model and power model.
2) Through comparison of suspended sediment concentration inversion models founded by data from different periods and in the existing literature, it is found that models founded by different researchers are comparable, especially in a certain range of low suspended sediment concentration value indicating the statistical model is reliable. Strengthen the comparative study on the statistical models is an effective way to improve cognition of the reliability of the application.
3) There is some correlation between sediment grain size and spectrum, but it cannot certify the impact of particle size on the spectrum, because sediment particle size has a good correlation with suspended sediment concentration which also has a high correlation with the spectrum. Theoretical analysis shows that sediment particle size distribution mainly through the effect of scattering to impact on the spectral reflectance; fine sediments have a stronger backscatter than coarse sediment.
4) Field data showed that fine particle size would increase the spectral reflectance which was consistent with the theoretical analysis. Comparison of regression models founded using data from two different periods, it was found that the smaller the particle size distribution changes, the higher value the regression model R2 got.
5) By establishing regression models regression equations between spectral reflectance, the suspended sediment concentration and particle size, it showed that it could not help to improve model accuracy when particle size was included as an parameter, but lead to a decline in accuracy.
6) Grain size distribution of flocs particles had an important impact on water spectrum but it was difficult to express the effect quantitatively, when analysis by using suspended sediment mean diameter, median diameter and flocs mean diameter. When establish regression models regression equations between spectral reflectance, the suspended sediment concentration and flocs mean diameter, it also led to a decline in accuracy.
引文
[1]AMOS, C.L. and ALFOLDI, T.T., The determination of SSC in a macrotidal system using Landsat data[J]. Journal of Sedimentary Petrology, 1979,49:159-174.
[2]Blondeau-Patissier, D., Tilstone, G.H., Marinez-Vicente, V.,& Moore, G F. Comparison of bio-physical marine products from SeaWiFS, MODIS and a Bio-optical model with in situ measurememts from Northern European[J]. waters. Journal of Optics.2004,6:875-889.
[3]D. Doxaran, J.-M. Froidefond and P. Castaing. A reflectance band ratio used to estimate suspended matter concentrations in sediment-dominated coastal waters[J]. International Journal of Remote Sensing,2002,23(23):5079-5085.
[4]David Doxaran, Jean-Marie Froidefond, Samantha Lavender, Patrice Castaing. Spectral signature of highly turbid water:Application with SPOT data to quantify suspended particulate matter concentrations [J], Remote Sensing of Environment,2002,81(1):149-161
[5]David Doxaran, Jean-Marie Froidefond, Patrice Castaing. Remote-sensing reflectance of turbid sediment-dominated waters. Reduction of sediment type variations and changing illumination conditions effects by use of reflectance ratios[J].Applied Optics,2003, Vol.42, No.15:2623-2634
[6]David Doxaran, R. C. N. Cherukuru, and S. J. lavender, Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters[J],Int. J. Remote Sens.2005, Vol.26:1763-1769.
[7]David Doxaran, Nagur Cherukuru and Samantha J. Lavender. Apparent and inherent optical properties of turbid estuarine waters:measurements, empirical quantification relationships, and modeling [J].Applied Optics,2006, Vol.45, No.10:2310-2324.
[8]D. S. Bhargava, Dejene W. Mariam Effects of Suspended Particle Size and Concentration on Reflectance Measurements [J].Photogrammetric Engineering and Remote Sensing,1991,57:519-529
[9]Evlyn Marcia Leao Moraes Novo, Carlos Alberto Steffen and Claudia Zuccari Fernandes Braga. Results of a laboratory experiment relating spectral reflectance to total suspended solids [J]. Remote Sensing of Environment,1991,38(1):67-72
[10]Forget P, Ouillon S, Lahet F, et al. Inversion of reflectance spectra of non-chlorophyllous turbid coastal waters[J]. Remote Sensing of Environment, 1999,68:264-272.
[11]Hu, C.M., Carder K.L., Muller K., Frank E. Atomospheric correction of SeaWiFS imagery over turbid coastal waters [J]. Remote sensing of Environment,2000, 74(2):195-206.
[12]Hu, C.M., Muller-Karger, F.E., Biggs, D.C., Carder K.L., Nababan, B. Nadeau, D., and Vanderbloemen J.. Comparison of ship and satellite bio-optical measurements on the continental margin of the NE Gulf of Mexico [J]. Int. J. Remote Sens.,2003,24:2597-2612.
[13]Moore G.K.. Satellite remote sensing of water turbidity[J]. Hyd Sci,1980,25: 415-421.
[14]Jerlov.N.G.海洋光学[M].北京：北京科学出版社,1981.
[15]Kuang Runyuan, Zhou YuXuan, Li Xing, Shen Fang, Quantitative analysis of suspended sediment in Yangtze River Estuary from MODIS[C]. Images,Proceedings of SPIE,2008,0277-786X, Vol.7285,No.728553
[16]LISST-100X User's Manual, Version 4.65
[17]Leal A.K Mertes, Milton O Smith and John B Adams. Estimating suspended sediment concentrations in surface waters of the Amazon River wetlands from Landsat images[J]. Remote Sensing of Environment,1993,43(3):281-301
[18]L. Han, D. C Rundquist, L. L. Liu, R. N. Fraser, J. F. Schalles. The response of both surface reflectance and the underwater light field to various levels of suspended sediments:preliminary results[J]. American Society for Photogrammetry and Remote Sensing,1994,60(12):1463-1471.
[19]Munday J.C., Steffen C.A. and Braga C.Z.F.,Results of a laboratory experiment relating spectral reflectance to total suspended solid. Remote Sensing of Environment,1991,36:67-72.
[20]Mobley C. D.Light and Water,Radiative Transfer in Natural Waters[M].San Diego:Academic Press,1994.
[21]Richard L, Miller, etc. Using MODIS Terra 250m imagery to map concentrations of total suspended matter in coastal waters. Remote sensing of Environment,2004, 93:259-266.
[22]Slawomir B. Wozniak and Dariusz Stramski, Modeling the Optical Properties of Mineral Particles Suspended in Seawater and their Influence on Ocean Reflectance and Chlorophyll Estimation from Remote Sensing Algorithms [J]. Applied Optics,2004,43(17):3489-3503.
[23]Seelye Martin,海洋遥感导论[M]蒋兴伟等译,北京：海洋出版社,2008
[24]V. Klemas, Borchartdt, J.F., and Treasure, W,M. Suspended Sediment Observations from ERT-1.Remote Sensing of Environment,1973,2:205-221.
[25]V. Klemas, D. Bartlett, W. Philpot, and R. Roger. Coastal and estuarine studies with ERTs-1 and Skylab. Remote Sensing of Environment,1974,3:153-177.
[26]W. van Raaphorst, C. J. M. Philippart, J. P. C. Smit, F. J. Dijkstra and J. F. P. Malschaert. Distribution of suspended particulate matter in the North Sea as inferred from NOAA/AVHRR reflectance images and in situ observations [J]. Journal of Sea Research,1998,39(3-4):197-215.
[27]Wu Y.,Zhang J.,Liu S.M.,Zhang Z F.,Yao Q.Z.,Hong G.H.,L.Cooper. Sources and distribution of carbon within the Yangtze River system. Estuarine Coastal and Shelf Science.2007,71:13-15
[28]Yang S L, Cao A, Hotz H J, et al. Trends in annual discharge from the Yangtze River to the sea(1865-2004). Hydrological Science-Journal-des Science Hydrologiques,2005,50(5):825-836.
[29]Yang S L, Shi Z,Zhao H Y, et al.Effects of human activities on the Yangtze River suspended sediment flux into the estuary in the last century. Hydrol Earth Syst Sci,2004,8(6):1210-1216.
[30]Yang, S.L., J.Zhang, J.Zhu,J.P.Smith,S.B.Dai,A Gao,and P.Li. Imapact of dams on Yangtze River sediment supply to the sea and delta intertidal wetland response, J.Geophys. Res.,2005,110,F03006,doi:10.1029/2004JF000271.
[31]Yang,S.L., Li,M., Dai,S.B., Liu Z., Zhang,J. and Ding, P.X. Drastic decrease in sediment supply from the Yangtze River and its challenge to coastal wetland management. Geophysical Research Letters. 2006,33,L06408,doi:10.1029/2005GL025507.
[32]Young-Je Park, Kevin Ruddick. Model of remote-sensing reflectance including bidirectional effects for case 1 and case 2 waters[J]. Applied Optics, 2005,44(7):1236-1249
[33]陈吉余,长江河口动力过程和地貌演变[M].1988,上海科学技术出版社.
[34]陈吉余,沈焕庭,恽才兴,长江河口动力过程和地貌演变[M],上海：上海科学技术出版社,1988
[35]陈吉余等,21世纪的长江河口初探[M],北京：海洋出版社,2009
[36]陈沈良,张国安,杨世伦,虞志英长江口水域悬沙浓度时空变化与泥沙再悬浮[J].地理学报.2004,59(2)：260-266.
[37]陈涛,李武,悬浮泥沙浓度与光谱反射率峰值波长红移的相关关系[J].海洋学报,1994,16(1)：38-43.
[38]程江,何青,夏小明.长江口徐六泾悬浮细颗粒泥沙絮凝体特性[J].海洋与湖沼,2007,38(4)：304-313.
[39]程江,何青,王元,刘红,夏小明.长江河口细颗粒泥沙絮凝体粒径的谱分析[J].长江流域资源与环境.2005,14(4)：460-464.
[40]关许为,陈英祖,林以安,李炎.长江口泥沙絮凝体的现场显微观测[J].泥沙研究,1982，3：54-59.
[41]傅克忖,荒川久幸,曾宪模,悬沙水体不同波段反射比的分布特征及悬沙量估算实验研究[J].海洋学报,1999,21(3)：134-140.
[42]韩震,恽才兴,蒋雪中.悬浮泥沙反射光谱特性实验研究[J].水利学报,2003，12：118-121.
[43]孔亚珍,丁平兴,贺松林,何超,肖文军.长江口外及其邻近海域含沙量时空变化特征分析[J].海洋科学进展,2006,24(4)：446-454.
[44]李军,高抒,曾志刚,贾建军.长江口悬浮体粒度特征及其季节性差异[J].海洋与湖沼,2003,34(5)：499-510.
[45]李九发,何青,张琛.长江河口拦门沙河床淤积和泥沙再悬浮过程[J].海洋与湖沼,2000,31(1)：101-109.
[46]李九发等.上海滩涂后备土地资源及其可持续开发途径[J].长江流域资源与环境.2003,12(1)：17-22.
[47]李四海,恽才兴.河口表层悬浮泥沙气象卫星遥感定量模式研究[J].遥感学 报,2001,5(2)：154-160.
[48]李四海,恽才兴,唐军武.河口悬浮泥沙SeaWiFS遥感定量模式研究[J].海洋学报,2002,24(2)：51-58.
[49]李炎,李京.基于海面-遥感器光谱反射率斜率传递现象的悬浮泥沙遥感算法[J].科学通报,1999,44(77)：1892-1897.
[50]黎夏.悬浮泥沙遥感定量的统一模式及其在珠江口中的应用.环境遥感[J],1992,7(2)：106-114.
[51]刘良明,卫星海洋遥感导论[M],武汉：武汉大学出版社,2005
[52]刘显傅,李铜基,陈清莲.水体主要成分对表观光学量的影响[J].海洋技术.2004,23(1)：85-89.
[53]刘志国,周云轩,沈芳.河口水体泥沙浓度的水面光谱统计模式分析[J].水利学报.2007,38(7)：799-805.
[54]刘志国,长江口水体表层泥沙浓度的遥感反演与分析[D],华东师范大学,2007
[55]任敬萍,赵进平,二类水体水色遥感的主要进展与发展前景[J].地球科学进展,2002,17(3)：363-371.
[56]沈芳,周云轩,李九发,刘小丽,河口悬沙粒径对遥感反射率影响的理论分析与实验观测[J],红外与毫米波学报,2009,28(3)：168-172.
[57]沈焕庭.长江河口物质通量[M].北京：海洋出版社,2001.
[58]水利部长委水文局,1998年长江暴雨洪水[R],北京：中国水利水电出版社,2002,
[59]唐军武,田国良,汪小勇,王晓梅,宋庆君.水体光谱测量与分析Ⅰ：水面以上测量法[J].遥感学报,2004,8(1)：37-43.
[60]唐兆明,何志刚,韩玉梅.悬浮泥沙的测量[J].中山大学学报,2003,42(2)：244-247
[61]汪小勇,李铜基,唐军武,杨安安.二类水体表观光学特性的测量与分析——水面之上法方法研究[J].海洋技术,2004,23(2)：2-6
[62]王芳,李国胜.海洋悬浮泥沙二元特征参数MODIS遥感反演模型研究[J].地理研究.2007,26(6)：1186-1196.
[63]王繁,河口水体悬浮物固有光学性质及浓度遥感反演模式研究[D],浙江大学,2008
[64]汪亚平,潘少明,H. V. Wang,高建华,杨旸,王爱军,李占海,吴中.长江口水沙入海通量观测与分析[J].地理学报.2006.61(1)：35-46.
[65]许陈忠,乐华福,毛显谋.表层水体悬浮泥沙光谱特性及航空遥感方法的初步研究[J].海洋通报.1982,1(2)：48-56.
[66]恽才兴,蔡孟裔,王宝全.利用卫星相片分析长江入海泥沙扩散问题[J].海洋与湖沼,1981,12(5)：1981,12(5)：391-401.
[67]恽才兴,长江河口近期演变基本规律[M],北京：海洋出版社,2004
[68]恽才兴,海岸带及近海卫星遥感综合应用技术[M],北京：海洋出版社,2005
[69]张渊智,聂跃平,蔺启忠,荆林海,张兵.表面水质遥感[J].遥感技术与应用,2000,15(4)：214-219
[70]张芸,张鹰,王晶晶.悬沙水体光谱反射率与质量浓度、粒径的相关关系[J].海洋科学进展.2008,26(3)：142-148.
[71]赵英时等,遥感应用分析原理与方法[M],北京：科学出版社,2003.
[72]左书华,李九发,万新宁,沈焕庭,付桂.长江河口悬沙浓度变化特征分析[J].泥沙研究,2006,3：68-75.
[73]周雯,曹文熙,李彩.海水中矿物质颗粒吸收和散射特性Mie理论分析[J].热带海洋学报.2008,27(1)：22-26.
[74]中华人民共和国水利部.2001-2007.中国河流泥沙公报[R].北京：中国水利水电出版社
[2]Blondeau-Patissier, D., Tilstone, G.H., Marinez-Vicente, V.,& Moore, G F. Comparison of bio-physical marine products from SeaWiFS, MODIS and a Bio-optical model with in situ measurememts from Northern European[J]. waters. Journal of Optics.2004,6:875-889.
[3]D. Doxaran, J.-M. Froidefond and P. Castaing. A reflectance band ratio used to estimate suspended matter concentrations in sediment-dominated coastal waters[J]. International Journal of Remote Sensing,2002,23(23):5079-5085.
[4]David Doxaran, Jean-Marie Froidefond, Samantha Lavender, Patrice Castaing. Spectral signature of highly turbid water:Application with SPOT data to quantify suspended particulate matter concentrations [J], Remote Sensing of Environment,2002,81(1):149-161
[5]David Doxaran, Jean-Marie Froidefond, Patrice Castaing. Remote-sensing reflectance of turbid sediment-dominated waters. Reduction of sediment type variations and changing illumination conditions effects by use of reflectance ratios[J].Applied Optics,2003, Vol.42, No.15:2623-2634
[6]David Doxaran, R. C. N. Cherukuru, and S. J. lavender, Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters[J],Int. J. Remote Sens.2005, Vol.26:1763-1769.
[7]David Doxaran, Nagur Cherukuru and Samantha J. Lavender. Apparent and inherent optical properties of turbid estuarine waters:measurements, empirical quantification relationships, and modeling [J].Applied Optics,2006, Vol.45, No.10:2310-2324.
[8]D. S. Bhargava, Dejene W. Mariam Effects of Suspended Particle Size and Concentration on Reflectance Measurements [J].Photogrammetric Engineering and Remote Sensing,1991,57:519-529
[9]Evlyn Marcia Leao Moraes Novo, Carlos Alberto Steffen and Claudia Zuccari Fernandes Braga. Results of a laboratory experiment relating spectral reflectance to total suspended solids [J]. Remote Sensing of Environment,1991,38(1):67-72
[10]Forget P, Ouillon S, Lahet F, et al. Inversion of reflectance spectra of non-chlorophyllous turbid coastal waters[J]. Remote Sensing of Environment, 1999,68:264-272.
[11]Hu, C.M., Carder K.L., Muller K., Frank E. Atomospheric correction of SeaWiFS imagery over turbid coastal waters [J]. Remote sensing of Environment,2000, 74(2):195-206.
[12]Hu, C.M., Muller-Karger, F.E., Biggs, D.C., Carder K.L., Nababan, B. Nadeau, D., and Vanderbloemen J.. Comparison of ship and satellite bio-optical measurements on the continental margin of the NE Gulf of Mexico [J]. Int. J. Remote Sens.,2003,24:2597-2612.
[13]Moore G.K.. Satellite remote sensing of water turbidity[J]. Hyd Sci,1980,25: 415-421.
[14]Jerlov.N.G.海洋光学[M].北京：北京科学出版社,1981.
[15]Kuang Runyuan, Zhou YuXuan, Li Xing, Shen Fang, Quantitative analysis of suspended sediment in Yangtze River Estuary from MODIS[C]. Images,Proceedings of SPIE,2008,0277-786X, Vol.7285,No.728553
[16]LISST-100X User's Manual, Version 4.65
[17]Leal A.K Mertes, Milton O Smith and John B Adams. Estimating suspended sediment concentrations in surface waters of the Amazon River wetlands from Landsat images[J]. Remote Sensing of Environment,1993,43(3):281-301
[18]L. Han, D. C Rundquist, L. L. Liu, R. N. Fraser, J. F. Schalles. The response of both surface reflectance and the underwater light field to various levels of suspended sediments:preliminary results[J]. American Society for Photogrammetry and Remote Sensing,1994,60(12):1463-1471.
[19]Munday J.C., Steffen C.A. and Braga C.Z.F.,Results of a laboratory experiment relating spectral reflectance to total suspended solid. Remote Sensing of Environment,1991,36:67-72.
[20]Mobley C. D.Light and Water,Radiative Transfer in Natural Waters[M].San Diego:Academic Press,1994.
[21]Richard L, Miller, etc. Using MODIS Terra 250m imagery to map concentrations of total suspended matter in coastal waters. Remote sensing of Environment,2004, 93:259-266.
[22]Slawomir B. Wozniak and Dariusz Stramski, Modeling the Optical Properties of Mineral Particles Suspended in Seawater and their Influence on Ocean Reflectance and Chlorophyll Estimation from Remote Sensing Algorithms [J]. Applied Optics,2004,43(17):3489-3503.
[23]Seelye Martin,海洋遥感导论[M]蒋兴伟等译,北京：海洋出版社,2008
[24]V. Klemas, Borchartdt, J.F., and Treasure, W,M. Suspended Sediment Observations from ERT-1.Remote Sensing of Environment,1973,2:205-221.
[25]V. Klemas, D. Bartlett, W. Philpot, and R. Roger. Coastal and estuarine studies with ERTs-1 and Skylab. Remote Sensing of Environment,1974,3:153-177.
[26]W. van Raaphorst, C. J. M. Philippart, J. P. C. Smit, F. J. Dijkstra and J. F. P. Malschaert. Distribution of suspended particulate matter in the North Sea as inferred from NOAA/AVHRR reflectance images and in situ observations [J]. Journal of Sea Research,1998,39(3-4):197-215.
[27]Wu Y.,Zhang J.,Liu S.M.,Zhang Z F.,Yao Q.Z.,Hong G.H.,L.Cooper. Sources and distribution of carbon within the Yangtze River system. Estuarine Coastal and Shelf Science.2007,71:13-15
[28]Yang S L, Cao A, Hotz H J, et al. Trends in annual discharge from the Yangtze River to the sea(1865-2004). Hydrological Science-Journal-des Science Hydrologiques,2005,50(5):825-836.
[29]Yang S L, Shi Z,Zhao H Y, et al.Effects of human activities on the Yangtze River suspended sediment flux into the estuary in the last century. Hydrol Earth Syst Sci,2004,8(6):1210-1216.
[30]Yang, S.L., J.Zhang, J.Zhu,J.P.Smith,S.B.Dai,A Gao,and P.Li. Imapact of dams on Yangtze River sediment supply to the sea and delta intertidal wetland response, J.Geophys. Res.,2005,110,F03006,doi:10.1029/2004JF000271.
[31]Yang,S.L., Li,M., Dai,S.B., Liu Z., Zhang,J. and Ding, P.X. Drastic decrease in sediment supply from the Yangtze River and its challenge to coastal wetland management. Geophysical Research Letters. 2006,33,L06408,doi:10.1029/2005GL025507.
[32]Young-Je Park, Kevin Ruddick. Model of remote-sensing reflectance including bidirectional effects for case 1 and case 2 waters[J]. Applied Optics, 2005,44(7):1236-1249
[33]陈吉余,长江河口动力过程和地貌演变[M].1988,上海科学技术出版社.
[34]陈吉余,沈焕庭,恽才兴,长江河口动力过程和地貌演变[M],上海：上海科学技术出版社,1988
[35]陈吉余等,21世纪的长江河口初探[M],北京：海洋出版社,2009
[36]陈沈良,张国安,杨世伦,虞志英长江口水域悬沙浓度时空变化与泥沙再悬浮[J].地理学报.2004,59(2)：260-266.
[37]陈涛,李武,悬浮泥沙浓度与光谱反射率峰值波长红移的相关关系[J].海洋学报,1994,16(1)：38-43.
[38]程江,何青,夏小明.长江口徐六泾悬浮细颗粒泥沙絮凝体特性[J].海洋与湖沼,2007,38(4)：304-313.
[39]程江,何青,王元,刘红,夏小明.长江河口细颗粒泥沙絮凝体粒径的谱分析[J].长江流域资源与环境.2005,14(4)：460-464.
[40]关许为,陈英祖,林以安,李炎.长江口泥沙絮凝体的现场显微观测[J].泥沙研究,1982，3：54-59.
[41]傅克忖,荒川久幸,曾宪模,悬沙水体不同波段反射比的分布特征及悬沙量估算实验研究[J].海洋学报,1999,21(3)：134-140.
[42]韩震,恽才兴,蒋雪中.悬浮泥沙反射光谱特性实验研究[J].水利学报,2003，12：118-121.
[43]孔亚珍,丁平兴,贺松林,何超,肖文军.长江口外及其邻近海域含沙量时空变化特征分析[J].海洋科学进展,2006,24(4)：446-454.
[44]李军,高抒,曾志刚,贾建军.长江口悬浮体粒度特征及其季节性差异[J].海洋与湖沼,2003,34(5)：499-510.
[45]李九发,何青,张琛.长江河口拦门沙河床淤积和泥沙再悬浮过程[J].海洋与湖沼,2000,31(1)：101-109.
[46]李九发等.上海滩涂后备土地资源及其可持续开发途径[J].长江流域资源与环境.2003,12(1)：17-22.
[47]李四海,恽才兴.河口表层悬浮泥沙气象卫星遥感定量模式研究[J].遥感学 报,2001,5(2)：154-160.
[48]李四海,恽才兴,唐军武.河口悬浮泥沙SeaWiFS遥感定量模式研究[J].海洋学报,2002,24(2)：51-58.
[49]李炎,李京.基于海面-遥感器光谱反射率斜率传递现象的悬浮泥沙遥感算法[J].科学通报,1999,44(77)：1892-1897.
[50]黎夏.悬浮泥沙遥感定量的统一模式及其在珠江口中的应用.环境遥感[J],1992,7(2)：106-114.
[51]刘良明,卫星海洋遥感导论[M],武汉：武汉大学出版社,2005
[52]刘显傅,李铜基,陈清莲.水体主要成分对表观光学量的影响[J].海洋技术.2004,23(1)：85-89.
[53]刘志国,周云轩,沈芳.河口水体泥沙浓度的水面光谱统计模式分析[J].水利学报.2007,38(7)：799-805.
[54]刘志国,长江口水体表层泥沙浓度的遥感反演与分析[D],华东师范大学,2007
[55]任敬萍,赵进平,二类水体水色遥感的主要进展与发展前景[J].地球科学进展,2002,17(3)：363-371.
[56]沈芳,周云轩,李九发,刘小丽,河口悬沙粒径对遥感反射率影响的理论分析与实验观测[J],红外与毫米波学报,2009,28(3)：168-172.
[57]沈焕庭.长江河口物质通量[M].北京：海洋出版社,2001.
[58]水利部长委水文局,1998年长江暴雨洪水[R],北京：中国水利水电出版社,2002,
[59]唐军武,田国良,汪小勇,王晓梅,宋庆君.水体光谱测量与分析Ⅰ：水面以上测量法[J].遥感学报,2004,8(1)：37-43.
[60]唐兆明,何志刚,韩玉梅.悬浮泥沙的测量[J].中山大学学报,2003,42(2)：244-247
[61]汪小勇,李铜基,唐军武,杨安安.二类水体表观光学特性的测量与分析——水面之上法方法研究[J].海洋技术,2004,23(2)：2-6
[62]王芳,李国胜.海洋悬浮泥沙二元特征参数MODIS遥感反演模型研究[J].地理研究.2007,26(6)：1186-1196.
[63]王繁,河口水体悬浮物固有光学性质及浓度遥感反演模式研究[D],浙江大学,2008
[64]汪亚平,潘少明,H. V. Wang,高建华,杨旸,王爱军,李占海,吴中.长江口水沙入海通量观测与分析[J].地理学报.2006.61(1)：35-46.
[65]许陈忠,乐华福,毛显谋.表层水体悬浮泥沙光谱特性及航空遥感方法的初步研究[J].海洋通报.1982,1(2)：48-56.
[66]恽才兴,蔡孟裔,王宝全.利用卫星相片分析长江入海泥沙扩散问题[J].海洋与湖沼,1981,12(5)：1981,12(5)：391-401.
[67]恽才兴,长江河口近期演变基本规律[M],北京：海洋出版社,2004
[68]恽才兴,海岸带及近海卫星遥感综合应用技术[M],北京：海洋出版社,2005
[69]张渊智,聂跃平,蔺启忠,荆林海,张兵.表面水质遥感[J].遥感技术与应用,2000,15(4)：214-219
[70]张芸,张鹰,王晶晶.悬沙水体光谱反射率与质量浓度、粒径的相关关系[J].海洋科学进展.2008,26(3)：142-148.
[71]赵英时等,遥感应用分析原理与方法[M],北京：科学出版社,2003.
[72]左书华,李九发,万新宁,沈焕庭,付桂.长江河口悬沙浓度变化特征分析[J].泥沙研究,2006,3：68-75.
[73]周雯,曹文熙,李彩.海水中矿物质颗粒吸收和散射特性Mie理论分析[J].热带海洋学报.2008,27(1)：22-26.
[74]中华人民共和国水利部.2001-2007.中国河流泥沙公报[R].北京：中国水利水电出版社
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