长江口水色遥感参数模拟研究
|
摘要
长江口水色定量遥感对于监测长江口泥沙入海通量、时空分布有着重要的意义。当前水色遥感常用经验关系模式反演成分浓度,算法简单、稳定性差、信息机理不明确。为更加准确的反演长江口水色浓度需要从深层次地了解长江口水体成分的光学特性和光在水中的辐射传输问题,构建水体光谱辐射传输模型,建立一个符合长江口区域的水色反演模型。本文基于此,选择长江口为研究区,通过大量的实地水体光学调查工作和室内实验分析,进一步探讨水色反演问题。
根据现场实测数据和室内实验数据,分析了长江口水色组分的吸收、散射特性,建立了长江口泥沙吸收光谱、(后向)散射光谱参数化模型,叶绿素吸收光谱参数化模型,黄色物质吸收光谱参数化模型。
根据长江口实测资料,分析了长江口水体反射光谱特征,长江口水体反射光谱可以分为8种类型；根据各种类型的水体反射光谱特征,提出相邻或相间波段的反射光谱斜率算法应用于MODIS中高分辨率影像进行水体分类,分类结果与实际基本符合,分类结果可用来监测不同水体的空间分布情况。
借鉴前人研究成果,建立长江口水体辐射传输模型,模拟了水体表面遥感反射率光谱。模拟表明,建立的辐射传输模型和参数化模型在泥沙中低浓度范围内适应性比较好,而在高浓度范围(0.2kg/m3以上),因超过光学参数化模型的范围,结果不理想：泥沙浓度垂向不同分布结构对反射光谱有明显的影响,与泥沙垂向分布均一型相比,近表层水域泥沙浓度梯度变化大的水面反射光谱比梯度变化小的反射光谱偏差大；黄色物质的主要效应是降低短波长反射率值,而反射光谱形态特征不会有明显变化；口外泥沙低浓度区,叶绿素的吸收效应明显大于叶绿素的散射效应,叶绿素对反射光谱的贡献以吸收为主：各种类型水体透光层深度模拟表明,长江口透光层深度小于实际水深,说明水面的离水辐射主要来自一定深度内水体本身的辐射贡献,水底反射贡献可忽略不计；最后提出透光层深度的泥沙垂向加权积分浓度,传统经验方法中,与反射光谱建立算法关系的表层浓度建议用此代替,以真实反映反射光谱对应的浓度信息。
耦合非线性优化方法Levenberg-Marquaudt和水体辐射传输模式建立水色多组分反演模型。根据实测的反射光谱反演水色组分浓度,模式导出的遥感反射率与实测非常接近。反演浓度与实测水体组分浓度对比表明,泥沙和叶绿素浓度反演精度较高,黄色物质反演精度偏低。泥沙浓度平均误差25.3%,叶绿素浓度平均误差31.5%,黄色物质平均误差59.4%。
Ocean color remote sensing is a great significance in monitoring sediment flux and spatial and temporal distribution of suspended sediment in Yangtze estuary. The empirical approach often applies to retrieval of water compositions concentration. However, the disadvantages of empirical algorithms are regional or seasonal effects, fuzzy of information mechanism. In order to accurately retrieve concentration of water compositions, we need understand deep optics properties of ocean color in Yangtze estuary and radiative transfer of light in water, and establish the radiative transfer model and the retrieval model in Yangtze estuary. Based on these reasons, we discuss about inverse problem by in site optics investigation and experimental analysis indoor.
Based on the measured data in Yangtze estuary and experimental data indoor, we analyze absorption and scattering properties of water body. Furthermore, the study builds parameterization model about suspended sediment absorption and scattering, chlorophyll absorption, and yellow matter absorption.
According to the measured data in Yangtze estuary, the characters of reflectance spectrum were analyzed. There are eight types reflectance spectrum. We put forward an algorithm of spectrum slope in order to distinguish different spectrum types. The algorithms applied to water body classification of MODIS images. The results are consistent with the facts and monitor dynamic distributions of different water body.
The study builds water radiative transfer model by using previous research results for reference, and model remote sensing reflectance on water surface. The result shows the radiative transfer model and parameterization model is effective in the range of low-middle concentration of suspended sediment. However, in the range of high concentration (>0.2km/m3), the result is inconsistent with fact. The model indicates the depth of euphotic zone is less than water depth in the different type water body. This show the water-leaving radiances on water surface mainly come from radiance contribution of water body itself, and bottom effects are negligible. Based on the depth of euphotic zone, the paper suggested the optically weighted suspended sediment concentration instead of surface concentration when building traditional empirical algorithms in order to reflect truly suspended sediment concentration correspondence with remote sensing reflectance.
Coupling non-linear optimization techniques and water body radiative transfer, the article set up ocean color retrieval model. The retrieval results show the average error of suspended sediment is 25.3%, and the average error of chlorophyll concentration is 31.5%, and the average error of yellow matters absorption is 59.4%. The retrieval precision of suspended sediment concentration and chlorophyll concentration is high. However, the retrieval precision of yellow matter absorption is low.
根据现场实测数据和室内实验数据,分析了长江口水色组分的吸收、散射特性,建立了长江口泥沙吸收光谱、(后向)散射光谱参数化模型,叶绿素吸收光谱参数化模型,黄色物质吸收光谱参数化模型。
根据长江口实测资料,分析了长江口水体反射光谱特征,长江口水体反射光谱可以分为8种类型；根据各种类型的水体反射光谱特征,提出相邻或相间波段的反射光谱斜率算法应用于MODIS中高分辨率影像进行水体分类,分类结果与实际基本符合,分类结果可用来监测不同水体的空间分布情况。
借鉴前人研究成果,建立长江口水体辐射传输模型,模拟了水体表面遥感反射率光谱。模拟表明,建立的辐射传输模型和参数化模型在泥沙中低浓度范围内适应性比较好,而在高浓度范围(0.2kg/m3以上),因超过光学参数化模型的范围,结果不理想：泥沙浓度垂向不同分布结构对反射光谱有明显的影响,与泥沙垂向分布均一型相比,近表层水域泥沙浓度梯度变化大的水面反射光谱比梯度变化小的反射光谱偏差大；黄色物质的主要效应是降低短波长反射率值,而反射光谱形态特征不会有明显变化；口外泥沙低浓度区,叶绿素的吸收效应明显大于叶绿素的散射效应,叶绿素对反射光谱的贡献以吸收为主：各种类型水体透光层深度模拟表明,长江口透光层深度小于实际水深,说明水面的离水辐射主要来自一定深度内水体本身的辐射贡献,水底反射贡献可忽略不计；最后提出透光层深度的泥沙垂向加权积分浓度,传统经验方法中,与反射光谱建立算法关系的表层浓度建议用此代替,以真实反映反射光谱对应的浓度信息。
耦合非线性优化方法Levenberg-Marquaudt和水体辐射传输模式建立水色多组分反演模型。根据实测的反射光谱反演水色组分浓度,模式导出的遥感反射率与实测非常接近。反演浓度与实测水体组分浓度对比表明,泥沙和叶绿素浓度反演精度较高,黄色物质反演精度偏低。泥沙浓度平均误差25.3%,叶绿素浓度平均误差31.5%,黄色物质平均误差59.4%。
Ocean color remote sensing is a great significance in monitoring sediment flux and spatial and temporal distribution of suspended sediment in Yangtze estuary. The empirical approach often applies to retrieval of water compositions concentration. However, the disadvantages of empirical algorithms are regional or seasonal effects, fuzzy of information mechanism. In order to accurately retrieve concentration of water compositions, we need understand deep optics properties of ocean color in Yangtze estuary and radiative transfer of light in water, and establish the radiative transfer model and the retrieval model in Yangtze estuary. Based on these reasons, we discuss about inverse problem by in site optics investigation and experimental analysis indoor.
Based on the measured data in Yangtze estuary and experimental data indoor, we analyze absorption and scattering properties of water body. Furthermore, the study builds parameterization model about suspended sediment absorption and scattering, chlorophyll absorption, and yellow matter absorption.
According to the measured data in Yangtze estuary, the characters of reflectance spectrum were analyzed. There are eight types reflectance spectrum. We put forward an algorithm of spectrum slope in order to distinguish different spectrum types. The algorithms applied to water body classification of MODIS images. The results are consistent with the facts and monitor dynamic distributions of different water body.
The study builds water radiative transfer model by using previous research results for reference, and model remote sensing reflectance on water surface. The result shows the radiative transfer model and parameterization model is effective in the range of low-middle concentration of suspended sediment. However, in the range of high concentration (>0.2km/m3), the result is inconsistent with fact. The model indicates the depth of euphotic zone is less than water depth in the different type water body. This show the water-leaving radiances on water surface mainly come from radiance contribution of water body itself, and bottom effects are negligible. Based on the depth of euphotic zone, the paper suggested the optically weighted suspended sediment concentration instead of surface concentration when building traditional empirical algorithms in order to reflect truly suspended sediment concentration correspondence with remote sensing reflectance.
Coupling non-linear optimization techniques and water body radiative transfer, the article set up ocean color retrieval model. The retrieval results show the average error of suspended sediment is 25.3%, and the average error of chlorophyll concentration is 31.5%, and the average error of yellow matters absorption is 59.4%. The retrieval precision of suspended sediment concentration and chlorophyll concentration is high. However, the retrieval precision of yellow matter absorption is low.
引文
[1]Aas E.. Two-stream irradiance model for deep waters. Applied Optics,1987,26 (11):2095-2101.
[2]Agrawal, Y.C. The optical volume scattering function:Temporal and vertical variability in the water column off the New Jersey coast. Limnol. Oceanogr., 2005,50(6):1787-1794
[3]Albert A and Gege P. Inversion of irradiance and remote sensing reflectance in shallow water between 400 and 800 nm for calculations of water and bottom properties. Applied Optics,2006,45(10):2331-2343.
[4]Albert A., Mobley C. D. An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters. Optics express, 2003,11(22):2873-2890.
[5]Austin, R.W. and G. Halikas,1976:The index of refraction of seawater. SIO Ref. 76-1, Vis. Lab., Scripps Inst. Of Oceanography, La Jolla, California,64pp.
[6]Austin, R.W.,1974:Inherent spectral radiance signatures of the ocean surface. In: S.Q. Duntley, R.W. Austin, W.H. Wilson, C.F. Edgerton, and S.W. Moran, Ocean Color Analysis, SIO Ref.74-10, Scripps Institution of Oceanography, La Jolla, CA.
[7]Babin M., Stramski D., Ferrari G. M., et al.. Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe. Journal Geophysical Research,108,3211 (2003), doi:10.1029/2001JC000882.
[8]Bates D E, Porter J N. AO3D:A Monte Carlo code for modeling of environmental light propagation. Journal of Quantitative Spectroscopy & Radiative Transfer,2008,109:1802-1814
[9]Beardsley, GF. and J.R.V. Zaneveld,1969:Theoretical dependence of the near-asymptotic apparent optical properties on the Inherent Optical Properties of sea water. J. Opt. Soc. Amer.59:373-377.
[10]Bowers D G, Harker G E L, Stephan B. Absorption spectra of inorganic particles in the Irish Sea and their relevance to remote sensing of chlorophyll. International Journal of Remote Sensing,1996,17:2449-2460.
[11]Bricaud A, Morel A, Babin M, et al. Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters:Analysis and implications for bio-optical models. Journal of Geophysical Research,1998, 103(C13):31033-31044.
[12]Bricaud A., Morel A. and Prieur L.. Optical efficiency factors of some phytoplankters. Limnol. Oceanogr.,1983,28:816-832.
[13]Bricaud A., Morel A. and Prieur, L.. Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains. Limnol. Oceanogr. 1981,26:43-53.
[14]Bukata R. P., Jerome J. H., Kondratyev K. Y., et al. Optical Properties and Remote Sensing of Inland and Coastal Waters, CRC Press, Inc., Boca Raton, Florida,1995,362 p.
[15]Bukata, R. P., Bruton, J. E., Jerome, J. H., Jain, S. C. and Zwick, H. H. (1981a). Optical water quality model of Lake Ontario.2. Determination of chlorophyll a and suspended mineral concentrations of natural waters from submersible and low altitude remote sensors. Appl. Optics 20:1704-1714.
[16]Bukata, R. P., Jerome, J. H., Bruton, J. E., Jain, S. C. and Zwick, H. H.. Optical water quality model of Lake Ontario.1. Determination of the optical cross sections of organic and inorganic particulates in Lake Ontario. Appl. Optics, 1981b,20:1696-1703.
[17]Bukata, R. P., Jerome, J. H., Kondratyev, K. Y. and Pozdnyakov, D. V. (1991). Satellite monitoring of optically-active components of inland waters:an essential input to regional climate change impact studies. J. Great Lakes Res 17:470-478.
[18]Bulgarelli B., Kisselev V. B., and Roberti L. Radiative Transfer in the Atmosphere-Ocean System:The Finite-Element Method. Appl. Opt.1999,38: 1530-1542.
[19]Carder, K. L., Chen, F. R., Lee, Z. P., et al. Semianalytic Moderate-Resolution Imaging Spectrometer algorithms for chlorophyll a and absorption with bio-optical domains based on nitrate-depletion temperatures. J. Geophys. Res., 1999,104:5403-5421.
[20]Carder, K. L., S. K. Hawes, and Z. P. Lee.1994. SeaWiFS algorithm for chlorophyll a and colored dissolved organic matter in a subtropical environment. SeaWiFS working group report.
[21]Carder, K. L., Steward, R. G., Harvey, G. R. and Ortner, P. B. (1989). Marine humic and fulvic acids:Their effect on remote sensing of ocean chlorophyll. Limnol. Oceanogr.34:68-81.
[22]Carpenter D J, Carpenter S M. Modeling inland water quality using LANDSAT data. Remote Sensing of Environment,1983,13:345-352.
[23]Chami M and Robilliard D. Inversion of Oceanic Constituents in Case I and II Waters with Genetic Programming Algorithms. Applied Optics,2002,41(30): 6260-6275.
[24]Chami M. Importance of the polarization in the retrieval of oceanic constituents from the remote sensing reflectance. Journal of Geophysical Research,2007,112, C05026:1-13.
[25]Chami M, Santer R, and Dilligeard E. Radiative transfer model for the computation of radiance and polarization in an ocean-atmosphere system: polarization properties of suspended matter for remote sensing, Appl. Opt.40, 2398-2416 (2001),
[26]Chang C H, Liu C C, Wen C G. Integrating semianalytical and genetic algorithms to retrieve the constituents of water bodies from remote sensing of ocean color. Optics Express,2007,15(2):252-265.
[27]Chowdhary J., Cairns B., and Travis L. D. Contribution of water-leaving radiances to multiangle, multispectral polarimetric observations over the open ocean:bio-optical model results for case 1 waters, Appl. Opt.45,5542-5567 (2006)
[28]Cococcioni M, Lazzerini B, Marcelloni F. Estimating the concentration of optically active constituents of sea water by Takagi-Sugeno models with quadratic rule consequents. Pattern Recognition,2007,40:2846-2860
[29]Defoin-Platel M, Chami M. How ambiguous is the inverse problem of ocean color in coastal waters. Journal of Geophysical Research,2007,112:1-16
[30]Dekker A G, Vos R J, Peters S W M. Comparison of remote sensing data, model results and in situ data for total suspended matter (TSM) in the southern Frisian lakes. The Science of the Total Environment 2001,268:197-214.
[31]Dekker, A. G, Malthus, T. J. and Seyhan, E. (1991). Quantitative modeling of inland water quality for high-resolution MSS systems. IEEE Trans. Geosci. Remote Sens.29:89-95.
[32]Devred E, Dubuisson P and Chami M. Radiative transfer code:Application to the calculation of PAR. Proc. Indian Acad. Sci. (Earth Planet. Sci.),2000,109(4): 407-413.
[33]Doerffer R. and Schiller H.. The MERIS Case 2 water algorithm. International Journal of Remote Sensing,2007,28(3)-4:517-535.
[34]Doerffer, R. and Fischer, J. (1994). Concentrations of chlorophyll, suspended matter, and gelbstoff in case II waters derived from satellite coastal zone color scanner data with inverse modeling methods. J. Geophys. Res.99:7457-7466.
[35]Doxaran D, Cherukuru N and Lavender S J. Apparent and inherent optical properties of turbid estuarine waters_measurements, empirical quantification relationships, and modeling. Applied Optics,2006,45(10):2310-2324.
[36]Doxaran D, Cherukuru R C N, and Lavender S J. Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters. International Journal of Remote Sensing,2005,26(8):1763-1769.
[37]Doxaran D, Froidefond J M, Castaing P. A reflectance band ratio used to estimate suspended matter concentrations in coastal sediment-dominated waters. International Journal of Remote Sensing,2002,23(23):5079-5085.
[38]Doxaran D, Froidefond J M, Castaing P. Remote-Sensing reflectance of turbid ediment-dominated waters. Reduction of sediment type Variations and changing illumination conditions effects by use of reflectance ratios. Applied Optics,2003, 42(15):2623-2634.
[39]Doxaran D, Froidefond J M, Lavender S, et al. Spectral signature of highly turbid waters Application with SPOT data to quantify suspended particulate matter concentrations. Remote Sensing of Environment,2002,81:149-161.
[40]Ekercin S. Water quality retrievals from high resolution IKONOS multispectral imagery:A case study in Istanbul, Turkey. Water Air Soil Pollut,2007,183: 239-251.
[41]Eurico J D'Sa, Richard L Miller. Bio-optical Properties in Waters Influenced by the Mississippi River during Low Flow Conditions. Remote Sensing of Environment.2003,84:538-549.
[42]Fell F., Fischer J.. Numerical simulation of the light field in the atmosphere-ocean system using the matrix-operator method. Journal of Quantitative Spectroscopy & Radiative Transfer,2001,69:351-388.
[43]Fischer J. and Grassl H. Radiative transfer in an atmosphere-ocean system:an azimuthally dependent matrix operator approach. Appl. Opt.1984,23: 1032-1039.
[44]Fischer, J. (1985). On the information content of multispectral radiance measurements over an ocean. Int. J. Remote Sensing 6:773-786.
[45]Forget P, Broche P, Naudin J J. Reflectance sensitivity to solid suspended sediment stratification in coastal water and inversion:A case study. Remote Sensing of Environment,2001,77:92-103.
[46]Fougnie, B., R. Frouin, P. Lecomte and Pierre-Yves Deschamps,1999:Reduction of skylight reflection effects in the above-water measurement of diffuse marine reflectance. Appl. Opt.38:3844-3856.
[47]Frank E H et al. Inherent optical properties of the ocean. Retrieval of the absorption coefficient of chromophoric dissolved organic matter from fluorescence measurement. Linmal. Oceanogr.1993,38(7):1394-1402
[48]Gallegos C. L., Correll D. L. and Pierce J. W. Modeling spectral diffuse attenuation, absorption, and scattering coefficients in a turbid estuary. Limnol. Oceanogr.1990,35:1486-1502.
[49]Garver S A and Siegel, D A. Inherent optical properties inversion of ocean color spectra and its biogeochemical interpretation, I. Time series from the Sargasso Sea. J geophys Res,1997,102:18607.
[50]Gimond M. Description and verification of an aquatic optics Monte Carlo model. Environmental Modelling & Software,2004,19:1065-1076.
[51]Gitelson A., Garbuzov G., Szilagyi F., et al. Quantitative remote sensing methods for real-time monitoring of inland waters quality. International journal of remote sensing,1993,14(7):1269-1295.
[52]Gitelson, A. (1992). The peak near 700nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration. Int. J. Remote Sensing 13:3367-3373.
[53]Gordon H R and McCluney W R. Estimation of the depth of sunlight penetration in the sea for remote sensing
[54]Gordon H R, Boynton G C. Radiance-irradiance inversion algorithm for estimating the absorption and backscattering coefficients, of natural waters---homogeneous waters. Applied Optics,1997,36(12):2636-2641.
[55]Gordon H R, Morel A. Remote assessment of Ocean color for satellite visible imagery. A review, p1-114. In R. T. Barber, C. N. K. Mooers, M J. Bowman, and B. Zeizschel [eds.] Leture notes on coastal and estuarine studies. Springer-Verlag.
[56]Gordon H. R., Brown O. B., Evans R. H., et al. A semianalytic radiance model of ocean color. J. Geophys. Res.1988,93,10,909-10,924.
[57]Gordon H. R., Ship perturbation of irradiance measurements at sea.1:Monte Carlo simulations. Appl. Opt.1985,24,4172-4182.
[58]Gordon H.R.. Can the Lambert-Beer law be applied to the diffuse attenuation coefficient of ocean water? Limnol. Oceanogr.34,1389-1409 (1989).
[59]Gordon, H. R. and Boynton, G. C. (1998). Radiance-irradiance inversion algorithm for estimating the absorption and backscattering coefficients of natural waters:vertically stratified water bodies. Appl. Optics 37:3886-3896.
[60]Gordon, H. R. and Morel, A. (1983). Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery. A Review, Lecture Notes on Coastal and Estuarine Studies, R. T. Barber, N. K. Mooers, M. J. Bowman and B. Zeitzschel (eds.), Springer-Verlag, New York,114 p.
[61]Gordon, H.R. Influence of vertical stratification on the distribution of irradiance at the sea surface from a point source in the ocean.Applied Optics,1988,27: 2643-2645.
[62]Gould R W, Arnone R A and Martinolich P M. Spectral Dependence of the Scattering Coefficient in Case 1 and Case 2 Waters.1999,38(12):2377-2383.
[63]Haltrin, V I.. Self-consistent approach to the solution of the light transfer problem for irradiances in marine waters with arbitrary turbidity, depth, and surface illumination:I. Case of absorption and elastic scattering. Applied Optics,1998, 37 (18),3773-3784.
[64]Harma K, Vepsalainen J, Hannonen T, et al. Detection of water quality using simulated satellite data and semi-empirical algorithms in Finland. The Science of the Total Environment,2001,268:107-121.
[65]He M X, Hu L B, Wang Y F, et al. Depth and opticalproperties of water column retieved from MERIS data around the DongSha Atoll. Proc. Dragon 1 Programme Final Results 2004-2007, Beijing, P.R. China 21-25 April 2008.
[66]Hoepffner, N., and S. Sathyendranath. Effect of pigment composition on absorption properties of phytoplankton. Mar. Ecol. Prog. Ser.1991,73:11-23.
[67]Hoogenboom H J, Dekker A. G, and Althuis IJ A. Simulation of AVIRIS Sensitivity for Detecting Chlorophyll over Coastal and Inland Waters. Remote Sensing of Environment,1998,65(3):333-340
[68]Hu C M, Chen Z Q, Clayton T D, et al. Assessment of estuarine water-quality indicators using MODIS medium-resolution bands:Initial results from Tampa Bay, FL. Remote Sensing of Environment,2004,93:423-441.
[69]Hφjerslev, N. K. (1998). Spectral light absorption by gelbstoff in coastal waters displaying highly different concentrations. In:Proceedings, Ocean Optics XIV, S. G. Ackleson and J. Campbell (eds.), Office of Naval Research, Washington, DC.
[70]IOCCG (2000). Remote Sensing of Ocean Colour in Coastal, and Other Optically-Complex, Waters. Sathyendranath, S. (ed.), Reports of the International Ocean-Colour Coordinating Group, No.3, IOCCG, Dartmouth, Canada.
[71]Jerlov, N. G.. Marine Optics. Amsterdam:Elsevier,1976.
[72]Jerlov, N. G.. Optical studies of ocean water. Report Swedish Deep-Sea Expedition,1951,3:1-59.
[73]Jin Z. and Stamnes K., "Radiative transfer in nonuniformly refracting layered media:atmosphere-ocean system," Appl. Opt.33,431-442 (1994).
[74]Jin Z., Charlock T. P., Rutledge K., K. et al, "Analytical solution of radiative transfer in the coupled atmosphere-ocean system with a rough surface," Appl. Opt.45,7443-7455 (2006).
[75]Kattawar G. W. and Adams C. N., "Stokes vector calculations of the submarine light field in an atmosphereocean with scattering according to a Rayleigh phase matrix:effect of interface refractive index on radiance and polarization," Limnol. Oceanogr.1989,34,1453-1472.
[76]Keiner L E, Yan X H. A Neural Network Model for Estimating Sea Surface Chlorophyll and Sediments from Thematic Mapper Imagery. Remote sensing of Environment,1998,66:153-165.
[77]Kirk J T O. Dependence of relationship between inherent and apparent optical properties of water on solar altitude. Limnol Oceanogr,1984,29(2):350-356.
[78]Kirk J T O. Light and photosynthesis in aquatic ecosystem. Cambridge, Britain: Cambridge University Press,1994.47-144
[79]Kirk J. T. O.. Volume scattering function, average cosines, and the underwater light field. Limnol. Oceanogr.36,455-467 (1991)
[80]Kishino M, Tanaka A, Ishizaka J. Retrieval of Chlorophyll a, suspended solids, and colored dissolved organic matter in Tokyo Bay using ASTER data. Remote Sensing of Environment.2005,99:66-74.
[81]Kisselev V. B., Roberti L., and Perona G. Finite-element algorithm for radiative transfer in vertically inhomogeneous media--numerical scheme and applications. 1995, APPLIED OPTICS,34(36):8460-8471.
[82]Kopelevich,O. V. and Ershova, S. V. (1997). Model for seawater optical characteristics at UV spectral region. In:Ocean Optics XIII, S. G. Ackleson and R. Frouin (eds.), Proc. SPIE 2963, Washington, USA,167-172.
[83]Kopelevich, O. V., Lutsarev, S. V. and Rodionov, V. V. Light spectral absorption by yellow substance of ocean water (in Russian). Okeanologiya,1989,29: 409-414.
[84]Kou, L., D. Labrie and P. Chylek,1993:Refractive indices of water and ice in the 0.65 to 2.5 u m spectral range, Appl. Opt.,32:3531-3540.
[85]Lahet F., Ouillon S. and Forget P.. Colour classification of coastal waters of the Ebro river plume from spectral reflectances. International Journal of Remote Sensing,2001,22(9):1639-1664.
[86]Lee Z P, Carder K L, Arnone R A. Deriving inherent optical properties from water color:a multiband quasi-analytical algorithm for optically deep waters, Applied optics,2002,41(27):5755-5772.
[87]Lee Z P, Carder K L, Mobley C D et al. Hyperspectral Remote Sensing for Shallow Waters. I. A Semianalytical Model. Applied Optics,1998,37(27): 6329-6338.
[88]Lee Z P, Carder K L, Mobley C D et al. Hyperspectral remote sensing for shallow waters:2. Deriving bottom depths and water properties by optimization. Applied optics,1999,38(18):3831-3843.
[89]Lee Z. P. Visible-infrared remote-sensing model and applications for ocean waters Ph.D. dissertation Department of Marine Science, University of South Florida, St. Petersburg, Fla.,1994。
[90]Lee, Z. P., Carder, K. L., Peacock, T. G, Davis, C.0. and Mueller, J. L. (1996). Method to derive ocean absorption coefficients from remote-sensing reflectance. Appl. Optics 35:453-462.
[91]Lee, Z. P., K. L. Carder, and T. G. Peacock.1994b. Hyperspectral modeling of remote sensing reflectance:from the Florida Shelf to the Mississippi river. Eos Trans. AGU 75:193.
[92]Lee, Z.P., K.L. Carder, T.G. Peacock, and R.G Steward,1997b:Remote sensing reflectance measured with and without a vertical polarizer. In:Ocean Optics ⅩⅢ, S.G Ackleson, ed., Proc. SPIE 2693:483-488.
[93]Lee, Z.P., K.L. Carder, T.G. Peacock, C.O. Davis and J.L. Mueller,1997a: Remote-sensing reflectance and inherent optical properties of oceanic waters derived from above-water measurements. In:Ocean Optics ⅩⅢ, S.G. Ackleson, ed., Proc. SPIE 2693:160-166.
[94]Li Yan, Wei Huang, Ming Fang. An algorithm for the retrieval of suspended sediment in coastal waters of China from AVHRR data.Continental Shelf Reseach, 1998,18:487-500
[95]Lodhi M A, Rundquist D C, Han L H, et al.. Estimation of suspended sediment concentration in water using integrated surface reflectance. Geocarto International,1998,13(2):11-15.
[96]Loisel H, Morel A, Light scattering and chlorophyll concentration in case 1 waters:A reexamination. Limnol. Oceanogr.,43(5):847-858.
[97]Lyzenga D. R., "Passive remote-sensing techniques for mapping water depth and bottom features," Appl. Opt.17,379-883 (1978)
[98]Maritorena S., Morel A., and Gentili B., "Diffuse reflectance of oceanic shallow waters:influence of water depth and bottom albedo", Limnol. Oceanogr.39, 1689-1703(1994).
[99]Mobley C. D., Gentili B., Gordon H. R., et al. Comparison of numerical models for computing underwater light fields, Appl. Opt.32,7484-7504 (1993).
[100]Mobley C. D., Light and Water:Radiative Transfer in Natural Waters (Academic, San Diego, Calif.,1994).
[101]Mobley, C.D.,1999:Estimation of the remote-sensing reflectance from above-surface measurements. Appl. Opt.38:7442-7455
[102]Moore,G. K.. Satellite remote sensing of water turbidity. Hydrological sciences,1980,25(4):407-421.
[103]Morel A Y, Prieur L. Analysis of variations in ocean color. Limnology and Oceanography,1977,22(4):709
[104]Morel A, Belanger. Improved detection of turbid waters from ocean color sensors information. Remote Sensing of Environment,2006,102:237-249.
[105]Morel A. and Gentili B.. Diffuse reflectance of oceanic waters. Ⅱ. Bidirectional aspects. Appl. Opt.1993,32,6864-6879.
[106]Morel A. Bio-optical properties of oceanic waters:A reappraisal. Journal of Geophysical Research,2001,106(4):7163-7180.
[107]Morel, A. (1973). Diffusion.de la lumiere par les eaux de mer. Resultats expe rimentaux et approche theorique. In:AGARD Lecture Series No.61. Optics of the Sea (Interface and In-water Transmission and Imaging), North Atlantic Treaty Organisation, London,3.1.1-3.1.76.
[108]Morel, A. (1988). Optical modeling of the upper ocean in relation to its biogenous matter content (Case I waters). J. Geophys. Res.93:10,749-10,768.
[109]Morel, A. and Ahn, Y.-H. (1991). Optics of heterotrophic nanoflagellates and ciliates:A tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algalcells. J. Mar. Res.49:177-202.
[110]Morel, A.,1974:Optical properties of pure water and pure sea water. In: Optical Aspects of Oceanography, N.G. Jerlov and E.S. Nielson, Eds., pp1-23.
[111]Morel, A., and Prieur, L.. Analysis of variations in ocean color. Limnology and Oceanography,1977,22:709-722.
[112]Morel, In-water and remote measurements of ocean color. Boundary-layer Meteorol,18:177-201
[113]Mueller J L., Fargion G S. and McClain C R. Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume Ⅳ:Inherent Optical Properties:Instruments, Characterizations, Field Measurements and Data Analysis Protocols.2003
[114]Mueller J. L., Fargion G S., McClain C. R., et al. Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Revision 4, Volume Ⅲ:Radiometric Measurements and Data Analysis Methods. NASA/TM-2003-21621,2003.
[115]Mueller J. L., Fargion G S., McClain C. R., et al. Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Revision 4, Volume Ⅲ:Radiometric Measurements and Data Analysis Methods. NASA/TM-2003-21621,2003.
[116]Mueller J. L., Fargion G S., McClain C. R., et al. Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Revision 4, Volume Ⅳ:Inherent Optical Properties:Instruments, Characterization, Field Measurements and Data Analysis Protocols. NASA/TM-2003-211621/Rev4-Vol.Ⅳ
[117]Mueller, J. L. (1973). Influence of phytoplankton on ocean color spectra, Ph.D., School of Oceanography, Oregon State University, Corvallis, Oregon.
[118]Mueller, J. L. (1976). Ocean color measured off the Oregon Coast: characteristic vectors. Appl. Optics 15:394-402.
[119]Mueller, J.L., J.R.V. Zaneveld, S. Pegau, E. Valdez, H. Maske, S. Alvararez-Borrego and R. Lara-Lara,1997:Remote sensing reflectance: preliminary comparisons between in-water and above-water measurements, and estimates modeled from measured inherent optical properties, In:Ocean Optics XIII, S.G Ackleson, ed., Proc. SPIE 2693:502-507.
[120]Nakajima T., Tanaka M.. Effect of wind-generated waves on the transfer of solar radiation in the atmosphere-ocean system. Journal of Quantitative Spectroscopy & Radiative Transfer,1983,29:521-537.
[121]Ning, X., Vaulot D., Liu Z., et al. Standing stock and production of phytoplankton in the estuary of the Changjiang (the Yangtze River) and the adjacent East China Sea. Mar. Ecol. Pro. Ser.,1988,49:141-150.
[122]O'Neill N. T.and Miller J. R., "On calibration of passive optical bathymetry through depth soundings analysis and treatment of errors resulting from the spatial variation of environmental parameters," Int. J. Remote Sensing 10, 1481-1501 (1989)
[123]Ohde T. and Siegel H.. Correction of bottom influence in ocean colour satellite images of shallow water areas of the Baltic Sea. Int. J. Rem. Sens.2001, 22:297-313.
[124]Ouilion S. An inversion method for reflectance in stratified turbid waters. International journal of Remote Sensing,2003,24(3):535-558.
[125]Paredes J. M. and Spero R. E., "Water depth mapping from passive remote sensing data under a generalized ratio assumption," Appl. Opt.22,1134-1135 (1983)
[126]Petzold T J.Volume scattering functions for selected ocean waters.Tech Rep SIO 1972,72-78 (Scripps Institution of Oceanography Visibility Laboratory, San Diego, California.)
[127]Petzold, T.J., Volume scattering functions for selected natural waters, Scripps Institution of Oceanography, Visibility Laboratory, San Diego, CA, SIO Ref. 71-78,1972
[128]Philpot W. D. Radiative transfer in stratified waters:a single-scattering approximation for irradiance. Applied Optics,1987,26(19):4123-4132.
[129]Philpot W.D. and Ackleson S.G., "Remote sensing of optically shallow, vertically inhomogeneous waters:a mathematical model", Delaware Sea Grant Collage Program (DEL-SG-12-81),283-299 (1981).
[130]Pope, R.M. and E.S. Fry.1997:Absorption spectrum (380-700 nm) of pure water. Ⅱ. Integrating cavity measurements. Appl. Opt.36:8710-8723.
[131]Pozdnyakov D, Shuchman R, Korosov A. Operational algorithm for the retrieval of water quality in the Great Lakes. Remote Sensing of Environment, 2005,97:352-370.
[132]Pozdnyakov D., Lyaskovsky A., Grassl H., et al, Numerical modelling of transspectral processes in natural waters:implications for remote sensing," Int. J. Rem. Sens.23,1581-1607 (2002).
[133]Preisendorfer R W and Mobley C. D.. Direct and inverse irradiance models in hydrologic optics. Limnology and Oceanography,1984,29 (5):903-929.
[134]Preisendorfer R. W., Hydrologic Optics, Vol.1:Introduction, NTIS PB-259 793/8ST (National Technical Information Service, Springfield, Va.,1976).
[135]Preisendorfer, R.W.1960:Recommendation on the standardization of concepts, terminology and notation of hydrologic optics. Scripps Inst. Of Oceanogr., SIO Report,96pp.
[136]Prieur, L. and Sathyendranath, S. An optical classification of coastal and oceanic waters based on the specific spectral absorption curves of phytoplankton pigments, dissolved organic matter, and other particulate materials. Limnol. Oceanogr.1981,26:671-689.
[137]Reinersman P. N. and Carder K. L.. Monte Carlo simulation of the atmospheric point-spread function with an application to correction for the adjacency effect. Appl. Opt.1995,34,4453-4471.
[138]Roesler C S, Perrym J, Carder K L. Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters. Limnol Oceanogr,1989,34:1510-1523.
[139]Roesler, C. S. and Perry, M. J. (1995). In situ phytoplankton absorption, fluorescence emission, and particulate backscattering spectra determined from reflectance. J. Geophys. Res.100:13,279-13,294.
[140]Salinas S V, Chang C W, Liew S C. Multiparameter retrieval of water optical properties from above-water remote-sensing reflectance using the simulated annealing algorithm. Applied Optics,2007,46(14):2727-2742.
[141]Sathyendranath S. and Platt T.. Analytic model of ocean color. Appl. Opt. 1997,36,2620-2629.
[142]Sathyendranath S. and Morel A.. Light emerging from the sea interpretation and uses in remote sensing. In:Remote Sensing Applications in Marine Science and Technology, A. P. Cracknell (ed.), D. Reidel Publishing Company, Dordrecht, 1983:323-357.
[143]Sathyendranath, S. and Platt, T. Remote sensing of ocean chlorophyll: Consequence of non-uniform pigment profile. Appl. Optics,1989,28:490-495.
[144]Sathyendranath, S., Hoge, F. E., Platt, T. and Swift, R. N. (1994). Detection of phytoplankton pigments from ocean colour:Improved algorithms. Appl. Optics 33:1081-1089.
[145]Sathyendranath, S., Platt, T., Cota, G., Stuart, V. and Borstad, G. (1997a). Some Canadian experiments on modelling and interpreting ocean-colour data. In: 1st International Workshop on MOS-IRS and Ocean Colour, Berlin, April 28-30, 1997, Institute of Space Sensor Technology, DLR (ed.), Wissenschaft und Technik Verlag, Berlin.
[146]Sathyendranath, S., Prieur, L. and Morel, A. (1989). A three-component model of ocean colour and its application to remote sensing of phytoplankton pigments in coastal waters. Int. J. Remote Sensing 10:1373-1394.
[147]Schalles, J. F., Gitelson, A. A., Yacobi, Y. Z. and Kroenke, A. E. (1998). Estimation of chlorophyll a from time series measurements of high spectral resolution reflectance in an eutrophic lake. J. Phycol.34:383-390.
[148]Schiller H, Doerffer R. Neural network for emulation of an inverse model operational derivation of Case Ⅱ water properties from MERIS data. International Journal of Remote sensing,1999,20(9):1735-1746.
[149]Slade W.H.,Boss E.S.. Calibrated near-forward volume scattering function obtained from the volume LISST particle sizer. Optics Express,2006,14(8): 3602-3615
[150]Smith, R.C. and K.S. Baker,1981. Optical properties of the clearest natural waters (200-800 nm), Appl Opt.20 (2):177-184.
[151]Sogandares, F.M. and E.S. Fry,1997. Absorption spectrum (340-640 nm) of pure water. I. Photothermal measurements. Appl. Opt.,36(33):8699-8709.
[152]Stramski D, Mobley C D. Effects of microbial particles on oceanic optics:a database of single-particle optical properties. Limnology Oceanography,2004,42: 538-549
[153]Stramski, D. and Kiefer, D. A. (1991). Light scattering by microorganisms in the open ocean. Prog.Oceanogr.28:343-383.
[154]Sullivan, J.M., Twardowski M.S., Zaneveld J.R. V., et al. The hyperspectral temperature and salt dependencies of absorption by water and heavy water in the 400-750 nm spectral range. Applied Optics,2006,45 (21):5294-5309.
[155]Tanaka A, Kishino M, Doerffer R, et al. Development of a neural network algorithm for retrieving concentrations of chlorophyll, suspended matter and yellow substance from radiance data of the ocean color and temperature scanner. Journal of oceanography,2004,60:519-530.
[156]Tassan S. A procedure to determine the particular content of shallow water from Thematic Mapper data. International Journal of Remote Sensing,1998, 19(3):557-562.
[157]Tassan S. Local algorithms using SeaWiFS data for the retrieval of phytoplankton, pigments, suspended sediment, and yellow substance in coastal waters. APPLIED OPTICS,1994,33(12):2369-2378.
[158]Toole, D.A., D.A. Siegel, D.W. Menzies, M.J. Neumann and R.C. Smith, 2000:Remote-sensing reflectance determinations in the coastal ocean environment:impact of instrumental characteristics and environmental variability. Appl. Opt.39:456-468.
[159]Twardowski M, Boss E, Macdonald J B, et al. A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case Ⅰ and case Ⅱ waters J. Geophys Res, 2001,106:14129-14142.
[160]Tynes H. H., Kattawar G. W., Zege E. P., et al. Monte Carlo and multicomponent approximation methods for vector radiative transfer by use of effective Mueller matrix calculations. Appl. Opt.2001,40,400-412.
[161]Ulloa, O., Sathyendranath, S. and Platt, T. (1994). Effect of the particle-size distribution on the backscattering ratio in seawater. Appl. Optics 33:7070-7077.
[162]Ulloa, O., Sathyendranath, S., Platt, T. and Quines, R. A. (1992). Light scattering by marine heterotrophic bacteria. J. Geophys. Res.97:9619-9629.
[163]Unoki, S., Okami, N., Kishino, M. et al. Optical Characteristics of Sea Water at Tokyo Bay. Science and Technology Agency Report, Japan,1978.
[164]Van Zee, H., D. Hankins, and C. deLespinasse,2002:ac-9 Protocol Document (Revision F). WET Labs Inc., Philomath, OR,41pp.
[165]WETLabs, ECO VSF 3 User's Guide, Revision M.2007.
[166]WETLabs. Ac Meter Protocol Document. Revision N,2008.
[167]Whitlock C. H., Poole, L. R., Ursy, J. W, et al. Comparison of reflectance with backscatter for turbid waters. Appl. Optics,1981,20:517-522.
[168]Yan B H, Stamnes K. Fast yet accurate computation of the complete radiance distribution in the coupled atmosphere-ocean system. Journal of Quantitative Spectroscopy & Radiative Transfer,2003,76:207-223.
[169]Zege E. P., and Chaikovskaya L. I., "New approach to the polarized radiative transfer problem," J. Quant. Spectrosc. Radiat. Transfer 55,19-31 (1996).
[170]Zege E. P., Katsev I. L., and Polonsky I. N., "Multicomponent approach to light propagation in clouds and mists," Appl. Opt.32,2803-2812 (1993).
[171]Zhai P W, Hu Y X, Trepte C R.. A vector radiative transfer model for coupled atmosphere and ocean systems based on successive order of scattering method. OPTICS EXPRESS,2009,17(4):2057-2079.
[172]Zhai P. W., Kattawar G W and Yang P.. Impulse response solution to the three-dimensional vector radiative transfer equation in atmosphere-ocean systems. II. The hybrid matrix operator-Monte Carlo method. APPLIED OPTICS,2008, 47(8):1063-1071.
[173]Zhang Y, Pulliainen J, Koponen S, et al. Application of an empirical neural network to surface water quality estimation in the Gulf of Finland using combined optical data and microwave data. Remote Sensing of Environment, 2002,81:327-336.
[174]Zibordi G and Berthon J-F. Relationships between Q-factor and seawater optical properties in a coastal region. Limnology and Oceanography,2001,46(5): 1130-1140.
[175]曹文熙,杨跃忠,许晓强,等。珠江口悬浮颗粒物的吸收光谱及其区域模式。科学通报,2003,48(17)：1876-1882。
[176]曹文熙,杨跃忠。海洋光合有效辐射分布的计算模式。热带海洋学报,2002,21(3)：47-54。
[177]曹文熙,钟其英,杨跃忠。南海水色遥感的主因子分析。遥感学报,1999,3(2)：112-115
[178]长江水利委员会。2007年长江泥沙公报,2007。
[179]陈楚群,潘志林,施平。海水光谱模拟及其在黄色物质遥感反演中的应用,热带海洋学报,2003,22(5)：33-39
[180]陈吉余,沈焕庭,恽才兴,等。长江河口动力过程和地貌演变。上海：上海科学技术出版社,1988。
[181]陈吉余主编。21世纪的长江河口初探。北京：海洋出版社,2009
[182]陈鸣,李士鸿。应用Landsat和NOAA遥感资料联合监测杭州湾的悬浮泥沙。泥沙研究,1989,3：29-34。
[183]陈沈良,张国安,杨世伦等。长江口水域悬沙浓度时空变化与泥沙再悬浮。地理学报,2004,59(2)：260-266。
[184]陈涛,李武,吴曙初。悬浮泥沙浓度与光谱反射率峰值波长红移的相关关系。海洋学报,1994,16(1)：38-43。
[185]陈夏法。杭州湾悬浮泥沙多时相遥感分析。环境遥感,1989,4‘(2)：128-135。
[186]陈晓玲,吴忠宜,田礼乔,等。水体悬浮泥沙动态监测的遥感反演模型对比分析-以鄱阳湖为例。科技导报,2007,25(6)：19-22。
[187]陈晓玲,袁中智,李毓湘,等。基于遥感反演结果的悬浮泥沙时空动态规律研究——以珠江河口及邻近海域为例。武汉大学学报(信息科学版),2005,30(8)：677-681。
[188]陈晓翔,丁晓英。用FY-1D数据估算珠江口海域悬浮泥沙含量,2004,43(增刊)：194-196
[189]丛丕福,牛铮,曲丽梅,等。基于神经网络和TM图像的大连湾海域悬浮物质量浓度的反演。海洋科学,2005,29(4)：31-35。
[190]崔廷伟,张杰,马毅,等。渤海近岸水体后向散射系数反演模型。光学学报,2007,28(11)：2041-2045。
[191]崔廷伟,张杰,马毅,等。赤潮光谱特征及其形成机制。光谱学与光谱分析,2006,26(5)：884-886。
[192]戴志军,韩震,恽才兴,等。茂名海域水体表层悬浮泥沙浓度时空分布特征的遥感分析。海洋科学进展,2006,24(4)：455-462。
[193]邓孺孺,何执兼,陈晓翔。基于二次散射的水污染遥感模型及其在珠江口水域的应用。海洋学报,2003,25(6)：69-78。
[194]丁晓英,许祥向。应用遥感技术分析韩江河口悬沙的动态特征,国土资源遥感,2007,73(3)：71-73。
[195]段民征,吴北婴,吕达仁。海洋-大气耦合辐射传输模式。大气科学,1997,21(6)：734-742。
[196]樊辉,黄海军,唐军武。黄河口水体光谱特性及悬沙浓度遥感估测。武汉大学学报(信息科学版),2007,32(7)：601-604。
[197]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。海洋学报,1999,21(3)：134-140。
[198]高铎,方圣辉,张雪虎。基于遗传算法的东湖水质参数反演方法探讨。测绘信息与工程,2006,31(6)：42-44。
[199]巩彩兰,尹球,匡定波。黄浦江水质指标与反射光谱特征的关系分析。遥感学报,2006,10(6)：910-916
[200]顾艳镇,刘玉光,刘亚豪,等。渤海海区颗粒物的后向散射系数和光束散射系数统计关系研究。中国海洋大学学报,2007,37(增刊)：001-007。
[201]光洁,韦玉春,黄家柱,等。分季节的太湖悬浮物遥感估测模型研究。湖泊科学,2007,19(3)：241-249。
[202]光洁,韦玉春,黄家柱,等。模糊回归在太湖悬浮物反演中的应用。南京师大学报(自然科学版),2006,29(3)：113-117。
[203]郭琳,陈植华。椒江口-台州湾悬浮泥沙分布特征遥感研究。武汉理工大学学报,2007,29(5)：49-52。
[204]韩震,金亚秋，恽才兴。神舟三号CMODIS数据获取长江口悬浮泥沙含量的时空分布。遥感学报,2006,10(3)：381-38。
[205]韩震，恽才兴,蒋雪中。悬浮泥沙反射光谱特性实验研究。水利学报,2003,327(12)：118-122
[206]何青,恽才兴,时伟荣。长江口表层水体悬沙浓度场遥感分析。自然科学进展,1999,9(2)：160-164
[207]何贤强,潘德炉,白雁,等。基于矩阵算法的海洋-大气耦合矢量辐射传输数值计算模型。中国科学(D辑),2006,36(6)：860-870。
[208]何贤强,潘德炉,毛志华,等。利用SeaWiFS反演海水透明度的模式研 究。海洋学报,2004,26(5)：55-62。
[209]黄海军,李成治,郭建军。黄河口海域悬沙光谱特征的研究。海洋科学,1994,5：40-44。
[210]姜杰。利用遥感反演悬浮泥沙浓度的方法研究。海洋地质动态,2006,22(9)：32-34。
[211]孔德星,杨红,吴建辉。长江口海域黄色物质光吸收特性。海洋环境科学。2008,27.(6)：629-631。
[212]乐华福,林寿仁,赵太初。近海Ⅱ类海水反射率与表面悬浮泥沙相关性的研究。国土资源遥感,2000,43(1)：34-38
[213]雷惠,潘德炉,陶邦一,等。东海典型水体的黄色物质光谱吸收及分布特征。海洋学报,2009,31(2)：57-62。
[214]黎夏。悬浮物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,1992,7(2)：106-113。
[215]李凡.海岸带陆海相互作用(LOICZ)研究及我们的策略.地球科学进展,1996,11(1)：19-23。
[216]李洪灵,张鹰,姜杰。基于遥感方法反演悬浮泥沙分布。水科学进展,2006,17(2)242-245
[217]李金和,周振忠,张庆河。滨州港海域泥沙运动遥感图像分析。中国港湾建设,2007,148(2)：5-8。
[218]李京。利用NOAA卫星的AVHRR数据监测杭州湾海域的悬浮泥沙含量。海洋学报,1987,9(1)：132-136
[219]李京。水域悬浮物固体含量的遥感定量研究。环境科学学报,1986,6(2)： 166-173
[220]李四海,唐军武，恽才兴。河口悬浮泥沙浓度SeaWiFS遥感定量模式研究。海洋学报,2002,24(2)：51-58。
[221]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,遥感学报,2001,5(2)：154-160
[222]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,遥感学报,2001,5(2)：154-160
[223]李铜基,陈清莲,汪小勇,杨安安。剖面法测量近岸水体遥感反射率的新方法。海洋技术,2004,23(3)：1-5。
[224]李铜基,陈清莲,杨安安,等。黄东海春季水体后向散射系数的经验模型研究。海洋技术,2004,23(3)：10-14。
[225]李铜基,陈清莲。Ⅱ类水体光学特性的剖面测量方法。海洋技术,2003,22(3)1-5。
[226]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。科学通报,1999,44(17)：1892-1897。
[227]李云驹,常庆瑞,杨晓梅,等。长江口悬浮泥沙的MODIS影像遥感监测研究,西北农林科技大学学报(自然科学版),2005,33(4)：117-121
[228]李云梅,黄家柱,陆皖宁。基于分析模型的太湖悬浮物浓度遥感监测。海洋与湖沼,2006,37(2)：171-177。
[229]刘灿德,何报寅,李茂田。利用MODIS反演长江中游悬浮泥沙含量的初步研究。地质科技情报,2006,25(2)：99-102
[230]刘良明,张红梅。基于基于MODIS数据的悬浮泥沙定量遥感方法。国土资源遥感,2006,68(2)：42-45
[231]刘堂友,匡定波,尹球。湖泊藻类叶绿素-a和悬浮物浓度的高光谱定量遥感模型研究。红外与毫米波学报,2004,23(1)：11-15。
[232]刘炜,李铜基,朱建华,等。黄东海海区总悬浮物散射特性研究。海洋技术,2007,26(2)：42-46
[233]刘小丽,沈芳,朱伟建,等。MERIS卫星数据定量反演长江河口的悬沙浓度。长江流域资源与环境,2009,18(11)：1026-1030。
[234]刘小平,邓孺孺,彭晓鹃。悬浮泥沙定量遥感综合模式及其在珠江口的应用。中山大学学报(自然科学版),2005,44(3)：109-113。
[235]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。水利学报,2007,38(7)：799-805。
[236]刘子琳,宁修仁,蔡昱明。杭州湾——舟山渔场秋季浮游植物现存量和初级生产力。2001,23(2)：93-99。
[237]刘子琳,张涛,刘艳岚,等。2004年春季长江河口水体与沉积物表层的叶绿素a浓度分布。海洋学研究,2008,26(4)：1-7。
[238]吕恒,李新国,曹凯。基于BP神经网络模型的太湖悬浮物浓度遥感定量提取研究。武汉大学学报(信息科学版),2006,31(8)：683-686
[239]吕恒,李新国,江南。基于反射光谱和模拟MERIS数据的太湖悬浮物遥 感定量模型。湖泊科学,2005,17(2)：104-109
[240]马超飞,蒋兴伟,唐军武,等。HY-1 CCD宽波段水色要素反演算法。海洋学报,2005,27(4)：38-44。
[241]马荣华,戴锦芳。结合Landsat ETM与实测光谱估测太湖叶绿素及悬浮物含量。湖泊科学,2005,17(2)：97-103。
[242]宁修仁,库蒂。长江口及冲淡水区叶绿素a、细菌、ATP、POC及微生物呼吸作用速率之间的关系。海洋学报,1991,13(6)：831-837。
[243]潘德炉,李淑青,毛天明。卫星海洋水色遥感的辐射模式研究。海洋与湖沼,1997,28(6)：652-658。
[244]潘德炉,李淑青。卫星海洋水色遥感信息特征量的研究。遥感学报,1998,2(1)：26-31。
[245]沈焕庭,李九发,朱慧芳。长江河口悬沙输移特性。泥沙研究,1986(1)：1-13。
[246]沈焕庭.论我国海岸带陆海相互作用研究。海洋通报,1999,18(6)：11-17
[247]沈新强,胡方西。长江口外水域叶绿素a分布的基本特征。1995,2(1)：71-80。
[248]时伟荣,李九发。长江河口南北槽输沙机制及混浊带发育分析。海洋通报,1993,12(4)：71-76。
[249]时钟,凌鸿烈。长江口细颗粒悬沙浓度垂向分布。泥沙研究,1999,(2)：59-64。
[250]时钟,周洪强。长江口北槽口外悬沙浓度垂线分布的数学模拟。海洋工程,2000,18(3)：57-62。
[251]宋立松,陈武,向卫华,等。基于粗糙集的杭州湾含沙量遥感模型。水利学报,2004,5：58-63。
[252]宋立松,王稳来,陈武,等。钱塘江河口含沙量遥感模式探讨。浙江水利科技,2003,3：1-3。
[253]宋庆君,唐军武。黄海东海海区水体散射特性研究。海洋学报,2006,28(4)：56-63。
[254]宋书群,孙军,沈志良,等。三峡库区蓄水后夏季长江口及其邻近水域粒级叶绿素a。中国海洋大学学报,2006,36(Sup.)：114-120。
[255]宋书群,孙军,俞志明。长江口及其邻近水域叶绿素a的垂直格局及成因初析。植物生态学报,2009,33(2)：369-379。
[256]宋召军,黄海军,刘芳。南黄海辐射沙洲附近海域悬浮泥沙的遥感反演研究。高技术通讯,2006,16(11)：1185-1189。
[257]孙德勇,李云梅,王桥,等。不同浓度悬浮泥沙水体的光谱吸收特性模拟。地理与信息科学,2008,24(5)：16-20。
[258]唐军武,丁静,田纪委,等。黄东海二类水体三要素浓度反演的神经网络模型。高技术通讯,2005,15(3)：83-88。
[259]唐军武,马超飞,牛生丽,等。CBERS-02卫星CCD相机资料定量化反演水体成分初探。中国科学(E辑),2005,35(增刊Ⅰ)：156-170。
[260]唐军武,田国良,汪小勇。水体光谱测量与分析Ⅰ：水面以上测量法。遥感学报,2004,8(1)：37-44。
[261]唐军武,田国良。离水辐射非朗伯特性的Monte Carlo模拟及分析。海洋学报,2000,22,(2)：48-57。
[262]唐军武,王晓梅,宋庆君。黄、东海二类水体水色要素的统计反演模式。海洋科学进展,2004,22(增刊)：1-7
[263]童小华,谢欢,仇雁翎,等。基于多光谱遥感的水质监测处理方法与分析。同济大学学报(自然科学版),2007,35(5)：675-680。
[264]万新宁,李九发,沈焕庭。长江口外海滨悬沙分布及扩散特征。地理研究,2006,25(2)：294-302。
[265]汪小钦,王钦敏,邬群勇,等。遥感在悬浮物质浓度提取中的应用——以福建闽江口为例。遥感学报,2003,7(1)：54-57。
[266]汪小勇,李铜基,刘炜,等。黄东海表观光学量与固有光学量经验模式研究。海洋技术,2008,27(1)：58-64
[267]汪小勇,李铜基,唐军武。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。海洋技术,2004,23(2)：1-7
[268]王繁,周斌,徐建明,等。杭州湾混浊水体表面光谱测量及光谱特征分析。光谱学与光谱分析,2009,29(3)：730-734
[269]王繁,周斌,徐建明,等。基于实测光谱的杭州湾悬浮物浓度遥感反演模式,环境科学,2008,29(11)：3022-3026。
[270]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。 地理研究,2007,26(6)：
[271]王桂芬,曹文熙,许大志,等。南海北部海区非藻类颗粒物吸收系数的变化特性。海洋技术,2007,26(1)：45-49。
[272]王建平,程声通,贾海峰,等。用TM影像进行湖泊水色反演研究的人工神经网络模型。环境科学,2003,24(2)：73-76。
[273]王心源,李文达,严小华,等。基于LandsatTM/ETM+数据提取巢湖悬浮泥沙相对浓度的信息与空间分布变化。湖泊科学,2007,19(3)：255-260。
[274]温令平。伶仃洋悬浮泥沙遥感定量分析。水运工程,2001,332(9)：9-13
[275]吴传庆,王桥,王昌佐。去除叶绿素a影响的泥沙反演模型。中国环境监测,2009,25(2)：26-30。
[276]吴传庆,杨志峰,王桥,等。泥沙浓度的动态峰反演方法。遥感技术与应用,2008,23(5)：517-519。
[277]吴加学,张叔英,任来法.长江口北槽抛泥流速和悬沙浓度时空分布观测。海洋科学,2003,25(4)：91-103。
[278]吴敏,王学军。应用MODIS遥感数据监测巢湖水质。湖泊科学,2005,17(2)：110-113。
[279]吴荣军,吕瑞华,朱明远,等。海水混合和层化对叶绿素a垂直分布的影响。生态环境,2004,13(4)：515-519。
[280]邢小罡,赵冬至,刘玉光,等。渤海非色素颗粒物和黄色物质的吸收特性研究。海洋环境科学,2008,27(6)：595-598。
[281]徐京萍,张柏,蔺钰,等。结合高光谱数据反演吉林石头口门水库悬浮物含量和透明度。湖泊科学,2007,19(3)：269-274。
[282]徐京萍,张柏,宋开山,等。近红外波段二类水体悬浮物生物光学反演模型研究。光谱学与光谱分析,2008,28(10)：2273-2277。
[283]许珺,方红亮,傅肃性,等。运用SPOT数据进行河流水体悬浮固体浓度的研究-以台湾淡水河为例。遥感技术与应用。1999,14(4)：17-22。
[284]许晓强,曹文熙,杨跃忠。珠江口颗粒物吸收系数与盐度及叶绿素a浓度的关系。热带海洋学报,2004,23(5)：63-71。
[285]许勇,张鹰,张东。基于Hyperion影像的悬浮泥沙遥感监测研究。光学技术,2009,35(4)：622-625。
[286]阎福礼,王世新,周艺,等。利用Hyperion星载高光谱传感器监测太湖 水质的研究。红外与毫米波学报,2006,25(6)：
[287]阳锋,沈晓华,邹乐君。非线性函数拟合算法在遥感泥沙定量模式中的应用。遥感技术与应用,2003,18(3)：138-143。
[288]杨安安,李铜基,陈清莲,毕大勇。二类水体表观光学特性的测量与分析--剖面法方法研究。海洋技术,2005,26(3)111-115。
[289]杨伟,陈晋,松下文经。基于生物光学模型的水体叶绿素浓度反演算法。光谱学与光谱分析,2009,29(1)：.38-4。
[290]杨燕明,刘贞文,陈本清,等。用偏最小二乘法反演二类水体的水色要素。遥感学报,2005,9(2)：123-130。
[291]叶琳,徐涵秋。闽江流域福州段悬浮物浓度的遥感分析。遥感技术与应用。2006,21(6)：497-501。
[292]尹球,巩彩兰,匡定波,等。湖泊水质卫星遥感方法及其应用。红外与毫米波学报,2005,24(3)：198-202
[293]恽才兴,胡嘉敏,冯辉,等。河口悬浮泥沙遥感定量研究及其应用研究。见：遥感技术在海洋环境与资源调查中的开发研究成果汇编,北京：海洋出版社,1987,99-110。
[294]恽才兴。长江河口近期演变基本规律。北京：海洋出版社,2004。
[295]恽才兴。海岸带及近海卫星遥感综合应用技术。北京：海洋出版社,2004
[296]詹海刚,施平,陈楚群。基于贝叶斯反演理论的海水固有光学特性准分析算法。科学通报,2006,51(2)：204-210。
[297]詹海刚,施平,陈楚群。基于遗传算法的二类水体水色遥感反演。遥感学报,2004,8(1)：31-36
[298]张春桂,张星,陈敏艳,等。福建近岸海域悬浮泥沙浓度遥感定量监测研究。自然资源学报,2008,23(1)：150-160。
[299]张鉴,何晓雄,赵凤生。利用大气-海洋系统辐射传输模拟水色遥感信息量的变化特性。量子电子学报,2003,20(5)：623-628。
[300]张穗,陈慧娟,陈鹏霄。长江口水体表层泥沙含量遥感监测研究。长江科学院院报,2005,22(5)：23-25。
[301]张亭禄,邱国强。基于辐射传递模拟及人工神经网络技术的二类水体光学组分的反演。湖泊科学,2009,21(2)：173-181。
[302]张绪琴,吴永森,张士魁,等。胶州湾海水黄色物质荧光分布初步研究。 遥感学报,2002,6(3)：229-232。
[303]赵碧云,贺彬,朱云燕,等。滇池水体中总悬浮物含量的遥感定量模型。环境科学与技术,2001,94(2)：16-18
[304]赵洪波,钱敏。江苏如东附近海域泥沙运动遥感分析。水道港口,2004,25(1)：34-37。
[305]仲京臣,汪小勇,陈清莲。基于神经网络的黄东海春季二类水体三要素浓度反演方法。海洋技术,2005,24(4)：118-122
[306]周冠华,李京,杨一鹏。基于半分析算法的太湖水质参数多光谱遥感反演。自然灾害学报,2008,17(6)：142-146。
[307]周冠华,杨一鹏,陈军,等。基于叶绿素荧光峰特征的浑浊水体悬浮物浓度遥感反演。湖泊科学,2009,21(2)：272-279
[308]周良明,刘玉光,郭佩芳。渤海和北黄海水色光谱的特征分析。海洋通报,2005,24(2)：13-19。
[309]周伟华,袁翔城,霍文毅,等。长江口邻域叶绿素a和初级生产力的分布。海洋学报,2004,26(3)：143-150。
[310]朱建华,李铜基。黄东海非色素颗粒与黄色物质的吸收系数光谱模型研究。海洋技术,2004,23(2)：7-13。
[311]朱建华,李铜基。黄东海海区浮游植物色素吸收系数与叶绿素a浓度关系研究。海洋技术,2004,23(4)：117-122。
[312]朱建荣。长江口外海区叶绿素a浓度分布及其动力成因分析。中国科学(D辑),2004,34(8)：757-762。
[313]祝令亚,王世新,周艺,等。应用MODIS影像估测太湖水体悬浮物浓度。水科学进展,2007,18(3)：444-450。
[314]左书华,李九发,万新宁,等。长江河口悬沙浓度变化特征分析。泥沙研究,2006,(3)：68-75.
[315]左书华,杨华,赵群,赵洪波。温州海区近岸表层水体悬沙分布及运动规律的遥感分析。地理与地理信息科学,2007,23(2)：47-50。
[2]Agrawal, Y.C. The optical volume scattering function:Temporal and vertical variability in the water column off the New Jersey coast. Limnol. Oceanogr., 2005,50(6):1787-1794
[3]Albert A and Gege P. Inversion of irradiance and remote sensing reflectance in shallow water between 400 and 800 nm for calculations of water and bottom properties. Applied Optics,2006,45(10):2331-2343.
[4]Albert A., Mobley C. D. An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters. Optics express, 2003,11(22):2873-2890.
[5]Austin, R.W. and G. Halikas,1976:The index of refraction of seawater. SIO Ref. 76-1, Vis. Lab., Scripps Inst. Of Oceanography, La Jolla, California,64pp.
[6]Austin, R.W.,1974:Inherent spectral radiance signatures of the ocean surface. In: S.Q. Duntley, R.W. Austin, W.H. Wilson, C.F. Edgerton, and S.W. Moran, Ocean Color Analysis, SIO Ref.74-10, Scripps Institution of Oceanography, La Jolla, CA.
[7]Babin M., Stramski D., Ferrari G. M., et al.. Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe. Journal Geophysical Research,108,3211 (2003), doi:10.1029/2001JC000882.
[8]Bates D E, Porter J N. AO3D:A Monte Carlo code for modeling of environmental light propagation. Journal of Quantitative Spectroscopy & Radiative Transfer,2008,109:1802-1814
[9]Beardsley, GF. and J.R.V. Zaneveld,1969:Theoretical dependence of the near-asymptotic apparent optical properties on the Inherent Optical Properties of sea water. J. Opt. Soc. Amer.59:373-377.
[10]Bowers D G, Harker G E L, Stephan B. Absorption spectra of inorganic particles in the Irish Sea and their relevance to remote sensing of chlorophyll. International Journal of Remote Sensing,1996,17:2449-2460.
[11]Bricaud A, Morel A, Babin M, et al. Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters:Analysis and implications for bio-optical models. Journal of Geophysical Research,1998, 103(C13):31033-31044.
[12]Bricaud A., Morel A. and Prieur L.. Optical efficiency factors of some phytoplankters. Limnol. Oceanogr.,1983,28:816-832.
[13]Bricaud A., Morel A. and Prieur, L.. Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains. Limnol. Oceanogr. 1981,26:43-53.
[14]Bukata R. P., Jerome J. H., Kondratyev K. Y., et al. Optical Properties and Remote Sensing of Inland and Coastal Waters, CRC Press, Inc., Boca Raton, Florida,1995,362 p.
[15]Bukata, R. P., Bruton, J. E., Jerome, J. H., Jain, S. C. and Zwick, H. H. (1981a). Optical water quality model of Lake Ontario.2. Determination of chlorophyll a and suspended mineral concentrations of natural waters from submersible and low altitude remote sensors. Appl. Optics 20:1704-1714.
[16]Bukata, R. P., Jerome, J. H., Bruton, J. E., Jain, S. C. and Zwick, H. H.. Optical water quality model of Lake Ontario.1. Determination of the optical cross sections of organic and inorganic particulates in Lake Ontario. Appl. Optics, 1981b,20:1696-1703.
[17]Bukata, R. P., Jerome, J. H., Kondratyev, K. Y. and Pozdnyakov, D. V. (1991). Satellite monitoring of optically-active components of inland waters:an essential input to regional climate change impact studies. J. Great Lakes Res 17:470-478.
[18]Bulgarelli B., Kisselev V. B., and Roberti L. Radiative Transfer in the Atmosphere-Ocean System:The Finite-Element Method. Appl. Opt.1999,38: 1530-1542.
[19]Carder, K. L., Chen, F. R., Lee, Z. P., et al. Semianalytic Moderate-Resolution Imaging Spectrometer algorithms for chlorophyll a and absorption with bio-optical domains based on nitrate-depletion temperatures. J. Geophys. Res., 1999,104:5403-5421.
[20]Carder, K. L., S. K. Hawes, and Z. P. Lee.1994. SeaWiFS algorithm for chlorophyll a and colored dissolved organic matter in a subtropical environment. SeaWiFS working group report.
[21]Carder, K. L., Steward, R. G., Harvey, G. R. and Ortner, P. B. (1989). Marine humic and fulvic acids:Their effect on remote sensing of ocean chlorophyll. Limnol. Oceanogr.34:68-81.
[22]Carpenter D J, Carpenter S M. Modeling inland water quality using LANDSAT data. Remote Sensing of Environment,1983,13:345-352.
[23]Chami M and Robilliard D. Inversion of Oceanic Constituents in Case I and II Waters with Genetic Programming Algorithms. Applied Optics,2002,41(30): 6260-6275.
[24]Chami M. Importance of the polarization in the retrieval of oceanic constituents from the remote sensing reflectance. Journal of Geophysical Research,2007,112, C05026:1-13.
[25]Chami M, Santer R, and Dilligeard E. Radiative transfer model for the computation of radiance and polarization in an ocean-atmosphere system: polarization properties of suspended matter for remote sensing, Appl. Opt.40, 2398-2416 (2001),
[26]Chang C H, Liu C C, Wen C G. Integrating semianalytical and genetic algorithms to retrieve the constituents of water bodies from remote sensing of ocean color. Optics Express,2007,15(2):252-265.
[27]Chowdhary J., Cairns B., and Travis L. D. Contribution of water-leaving radiances to multiangle, multispectral polarimetric observations over the open ocean:bio-optical model results for case 1 waters, Appl. Opt.45,5542-5567 (2006)
[28]Cococcioni M, Lazzerini B, Marcelloni F. Estimating the concentration of optically active constituents of sea water by Takagi-Sugeno models with quadratic rule consequents. Pattern Recognition,2007,40:2846-2860
[29]Defoin-Platel M, Chami M. How ambiguous is the inverse problem of ocean color in coastal waters. Journal of Geophysical Research,2007,112:1-16
[30]Dekker A G, Vos R J, Peters S W M. Comparison of remote sensing data, model results and in situ data for total suspended matter (TSM) in the southern Frisian lakes. The Science of the Total Environment 2001,268:197-214.
[31]Dekker, A. G, Malthus, T. J. and Seyhan, E. (1991). Quantitative modeling of inland water quality for high-resolution MSS systems. IEEE Trans. Geosci. Remote Sens.29:89-95.
[32]Devred E, Dubuisson P and Chami M. Radiative transfer code:Application to the calculation of PAR. Proc. Indian Acad. Sci. (Earth Planet. Sci.),2000,109(4): 407-413.
[33]Doerffer R. and Schiller H.. The MERIS Case 2 water algorithm. International Journal of Remote Sensing,2007,28(3)-4:517-535.
[34]Doerffer, R. and Fischer, J. (1994). Concentrations of chlorophyll, suspended matter, and gelbstoff in case II waters derived from satellite coastal zone color scanner data with inverse modeling methods. J. Geophys. Res.99:7457-7466.
[35]Doxaran D, Cherukuru N and Lavender S J. Apparent and inherent optical properties of turbid estuarine waters_measurements, empirical quantification relationships, and modeling. Applied Optics,2006,45(10):2310-2324.
[36]Doxaran D, Cherukuru R C N, and Lavender S J. Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters. International Journal of Remote Sensing,2005,26(8):1763-1769.
[37]Doxaran D, Froidefond J M, Castaing P. A reflectance band ratio used to estimate suspended matter concentrations in coastal sediment-dominated waters. International Journal of Remote Sensing,2002,23(23):5079-5085.
[38]Doxaran D, Froidefond J M, Castaing P. Remote-Sensing reflectance of turbid ediment-dominated waters. Reduction of sediment type Variations and changing illumination conditions effects by use of reflectance ratios. Applied Optics,2003, 42(15):2623-2634.
[39]Doxaran D, Froidefond J M, Lavender S, et al. Spectral signature of highly turbid waters Application with SPOT data to quantify suspended particulate matter concentrations. Remote Sensing of Environment,2002,81:149-161.
[40]Ekercin S. Water quality retrievals from high resolution IKONOS multispectral imagery:A case study in Istanbul, Turkey. Water Air Soil Pollut,2007,183: 239-251.
[41]Eurico J D'Sa, Richard L Miller. Bio-optical Properties in Waters Influenced by the Mississippi River during Low Flow Conditions. Remote Sensing of Environment.2003,84:538-549.
[42]Fell F., Fischer J.. Numerical simulation of the light field in the atmosphere-ocean system using the matrix-operator method. Journal of Quantitative Spectroscopy & Radiative Transfer,2001,69:351-388.
[43]Fischer J. and Grassl H. Radiative transfer in an atmosphere-ocean system:an azimuthally dependent matrix operator approach. Appl. Opt.1984,23: 1032-1039.
[44]Fischer, J. (1985). On the information content of multispectral radiance measurements over an ocean. Int. J. Remote Sensing 6:773-786.
[45]Forget P, Broche P, Naudin J J. Reflectance sensitivity to solid suspended sediment stratification in coastal water and inversion:A case study. Remote Sensing of Environment,2001,77:92-103.
[46]Fougnie, B., R. Frouin, P. Lecomte and Pierre-Yves Deschamps,1999:Reduction of skylight reflection effects in the above-water measurement of diffuse marine reflectance. Appl. Opt.38:3844-3856.
[47]Frank E H et al. Inherent optical properties of the ocean. Retrieval of the absorption coefficient of chromophoric dissolved organic matter from fluorescence measurement. Linmal. Oceanogr.1993,38(7):1394-1402
[48]Gallegos C. L., Correll D. L. and Pierce J. W. Modeling spectral diffuse attenuation, absorption, and scattering coefficients in a turbid estuary. Limnol. Oceanogr.1990,35:1486-1502.
[49]Garver S A and Siegel, D A. Inherent optical properties inversion of ocean color spectra and its biogeochemical interpretation, I. Time series from the Sargasso Sea. J geophys Res,1997,102:18607.
[50]Gimond M. Description and verification of an aquatic optics Monte Carlo model. Environmental Modelling & Software,2004,19:1065-1076.
[51]Gitelson A., Garbuzov G., Szilagyi F., et al. Quantitative remote sensing methods for real-time monitoring of inland waters quality. International journal of remote sensing,1993,14(7):1269-1295.
[52]Gitelson, A. (1992). The peak near 700nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration. Int. J. Remote Sensing 13:3367-3373.
[53]Gordon H R and McCluney W R. Estimation of the depth of sunlight penetration in the sea for remote sensing
[54]Gordon H R, Boynton G C. Radiance-irradiance inversion algorithm for estimating the absorption and backscattering coefficients, of natural waters---homogeneous waters. Applied Optics,1997,36(12):2636-2641.
[55]Gordon H R, Morel A. Remote assessment of Ocean color for satellite visible imagery. A review, p1-114. In R. T. Barber, C. N. K. Mooers, M J. Bowman, and B. Zeizschel [eds.] Leture notes on coastal and estuarine studies. Springer-Verlag.
[56]Gordon H. R., Brown O. B., Evans R. H., et al. A semianalytic radiance model of ocean color. J. Geophys. Res.1988,93,10,909-10,924.
[57]Gordon H. R., Ship perturbation of irradiance measurements at sea.1:Monte Carlo simulations. Appl. Opt.1985,24,4172-4182.
[58]Gordon H.R.. Can the Lambert-Beer law be applied to the diffuse attenuation coefficient of ocean water? Limnol. Oceanogr.34,1389-1409 (1989).
[59]Gordon, H. R. and Boynton, G. C. (1998). Radiance-irradiance inversion algorithm for estimating the absorption and backscattering coefficients of natural waters:vertically stratified water bodies. Appl. Optics 37:3886-3896.
[60]Gordon, H. R. and Morel, A. (1983). Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery. A Review, Lecture Notes on Coastal and Estuarine Studies, R. T. Barber, N. K. Mooers, M. J. Bowman and B. Zeitzschel (eds.), Springer-Verlag, New York,114 p.
[61]Gordon, H.R. Influence of vertical stratification on the distribution of irradiance at the sea surface from a point source in the ocean.Applied Optics,1988,27: 2643-2645.
[62]Gould R W, Arnone R A and Martinolich P M. Spectral Dependence of the Scattering Coefficient in Case 1 and Case 2 Waters.1999,38(12):2377-2383.
[63]Haltrin, V I.. Self-consistent approach to the solution of the light transfer problem for irradiances in marine waters with arbitrary turbidity, depth, and surface illumination:I. Case of absorption and elastic scattering. Applied Optics,1998, 37 (18),3773-3784.
[64]Harma K, Vepsalainen J, Hannonen T, et al. Detection of water quality using simulated satellite data and semi-empirical algorithms in Finland. The Science of the Total Environment,2001,268:107-121.
[65]He M X, Hu L B, Wang Y F, et al. Depth and opticalproperties of water column retieved from MERIS data around the DongSha Atoll. Proc. Dragon 1 Programme Final Results 2004-2007, Beijing, P.R. China 21-25 April 2008.
[66]Hoepffner, N., and S. Sathyendranath. Effect of pigment composition on absorption properties of phytoplankton. Mar. Ecol. Prog. Ser.1991,73:11-23.
[67]Hoogenboom H J, Dekker A. G, and Althuis IJ A. Simulation of AVIRIS Sensitivity for Detecting Chlorophyll over Coastal and Inland Waters. Remote Sensing of Environment,1998,65(3):333-340
[68]Hu C M, Chen Z Q, Clayton T D, et al. Assessment of estuarine water-quality indicators using MODIS medium-resolution bands:Initial results from Tampa Bay, FL. Remote Sensing of Environment,2004,93:423-441.
[69]Hφjerslev, N. K. (1998). Spectral light absorption by gelbstoff in coastal waters displaying highly different concentrations. In:Proceedings, Ocean Optics XIV, S. G. Ackleson and J. Campbell (eds.), Office of Naval Research, Washington, DC.
[70]IOCCG (2000). Remote Sensing of Ocean Colour in Coastal, and Other Optically-Complex, Waters. Sathyendranath, S. (ed.), Reports of the International Ocean-Colour Coordinating Group, No.3, IOCCG, Dartmouth, Canada.
[71]Jerlov, N. G.. Marine Optics. Amsterdam:Elsevier,1976.
[72]Jerlov, N. G.. Optical studies of ocean water. Report Swedish Deep-Sea Expedition,1951,3:1-59.
[73]Jin Z. and Stamnes K., "Radiative transfer in nonuniformly refracting layered media:atmosphere-ocean system," Appl. Opt.33,431-442 (1994).
[74]Jin Z., Charlock T. P., Rutledge K., K. et al, "Analytical solution of radiative transfer in the coupled atmosphere-ocean system with a rough surface," Appl. Opt.45,7443-7455 (2006).
[75]Kattawar G. W. and Adams C. N., "Stokes vector calculations of the submarine light field in an atmosphereocean with scattering according to a Rayleigh phase matrix:effect of interface refractive index on radiance and polarization," Limnol. Oceanogr.1989,34,1453-1472.
[76]Keiner L E, Yan X H. A Neural Network Model for Estimating Sea Surface Chlorophyll and Sediments from Thematic Mapper Imagery. Remote sensing of Environment,1998,66:153-165.
[77]Kirk J T O. Dependence of relationship between inherent and apparent optical properties of water on solar altitude. Limnol Oceanogr,1984,29(2):350-356.
[78]Kirk J T O. Light and photosynthesis in aquatic ecosystem. Cambridge, Britain: Cambridge University Press,1994.47-144
[79]Kirk J. T. O.. Volume scattering function, average cosines, and the underwater light field. Limnol. Oceanogr.36,455-467 (1991)
[80]Kishino M, Tanaka A, Ishizaka J. Retrieval of Chlorophyll a, suspended solids, and colored dissolved organic matter in Tokyo Bay using ASTER data. Remote Sensing of Environment.2005,99:66-74.
[81]Kisselev V. B., Roberti L., and Perona G. Finite-element algorithm for radiative transfer in vertically inhomogeneous media--numerical scheme and applications. 1995, APPLIED OPTICS,34(36):8460-8471.
[82]Kopelevich,O. V. and Ershova, S. V. (1997). Model for seawater optical characteristics at UV spectral region. In:Ocean Optics XIII, S. G. Ackleson and R. Frouin (eds.), Proc. SPIE 2963, Washington, USA,167-172.
[83]Kopelevich, O. V., Lutsarev, S. V. and Rodionov, V. V. Light spectral absorption by yellow substance of ocean water (in Russian). Okeanologiya,1989,29: 409-414.
[84]Kou, L., D. Labrie and P. Chylek,1993:Refractive indices of water and ice in the 0.65 to 2.5 u m spectral range, Appl. Opt.,32:3531-3540.
[85]Lahet F., Ouillon S. and Forget P.. Colour classification of coastal waters of the Ebro river plume from spectral reflectances. International Journal of Remote Sensing,2001,22(9):1639-1664.
[86]Lee Z P, Carder K L, Arnone R A. Deriving inherent optical properties from water color:a multiband quasi-analytical algorithm for optically deep waters, Applied optics,2002,41(27):5755-5772.
[87]Lee Z P, Carder K L, Mobley C D et al. Hyperspectral Remote Sensing for Shallow Waters. I. A Semianalytical Model. Applied Optics,1998,37(27): 6329-6338.
[88]Lee Z P, Carder K L, Mobley C D et al. Hyperspectral remote sensing for shallow waters:2. Deriving bottom depths and water properties by optimization. Applied optics,1999,38(18):3831-3843.
[89]Lee Z. P. Visible-infrared remote-sensing model and applications for ocean waters Ph.D. dissertation Department of Marine Science, University of South Florida, St. Petersburg, Fla.,1994。
[90]Lee, Z. P., Carder, K. L., Peacock, T. G, Davis, C.0. and Mueller, J. L. (1996). Method to derive ocean absorption coefficients from remote-sensing reflectance. Appl. Optics 35:453-462.
[91]Lee, Z. P., K. L. Carder, and T. G. Peacock.1994b. Hyperspectral modeling of remote sensing reflectance:from the Florida Shelf to the Mississippi river. Eos Trans. AGU 75:193.
[92]Lee, Z.P., K.L. Carder, T.G. Peacock, and R.G Steward,1997b:Remote sensing reflectance measured with and without a vertical polarizer. In:Ocean Optics ⅩⅢ, S.G Ackleson, ed., Proc. SPIE 2693:483-488.
[93]Lee, Z.P., K.L. Carder, T.G. Peacock, C.O. Davis and J.L. Mueller,1997a: Remote-sensing reflectance and inherent optical properties of oceanic waters derived from above-water measurements. In:Ocean Optics ⅩⅢ, S.G. Ackleson, ed., Proc. SPIE 2693:160-166.
[94]Li Yan, Wei Huang, Ming Fang. An algorithm for the retrieval of suspended sediment in coastal waters of China from AVHRR data.Continental Shelf Reseach, 1998,18:487-500
[95]Lodhi M A, Rundquist D C, Han L H, et al.. Estimation of suspended sediment concentration in water using integrated surface reflectance. Geocarto International,1998,13(2):11-15.
[96]Loisel H, Morel A, Light scattering and chlorophyll concentration in case 1 waters:A reexamination. Limnol. Oceanogr.,43(5):847-858.
[97]Lyzenga D. R., "Passive remote-sensing techniques for mapping water depth and bottom features," Appl. Opt.17,379-883 (1978)
[98]Maritorena S., Morel A., and Gentili B., "Diffuse reflectance of oceanic shallow waters:influence of water depth and bottom albedo", Limnol. Oceanogr.39, 1689-1703(1994).
[99]Mobley C. D., Gentili B., Gordon H. R., et al. Comparison of numerical models for computing underwater light fields, Appl. Opt.32,7484-7504 (1993).
[100]Mobley C. D., Light and Water:Radiative Transfer in Natural Waters (Academic, San Diego, Calif.,1994).
[101]Mobley, C.D.,1999:Estimation of the remote-sensing reflectance from above-surface measurements. Appl. Opt.38:7442-7455
[102]Moore,G. K.. Satellite remote sensing of water turbidity. Hydrological sciences,1980,25(4):407-421.
[103]Morel A Y, Prieur L. Analysis of variations in ocean color. Limnology and Oceanography,1977,22(4):709
[104]Morel A, Belanger. Improved detection of turbid waters from ocean color sensors information. Remote Sensing of Environment,2006,102:237-249.
[105]Morel A. and Gentili B.. Diffuse reflectance of oceanic waters. Ⅱ. Bidirectional aspects. Appl. Opt.1993,32,6864-6879.
[106]Morel A. Bio-optical properties of oceanic waters:A reappraisal. Journal of Geophysical Research,2001,106(4):7163-7180.
[107]Morel, A. (1973). Diffusion.de la lumiere par les eaux de mer. Resultats expe rimentaux et approche theorique. In:AGARD Lecture Series No.61. Optics of the Sea (Interface and In-water Transmission and Imaging), North Atlantic Treaty Organisation, London,3.1.1-3.1.76.
[108]Morel, A. (1988). Optical modeling of the upper ocean in relation to its biogenous matter content (Case I waters). J. Geophys. Res.93:10,749-10,768.
[109]Morel, A. and Ahn, Y.-H. (1991). Optics of heterotrophic nanoflagellates and ciliates:A tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algalcells. J. Mar. Res.49:177-202.
[110]Morel, A.,1974:Optical properties of pure water and pure sea water. In: Optical Aspects of Oceanography, N.G. Jerlov and E.S. Nielson, Eds., pp1-23.
[111]Morel, A., and Prieur, L.. Analysis of variations in ocean color. Limnology and Oceanography,1977,22:709-722.
[112]Morel, In-water and remote measurements of ocean color. Boundary-layer Meteorol,18:177-201
[113]Mueller J L., Fargion G S. and McClain C R. Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume Ⅳ:Inherent Optical Properties:Instruments, Characterizations, Field Measurements and Data Analysis Protocols.2003
[114]Mueller J. L., Fargion G S., McClain C. R., et al. Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Revision 4, Volume Ⅲ:Radiometric Measurements and Data Analysis Methods. NASA/TM-2003-21621,2003.
[115]Mueller J. L., Fargion G S., McClain C. R., et al. Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Revision 4, Volume Ⅲ:Radiometric Measurements and Data Analysis Methods. NASA/TM-2003-21621,2003.
[116]Mueller J. L., Fargion G S., McClain C. R., et al. Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Revision 4, Volume Ⅳ:Inherent Optical Properties:Instruments, Characterization, Field Measurements and Data Analysis Protocols. NASA/TM-2003-211621/Rev4-Vol.Ⅳ
[117]Mueller, J. L. (1973). Influence of phytoplankton on ocean color spectra, Ph.D., School of Oceanography, Oregon State University, Corvallis, Oregon.
[118]Mueller, J. L. (1976). Ocean color measured off the Oregon Coast: characteristic vectors. Appl. Optics 15:394-402.
[119]Mueller, J.L., J.R.V. Zaneveld, S. Pegau, E. Valdez, H. Maske, S. Alvararez-Borrego and R. Lara-Lara,1997:Remote sensing reflectance: preliminary comparisons between in-water and above-water measurements, and estimates modeled from measured inherent optical properties, In:Ocean Optics XIII, S.G Ackleson, ed., Proc. SPIE 2693:502-507.
[120]Nakajima T., Tanaka M.. Effect of wind-generated waves on the transfer of solar radiation in the atmosphere-ocean system. Journal of Quantitative Spectroscopy & Radiative Transfer,1983,29:521-537.
[121]Ning, X., Vaulot D., Liu Z., et al. Standing stock and production of phytoplankton in the estuary of the Changjiang (the Yangtze River) and the adjacent East China Sea. Mar. Ecol. Pro. Ser.,1988,49:141-150.
[122]O'Neill N. T.and Miller J. R., "On calibration of passive optical bathymetry through depth soundings analysis and treatment of errors resulting from the spatial variation of environmental parameters," Int. J. Remote Sensing 10, 1481-1501 (1989)
[123]Ohde T. and Siegel H.. Correction of bottom influence in ocean colour satellite images of shallow water areas of the Baltic Sea. Int. J. Rem. Sens.2001, 22:297-313.
[124]Ouilion S. An inversion method for reflectance in stratified turbid waters. International journal of Remote Sensing,2003,24(3):535-558.
[125]Paredes J. M. and Spero R. E., "Water depth mapping from passive remote sensing data under a generalized ratio assumption," Appl. Opt.22,1134-1135 (1983)
[126]Petzold T J.Volume scattering functions for selected ocean waters.Tech Rep SIO 1972,72-78 (Scripps Institution of Oceanography Visibility Laboratory, San Diego, California.)
[127]Petzold, T.J., Volume scattering functions for selected natural waters, Scripps Institution of Oceanography, Visibility Laboratory, San Diego, CA, SIO Ref. 71-78,1972
[128]Philpot W. D. Radiative transfer in stratified waters:a single-scattering approximation for irradiance. Applied Optics,1987,26(19):4123-4132.
[129]Philpot W.D. and Ackleson S.G., "Remote sensing of optically shallow, vertically inhomogeneous waters:a mathematical model", Delaware Sea Grant Collage Program (DEL-SG-12-81),283-299 (1981).
[130]Pope, R.M. and E.S. Fry.1997:Absorption spectrum (380-700 nm) of pure water. Ⅱ. Integrating cavity measurements. Appl. Opt.36:8710-8723.
[131]Pozdnyakov D, Shuchman R, Korosov A. Operational algorithm for the retrieval of water quality in the Great Lakes. Remote Sensing of Environment, 2005,97:352-370.
[132]Pozdnyakov D., Lyaskovsky A., Grassl H., et al, Numerical modelling of transspectral processes in natural waters:implications for remote sensing," Int. J. Rem. Sens.23,1581-1607 (2002).
[133]Preisendorfer R W and Mobley C. D.. Direct and inverse irradiance models in hydrologic optics. Limnology and Oceanography,1984,29 (5):903-929.
[134]Preisendorfer R. W., Hydrologic Optics, Vol.1:Introduction, NTIS PB-259 793/8ST (National Technical Information Service, Springfield, Va.,1976).
[135]Preisendorfer, R.W.1960:Recommendation on the standardization of concepts, terminology and notation of hydrologic optics. Scripps Inst. Of Oceanogr., SIO Report,96pp.
[136]Prieur, L. and Sathyendranath, S. An optical classification of coastal and oceanic waters based on the specific spectral absorption curves of phytoplankton pigments, dissolved organic matter, and other particulate materials. Limnol. Oceanogr.1981,26:671-689.
[137]Reinersman P. N. and Carder K. L.. Monte Carlo simulation of the atmospheric point-spread function with an application to correction for the adjacency effect. Appl. Opt.1995,34,4453-4471.
[138]Roesler C S, Perrym J, Carder K L. Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters. Limnol Oceanogr,1989,34:1510-1523.
[139]Roesler, C. S. and Perry, M. J. (1995). In situ phytoplankton absorption, fluorescence emission, and particulate backscattering spectra determined from reflectance. J. Geophys. Res.100:13,279-13,294.
[140]Salinas S V, Chang C W, Liew S C. Multiparameter retrieval of water optical properties from above-water remote-sensing reflectance using the simulated annealing algorithm. Applied Optics,2007,46(14):2727-2742.
[141]Sathyendranath S. and Platt T.. Analytic model of ocean color. Appl. Opt. 1997,36,2620-2629.
[142]Sathyendranath S. and Morel A.. Light emerging from the sea interpretation and uses in remote sensing. In:Remote Sensing Applications in Marine Science and Technology, A. P. Cracknell (ed.), D. Reidel Publishing Company, Dordrecht, 1983:323-357.
[143]Sathyendranath, S. and Platt, T. Remote sensing of ocean chlorophyll: Consequence of non-uniform pigment profile. Appl. Optics,1989,28:490-495.
[144]Sathyendranath, S., Hoge, F. E., Platt, T. and Swift, R. N. (1994). Detection of phytoplankton pigments from ocean colour:Improved algorithms. Appl. Optics 33:1081-1089.
[145]Sathyendranath, S., Platt, T., Cota, G., Stuart, V. and Borstad, G. (1997a). Some Canadian experiments on modelling and interpreting ocean-colour data. In: 1st International Workshop on MOS-IRS and Ocean Colour, Berlin, April 28-30, 1997, Institute of Space Sensor Technology, DLR (ed.), Wissenschaft und Technik Verlag, Berlin.
[146]Sathyendranath, S., Prieur, L. and Morel, A. (1989). A three-component model of ocean colour and its application to remote sensing of phytoplankton pigments in coastal waters. Int. J. Remote Sensing 10:1373-1394.
[147]Schalles, J. F., Gitelson, A. A., Yacobi, Y. Z. and Kroenke, A. E. (1998). Estimation of chlorophyll a from time series measurements of high spectral resolution reflectance in an eutrophic lake. J. Phycol.34:383-390.
[148]Schiller H, Doerffer R. Neural network for emulation of an inverse model operational derivation of Case Ⅱ water properties from MERIS data. International Journal of Remote sensing,1999,20(9):1735-1746.
[149]Slade W.H.,Boss E.S.. Calibrated near-forward volume scattering function obtained from the volume LISST particle sizer. Optics Express,2006,14(8): 3602-3615
[150]Smith, R.C. and K.S. Baker,1981. Optical properties of the clearest natural waters (200-800 nm), Appl Opt.20 (2):177-184.
[151]Sogandares, F.M. and E.S. Fry,1997. Absorption spectrum (340-640 nm) of pure water. I. Photothermal measurements. Appl. Opt.,36(33):8699-8709.
[152]Stramski D, Mobley C D. Effects of microbial particles on oceanic optics:a database of single-particle optical properties. Limnology Oceanography,2004,42: 538-549
[153]Stramski, D. and Kiefer, D. A. (1991). Light scattering by microorganisms in the open ocean. Prog.Oceanogr.28:343-383.
[154]Sullivan, J.M., Twardowski M.S., Zaneveld J.R. V., et al. The hyperspectral temperature and salt dependencies of absorption by water and heavy water in the 400-750 nm spectral range. Applied Optics,2006,45 (21):5294-5309.
[155]Tanaka A, Kishino M, Doerffer R, et al. Development of a neural network algorithm for retrieving concentrations of chlorophyll, suspended matter and yellow substance from radiance data of the ocean color and temperature scanner. Journal of oceanography,2004,60:519-530.
[156]Tassan S. A procedure to determine the particular content of shallow water from Thematic Mapper data. International Journal of Remote Sensing,1998, 19(3):557-562.
[157]Tassan S. Local algorithms using SeaWiFS data for the retrieval of phytoplankton, pigments, suspended sediment, and yellow substance in coastal waters. APPLIED OPTICS,1994,33(12):2369-2378.
[158]Toole, D.A., D.A. Siegel, D.W. Menzies, M.J. Neumann and R.C. Smith, 2000:Remote-sensing reflectance determinations in the coastal ocean environment:impact of instrumental characteristics and environmental variability. Appl. Opt.39:456-468.
[159]Twardowski M, Boss E, Macdonald J B, et al. A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case Ⅰ and case Ⅱ waters J. Geophys Res, 2001,106:14129-14142.
[160]Tynes H. H., Kattawar G. W., Zege E. P., et al. Monte Carlo and multicomponent approximation methods for vector radiative transfer by use of effective Mueller matrix calculations. Appl. Opt.2001,40,400-412.
[161]Ulloa, O., Sathyendranath, S. and Platt, T. (1994). Effect of the particle-size distribution on the backscattering ratio in seawater. Appl. Optics 33:7070-7077.
[162]Ulloa, O., Sathyendranath, S., Platt, T. and Quines, R. A. (1992). Light scattering by marine heterotrophic bacteria. J. Geophys. Res.97:9619-9629.
[163]Unoki, S., Okami, N., Kishino, M. et al. Optical Characteristics of Sea Water at Tokyo Bay. Science and Technology Agency Report, Japan,1978.
[164]Van Zee, H., D. Hankins, and C. deLespinasse,2002:ac-9 Protocol Document (Revision F). WET Labs Inc., Philomath, OR,41pp.
[165]WETLabs, ECO VSF 3 User's Guide, Revision M.2007.
[166]WETLabs. Ac Meter Protocol Document. Revision N,2008.
[167]Whitlock C. H., Poole, L. R., Ursy, J. W, et al. Comparison of reflectance with backscatter for turbid waters. Appl. Optics,1981,20:517-522.
[168]Yan B H, Stamnes K. Fast yet accurate computation of the complete radiance distribution in the coupled atmosphere-ocean system. Journal of Quantitative Spectroscopy & Radiative Transfer,2003,76:207-223.
[169]Zege E. P., and Chaikovskaya L. I., "New approach to the polarized radiative transfer problem," J. Quant. Spectrosc. Radiat. Transfer 55,19-31 (1996).
[170]Zege E. P., Katsev I. L., and Polonsky I. N., "Multicomponent approach to light propagation in clouds and mists," Appl. Opt.32,2803-2812 (1993).
[171]Zhai P W, Hu Y X, Trepte C R.. A vector radiative transfer model for coupled atmosphere and ocean systems based on successive order of scattering method. OPTICS EXPRESS,2009,17(4):2057-2079.
[172]Zhai P. W., Kattawar G W and Yang P.. Impulse response solution to the three-dimensional vector radiative transfer equation in atmosphere-ocean systems. II. The hybrid matrix operator-Monte Carlo method. APPLIED OPTICS,2008, 47(8):1063-1071.
[173]Zhang Y, Pulliainen J, Koponen S, et al. Application of an empirical neural network to surface water quality estimation in the Gulf of Finland using combined optical data and microwave data. Remote Sensing of Environment, 2002,81:327-336.
[174]Zibordi G and Berthon J-F. Relationships between Q-factor and seawater optical properties in a coastal region. Limnology and Oceanography,2001,46(5): 1130-1140.
[175]曹文熙,杨跃忠,许晓强,等。珠江口悬浮颗粒物的吸收光谱及其区域模式。科学通报,2003,48(17)：1876-1882。
[176]曹文熙,杨跃忠。海洋光合有效辐射分布的计算模式。热带海洋学报,2002,21(3)：47-54。
[177]曹文熙,钟其英,杨跃忠。南海水色遥感的主因子分析。遥感学报,1999,3(2)：112-115
[178]长江水利委员会。2007年长江泥沙公报,2007。
[179]陈楚群,潘志林,施平。海水光谱模拟及其在黄色物质遥感反演中的应用,热带海洋学报,2003,22(5)：33-39
[180]陈吉余,沈焕庭,恽才兴,等。长江河口动力过程和地貌演变。上海：上海科学技术出版社,1988。
[181]陈吉余主编。21世纪的长江河口初探。北京：海洋出版社,2009
[182]陈鸣,李士鸿。应用Landsat和NOAA遥感资料联合监测杭州湾的悬浮泥沙。泥沙研究,1989,3：29-34。
[183]陈沈良,张国安,杨世伦等。长江口水域悬沙浓度时空变化与泥沙再悬浮。地理学报,2004,59(2)：260-266。
[184]陈涛,李武,吴曙初。悬浮泥沙浓度与光谱反射率峰值波长红移的相关关系。海洋学报,1994,16(1)：38-43。
[185]陈夏法。杭州湾悬浮泥沙多时相遥感分析。环境遥感,1989,4‘(2)：128-135。
[186]陈晓玲,吴忠宜,田礼乔,等。水体悬浮泥沙动态监测的遥感反演模型对比分析-以鄱阳湖为例。科技导报,2007,25(6)：19-22。
[187]陈晓玲,袁中智,李毓湘,等。基于遥感反演结果的悬浮泥沙时空动态规律研究——以珠江河口及邻近海域为例。武汉大学学报(信息科学版),2005,30(8)：677-681。
[188]陈晓翔,丁晓英。用FY-1D数据估算珠江口海域悬浮泥沙含量,2004,43(增刊)：194-196
[189]丛丕福,牛铮,曲丽梅,等。基于神经网络和TM图像的大连湾海域悬浮物质量浓度的反演。海洋科学,2005,29(4)：31-35。
[190]崔廷伟,张杰,马毅,等。渤海近岸水体后向散射系数反演模型。光学学报,2007,28(11)：2041-2045。
[191]崔廷伟,张杰,马毅,等。赤潮光谱特征及其形成机制。光谱学与光谱分析,2006,26(5)：884-886。
[192]戴志军,韩震,恽才兴,等。茂名海域水体表层悬浮泥沙浓度时空分布特征的遥感分析。海洋科学进展,2006,24(4)：455-462。
[193]邓孺孺,何执兼,陈晓翔。基于二次散射的水污染遥感模型及其在珠江口水域的应用。海洋学报,2003,25(6)：69-78。
[194]丁晓英,许祥向。应用遥感技术分析韩江河口悬沙的动态特征,国土资源遥感,2007,73(3)：71-73。
[195]段民征,吴北婴,吕达仁。海洋-大气耦合辐射传输模式。大气科学,1997,21(6)：734-742。
[196]樊辉,黄海军,唐军武。黄河口水体光谱特性及悬沙浓度遥感估测。武汉大学学报(信息科学版),2007,32(7)：601-604。
[197]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。海洋学报,1999,21(3)：134-140。
[198]高铎,方圣辉,张雪虎。基于遗传算法的东湖水质参数反演方法探讨。测绘信息与工程,2006,31(6)：42-44。
[199]巩彩兰,尹球,匡定波。黄浦江水质指标与反射光谱特征的关系分析。遥感学报,2006,10(6)：910-916
[200]顾艳镇,刘玉光,刘亚豪,等。渤海海区颗粒物的后向散射系数和光束散射系数统计关系研究。中国海洋大学学报,2007,37(增刊)：001-007。
[201]光洁,韦玉春,黄家柱,等。分季节的太湖悬浮物遥感估测模型研究。湖泊科学,2007,19(3)：241-249。
[202]光洁,韦玉春,黄家柱,等。模糊回归在太湖悬浮物反演中的应用。南京师大学报(自然科学版),2006,29(3)：113-117。
[203]郭琳,陈植华。椒江口-台州湾悬浮泥沙分布特征遥感研究。武汉理工大学学报,2007,29(5)：49-52。
[204]韩震,金亚秋，恽才兴。神舟三号CMODIS数据获取长江口悬浮泥沙含量的时空分布。遥感学报,2006,10(3)：381-38。
[205]韩震，恽才兴,蒋雪中。悬浮泥沙反射光谱特性实验研究。水利学报,2003,327(12)：118-122
[206]何青,恽才兴,时伟荣。长江口表层水体悬沙浓度场遥感分析。自然科学进展,1999,9(2)：160-164
[207]何贤强,潘德炉,白雁,等。基于矩阵算法的海洋-大气耦合矢量辐射传输数值计算模型。中国科学(D辑),2006,36(6)：860-870。
[208]何贤强,潘德炉,毛志华,等。利用SeaWiFS反演海水透明度的模式研 究。海洋学报,2004,26(5)：55-62。
[209]黄海军,李成治,郭建军。黄河口海域悬沙光谱特征的研究。海洋科学,1994,5：40-44。
[210]姜杰。利用遥感反演悬浮泥沙浓度的方法研究。海洋地质动态,2006,22(9)：32-34。
[211]孔德星,杨红,吴建辉。长江口海域黄色物质光吸收特性。海洋环境科学。2008,27.(6)：629-631。
[212]乐华福,林寿仁,赵太初。近海Ⅱ类海水反射率与表面悬浮泥沙相关性的研究。国土资源遥感,2000,43(1)：34-38
[213]雷惠,潘德炉,陶邦一,等。东海典型水体的黄色物质光谱吸收及分布特征。海洋学报,2009,31(2)：57-62。
[214]黎夏。悬浮物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,1992,7(2)：106-113。
[215]李凡.海岸带陆海相互作用(LOICZ)研究及我们的策略.地球科学进展,1996,11(1)：19-23。
[216]李洪灵,张鹰,姜杰。基于遥感方法反演悬浮泥沙分布。水科学进展,2006,17(2)242-245
[217]李金和,周振忠,张庆河。滨州港海域泥沙运动遥感图像分析。中国港湾建设,2007,148(2)：5-8。
[218]李京。利用NOAA卫星的AVHRR数据监测杭州湾海域的悬浮泥沙含量。海洋学报,1987,9(1)：132-136
[219]李京。水域悬浮物固体含量的遥感定量研究。环境科学学报,1986,6(2)： 166-173
[220]李四海,唐军武，恽才兴。河口悬浮泥沙浓度SeaWiFS遥感定量模式研究。海洋学报,2002,24(2)：51-58。
[221]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,遥感学报,2001,5(2)：154-160
[222]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,遥感学报,2001,5(2)：154-160
[223]李铜基,陈清莲,汪小勇,杨安安。剖面法测量近岸水体遥感反射率的新方法。海洋技术,2004,23(3)：1-5。
[224]李铜基,陈清莲,杨安安,等。黄东海春季水体后向散射系数的经验模型研究。海洋技术,2004,23(3)：10-14。
[225]李铜基,陈清莲。Ⅱ类水体光学特性的剖面测量方法。海洋技术,2003,22(3)1-5。
[226]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。科学通报,1999,44(17)：1892-1897。
[227]李云驹,常庆瑞,杨晓梅,等。长江口悬浮泥沙的MODIS影像遥感监测研究,西北农林科技大学学报(自然科学版),2005,33(4)：117-121
[228]李云梅,黄家柱,陆皖宁。基于分析模型的太湖悬浮物浓度遥感监测。海洋与湖沼,2006,37(2)：171-177。
[229]刘灿德,何报寅,李茂田。利用MODIS反演长江中游悬浮泥沙含量的初步研究。地质科技情报,2006,25(2)：99-102
[230]刘良明,张红梅。基于基于MODIS数据的悬浮泥沙定量遥感方法。国土资源遥感,2006,68(2)：42-45
[231]刘堂友,匡定波,尹球。湖泊藻类叶绿素-a和悬浮物浓度的高光谱定量遥感模型研究。红外与毫米波学报,2004,23(1)：11-15。
[232]刘炜,李铜基,朱建华,等。黄东海海区总悬浮物散射特性研究。海洋技术,2007,26(2)：42-46
[233]刘小丽,沈芳,朱伟建,等。MERIS卫星数据定量反演长江河口的悬沙浓度。长江流域资源与环境,2009,18(11)：1026-1030。
[234]刘小平,邓孺孺,彭晓鹃。悬浮泥沙定量遥感综合模式及其在珠江口的应用。中山大学学报(自然科学版),2005,44(3)：109-113。
[235]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。水利学报,2007,38(7)：799-805。
[236]刘子琳,宁修仁,蔡昱明。杭州湾——舟山渔场秋季浮游植物现存量和初级生产力。2001,23(2)：93-99。
[237]刘子琳,张涛,刘艳岚,等。2004年春季长江河口水体与沉积物表层的叶绿素a浓度分布。海洋学研究,2008,26(4)：1-7。
[238]吕恒,李新国,曹凯。基于BP神经网络模型的太湖悬浮物浓度遥感定量提取研究。武汉大学学报(信息科学版),2006,31(8)：683-686
[239]吕恒,李新国,江南。基于反射光谱和模拟MERIS数据的太湖悬浮物遥 感定量模型。湖泊科学,2005,17(2)：104-109
[240]马超飞,蒋兴伟,唐军武,等。HY-1 CCD宽波段水色要素反演算法。海洋学报,2005,27(4)：38-44。
[241]马荣华,戴锦芳。结合Landsat ETM与实测光谱估测太湖叶绿素及悬浮物含量。湖泊科学,2005,17(2)：97-103。
[242]宁修仁,库蒂。长江口及冲淡水区叶绿素a、细菌、ATP、POC及微生物呼吸作用速率之间的关系。海洋学报,1991,13(6)：831-837。
[243]潘德炉,李淑青,毛天明。卫星海洋水色遥感的辐射模式研究。海洋与湖沼,1997,28(6)：652-658。
[244]潘德炉,李淑青。卫星海洋水色遥感信息特征量的研究。遥感学报,1998,2(1)：26-31。
[245]沈焕庭,李九发,朱慧芳。长江河口悬沙输移特性。泥沙研究,1986(1)：1-13。
[246]沈焕庭.论我国海岸带陆海相互作用研究。海洋通报,1999,18(6)：11-17
[247]沈新强,胡方西。长江口外水域叶绿素a分布的基本特征。1995,2(1)：71-80。
[248]时伟荣,李九发。长江河口南北槽输沙机制及混浊带发育分析。海洋通报,1993,12(4)：71-76。
[249]时钟,凌鸿烈。长江口细颗粒悬沙浓度垂向分布。泥沙研究,1999,(2)：59-64。
[250]时钟,周洪强。长江口北槽口外悬沙浓度垂线分布的数学模拟。海洋工程,2000,18(3)：57-62。
[251]宋立松,陈武,向卫华,等。基于粗糙集的杭州湾含沙量遥感模型。水利学报,2004,5：58-63。
[252]宋立松,王稳来,陈武,等。钱塘江河口含沙量遥感模式探讨。浙江水利科技,2003,3：1-3。
[253]宋庆君,唐军武。黄海东海海区水体散射特性研究。海洋学报,2006,28(4)：56-63。
[254]宋书群,孙军,沈志良,等。三峡库区蓄水后夏季长江口及其邻近水域粒级叶绿素a。中国海洋大学学报,2006,36(Sup.)：114-120。
[255]宋书群,孙军,俞志明。长江口及其邻近水域叶绿素a的垂直格局及成因初析。植物生态学报,2009,33(2)：369-379。
[256]宋召军,黄海军,刘芳。南黄海辐射沙洲附近海域悬浮泥沙的遥感反演研究。高技术通讯,2006,16(11)：1185-1189。
[257]孙德勇,李云梅,王桥,等。不同浓度悬浮泥沙水体的光谱吸收特性模拟。地理与信息科学,2008,24(5)：16-20。
[258]唐军武,丁静,田纪委,等。黄东海二类水体三要素浓度反演的神经网络模型。高技术通讯,2005,15(3)：83-88。
[259]唐军武,马超飞,牛生丽,等。CBERS-02卫星CCD相机资料定量化反演水体成分初探。中国科学(E辑),2005,35(增刊Ⅰ)：156-170。
[260]唐军武,田国良,汪小勇。水体光谱测量与分析Ⅰ：水面以上测量法。遥感学报,2004,8(1)：37-44。
[261]唐军武,田国良。离水辐射非朗伯特性的Monte Carlo模拟及分析。海洋学报,2000,22,(2)：48-57。
[262]唐军武,王晓梅,宋庆君。黄、东海二类水体水色要素的统计反演模式。海洋科学进展,2004,22(增刊)：1-7
[263]童小华,谢欢,仇雁翎,等。基于多光谱遥感的水质监测处理方法与分析。同济大学学报(自然科学版),2007,35(5)：675-680。
[264]万新宁,李九发,沈焕庭。长江口外海滨悬沙分布及扩散特征。地理研究,2006,25(2)：294-302。
[265]汪小钦,王钦敏,邬群勇,等。遥感在悬浮物质浓度提取中的应用——以福建闽江口为例。遥感学报,2003,7(1)：54-57。
[266]汪小勇,李铜基,刘炜,等。黄东海表观光学量与固有光学量经验模式研究。海洋技术,2008,27(1)：58-64
[267]汪小勇,李铜基,唐军武。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。海洋技术,2004,23(2)：1-7
[268]王繁,周斌,徐建明,等。杭州湾混浊水体表面光谱测量及光谱特征分析。光谱学与光谱分析,2009,29(3)：730-734
[269]王繁,周斌,徐建明,等。基于实测光谱的杭州湾悬浮物浓度遥感反演模式,环境科学,2008,29(11)：3022-3026。
[270]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。 地理研究,2007,26(6)：
[271]王桂芬,曹文熙,许大志,等。南海北部海区非藻类颗粒物吸收系数的变化特性。海洋技术,2007,26(1)：45-49。
[272]王建平,程声通,贾海峰,等。用TM影像进行湖泊水色反演研究的人工神经网络模型。环境科学,2003,24(2)：73-76。
[273]王心源,李文达,严小华,等。基于LandsatTM/ETM+数据提取巢湖悬浮泥沙相对浓度的信息与空间分布变化。湖泊科学,2007,19(3)：255-260。
[274]温令平。伶仃洋悬浮泥沙遥感定量分析。水运工程,2001,332(9)：9-13
[275]吴传庆,王桥,王昌佐。去除叶绿素a影响的泥沙反演模型。中国环境监测,2009,25(2)：26-30。
[276]吴传庆,杨志峰,王桥,等。泥沙浓度的动态峰反演方法。遥感技术与应用,2008,23(5)：517-519。
[277]吴加学,张叔英,任来法.长江口北槽抛泥流速和悬沙浓度时空分布观测。海洋科学,2003,25(4)：91-103。
[278]吴敏,王学军。应用MODIS遥感数据监测巢湖水质。湖泊科学,2005,17(2)：110-113。
[279]吴荣军,吕瑞华,朱明远,等。海水混合和层化对叶绿素a垂直分布的影响。生态环境,2004,13(4)：515-519。
[280]邢小罡,赵冬至,刘玉光,等。渤海非色素颗粒物和黄色物质的吸收特性研究。海洋环境科学,2008,27(6)：595-598。
[281]徐京萍,张柏,蔺钰,等。结合高光谱数据反演吉林石头口门水库悬浮物含量和透明度。湖泊科学,2007,19(3)：269-274。
[282]徐京萍,张柏,宋开山,等。近红外波段二类水体悬浮物生物光学反演模型研究。光谱学与光谱分析,2008,28(10)：2273-2277。
[283]许珺,方红亮,傅肃性,等。运用SPOT数据进行河流水体悬浮固体浓度的研究-以台湾淡水河为例。遥感技术与应用。1999,14(4)：17-22。
[284]许晓强,曹文熙,杨跃忠。珠江口颗粒物吸收系数与盐度及叶绿素a浓度的关系。热带海洋学报,2004,23(5)：63-71。
[285]许勇,张鹰,张东。基于Hyperion影像的悬浮泥沙遥感监测研究。光学技术,2009,35(4)：622-625。
[286]阎福礼,王世新,周艺,等。利用Hyperion星载高光谱传感器监测太湖 水质的研究。红外与毫米波学报,2006,25(6)：
[287]阳锋,沈晓华,邹乐君。非线性函数拟合算法在遥感泥沙定量模式中的应用。遥感技术与应用,2003,18(3)：138-143。
[288]杨安安,李铜基,陈清莲,毕大勇。二类水体表观光学特性的测量与分析--剖面法方法研究。海洋技术,2005,26(3)111-115。
[289]杨伟,陈晋,松下文经。基于生物光学模型的水体叶绿素浓度反演算法。光谱学与光谱分析,2009,29(1)：.38-4。
[290]杨燕明,刘贞文,陈本清,等。用偏最小二乘法反演二类水体的水色要素。遥感学报,2005,9(2)：123-130。
[291]叶琳,徐涵秋。闽江流域福州段悬浮物浓度的遥感分析。遥感技术与应用。2006,21(6)：497-501。
[292]尹球,巩彩兰,匡定波,等。湖泊水质卫星遥感方法及其应用。红外与毫米波学报,2005,24(3)：198-202
[293]恽才兴,胡嘉敏,冯辉,等。河口悬浮泥沙遥感定量研究及其应用研究。见：遥感技术在海洋环境与资源调查中的开发研究成果汇编,北京：海洋出版社,1987,99-110。
[294]恽才兴。长江河口近期演变基本规律。北京：海洋出版社,2004。
[295]恽才兴。海岸带及近海卫星遥感综合应用技术。北京：海洋出版社,2004
[296]詹海刚,施平,陈楚群。基于贝叶斯反演理论的海水固有光学特性准分析算法。科学通报,2006,51(2)：204-210。
[297]詹海刚,施平,陈楚群。基于遗传算法的二类水体水色遥感反演。遥感学报,2004,8(1)：31-36
[298]张春桂,张星,陈敏艳,等。福建近岸海域悬浮泥沙浓度遥感定量监测研究。自然资源学报,2008,23(1)：150-160。
[299]张鉴,何晓雄,赵凤生。利用大气-海洋系统辐射传输模拟水色遥感信息量的变化特性。量子电子学报,2003,20(5)：623-628。
[300]张穗,陈慧娟,陈鹏霄。长江口水体表层泥沙含量遥感监测研究。长江科学院院报,2005,22(5)：23-25。
[301]张亭禄,邱国强。基于辐射传递模拟及人工神经网络技术的二类水体光学组分的反演。湖泊科学,2009,21(2)：173-181。
[302]张绪琴,吴永森,张士魁,等。胶州湾海水黄色物质荧光分布初步研究。 遥感学报,2002,6(3)：229-232。
[303]赵碧云,贺彬,朱云燕,等。滇池水体中总悬浮物含量的遥感定量模型。环境科学与技术,2001,94(2)：16-18
[304]赵洪波,钱敏。江苏如东附近海域泥沙运动遥感分析。水道港口,2004,25(1)：34-37。
[305]仲京臣,汪小勇,陈清莲。基于神经网络的黄东海春季二类水体三要素浓度反演方法。海洋技术,2005,24(4)：118-122
[306]周冠华,李京,杨一鹏。基于半分析算法的太湖水质参数多光谱遥感反演。自然灾害学报,2008,17(6)：142-146。
[307]周冠华,杨一鹏,陈军,等。基于叶绿素荧光峰特征的浑浊水体悬浮物浓度遥感反演。湖泊科学,2009,21(2)：272-279
[308]周良明,刘玉光,郭佩芳。渤海和北黄海水色光谱的特征分析。海洋通报,2005,24(2)：13-19。
[309]周伟华,袁翔城,霍文毅,等。长江口邻域叶绿素a和初级生产力的分布。海洋学报,2004,26(3)：143-150。
[310]朱建华,李铜基。黄东海非色素颗粒与黄色物质的吸收系数光谱模型研究。海洋技术,2004,23(2)：7-13。
[311]朱建华,李铜基。黄东海海区浮游植物色素吸收系数与叶绿素a浓度关系研究。海洋技术,2004,23(4)：117-122。
[312]朱建荣。长江口外海区叶绿素a浓度分布及其动力成因分析。中国科学(D辑),2004,34(8)：757-762。
[313]祝令亚,王世新,周艺,等。应用MODIS影像估测太湖水体悬浮物浓度。水科学进展,2007,18(3)：444-450。
[314]左书华,李九发,万新宁,等。长江河口悬沙浓度变化特征分析。泥沙研究,2006,(3)：68-75.
[315]左书华,杨华,赵群,赵洪波。温州海区近岸表层水体悬沙分布及运动规律的遥感分析。地理与地理信息科学,2007,23(2)：47-50。
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |