基于HJ CCD影像的鄱阳湖总悬浮物浓度反演与时空化研究
|
摘要
鄱阳湖作为我国第一大淡水湖泊,具有明显的过水性、吞吐性典型湖泊特征,其总悬浮物浓度分布时间和空间差异较大。因此仅依靠地面点监测难以客观反映水体总悬浮物浓度时空变化规律。卫星遥感作为一种长时间和大范围获取地表信息的技术手段,在一定程度上能够解决水体监测野外观测不便、数据获取困难等问题。本文以时间序列的HJ-1A/1B卫星CCD传感器数据为数据源,以鄱阳湖水体总悬浮物浓度变化遥感监测为目标,开展模型算法研究与时空动态变化规律分析。本文主要研究成果如下：
1. HJ-1A/1BCCD总悬浮物指数法遥感监测。考虑内陆水体复杂特性,综合对比分析不同卫星光学遥感器数据,以鄱阳湖浑浊水体为典型研究区域,选用了较高时间、空间分辨的HJ-1A/1B卫星CCD数据,尝试遥感监测鄱阳湖水体总悬浮物浓度。提出了一种总悬浮物指数TSMI (Total Suspended Matter Index)的遥感监测方法,以CCD瑞利散射校正后的遥感反射率结果作为数据输入,分析CCD红光通道指数在不同浑浊程度水体中总悬浮物浓度所表现的基线高度的变化,有效解决了浑浊水体传统水色遥感大气校正处理中分子-气溶胶多次散射信号剔除困难的问题,能达到较高的监测精度,提高了非水色遥感器在浑浊水体区域的遥感应用潜力。
2.考虑悬浮物粒径分布的TSMI旨数总悬浮物浓度反演。以2008年、2009年和2011年三个航次的鄱阳湖野外LISST (Laser In-Situ Scattering and Transmissometry)激光粒径分析仪现场数据为基础,综合分析基于HJ-1A/1B CCD传感器数据TSMI指数与悬浮物浓度之间的关系。重点考虑水体不同粒径分布的悬浮颗粒物对光谱的敏感程度与总悬浮物质量浓度的影响,并应用实测数据对反演结果进行精度验证和评价。该方法能有效避免传统浑浊水体遥感大气校正和总悬浮物浓度反演相结合的多级模型误差的累积效应,能有效提高约10%的总悬浮物浓度遥感反演精度。
3.鄱阳湖总悬浮物浓度时空变化规律研究。选取鄱阳湖151景无云HJ-1A/1B卫星CCD传感器数据,应用TSMI总悬浮物浓度遥感反演结果,分析鄱阳湖近4年来水体总悬浮物浓度时空分布格局及其变化趋势。实验结果显示：从2009年-2011年鄱阳湖水体总悬浮物浓度具有明显的季节性特征,枯水期总悬浮物浓度较高,丰水期较低。鄱阳湖南北两个湖区水体总悬浮物浓度空间分布差异较大,分析总悬浮物浓度的日、季相、年际变化特征,南湖区水体总悬浮物浓度年际变化不大,北湖区持续升高,南北湖区差异有增加的趋势,主要原因是位于鄱阳湖中部的主采砂区近几年来采砂活动频繁和采砂强度增加的影响。
4.基于HJ-1A/1B CCD数据的采砂区遥感监测。结合鄱阳湖总悬浮物浓度遥感反演时序统计结果,分析鄱阳湖南北湖区水体总悬浮物浓度时空分布差异特征,考虑水体总悬浮物浓度空间分布年际差异变化,确定采砂区范围并分析采砂活动强度,结合采砂区实测水深数据,估算采砂量。结果显示：从2009-2011年间,位于鄱阳湖松门山岛的主采砂区年采砂量在6000万吨以上,采砂强度有逐年增加的趋势。
Poyang Lake is the largest freshwater lake in china, where the inundation area shows great inter-annual variability and the Total suspended matter (TSM) has significant tempo-spatial distribution. Being a new technique in acquiring the large-scale data, remote sensing could play a critical role in monitoring the water dynamics, while the traditional filed measurement is impossible to fulfill this task. High frequent remote sensing data is particularly suitable in monitoring TSM concentration. This study choose the high temporal and spatial resolution data-HJ-1A/1B satellite Charge Coupled Device (CCD) data to investigate the change of TSM variations in Poyang Lake, the main achievements are as follows:
1. A novel index for TSM retrieval was proposed, namely Total Suspended Matter Index (TMSI). Considering the dynamic nature of its inundation area, HJ-1A/IB CCD, with high temporal and spatial resolution, was selected as the main data source to monitor the total suspended matter concentration of Poyang Lake. A novel approach index was developed to retrieve the total suspended matter (TSM) concentration. For turbid waters, standard atmospheric correction method often failed in removing the molecule-aerosol multiple scattering from the satellite imagery, while the TSMI was proven to be more effective in detecting total suspended matter than other methods, which is primarily due to that most of the aerosol effects are removed by the baseline subtraction, and TSMI is insensitive to changes in solar/viewing geometry. The TSM estimates showed a satisfied accuracy, and this method could improve the potential of land-oriented sensors in water color applications.
2. Considering the particle size distribution when using TSMI method to retrieve TSM concentration. Particle size distribution measurements of LISST (Laser In-Situ Scattering and Transmissomentry) were collected from three cruises in2008,2009and2011. The different contribution to the reflectance and the quality concentration of total suspended matter is partly due to different particle sizes. A remote sensing inversion model was presented using the empirical relationship between the LISST total suspended concentration data and HJ-1A/1B CCD total suspended matter index. Validation of various methods showed that the TSMI method is particularly suitable for monitoring turbid waters in Poyang Lake.
3. The spatial and temporal distribution of total suspended matter in Poyang Lake. In total,151cloud-free HJ-1A/1B CCD images were selected from September2008to December2011, which has a spatial resolution of30m and temporal resolution of2days. Diurnal and seasonal variations of TSM in Poyang Lake were analyzed. Then, the change frequency of the TSM concentration was also studied to discuss the possible wet season and dry season seasonal changes in Poyang Lake, and the human interference to the TSM changes was also indentified. The most important finding is that the total suspended matter concentration in North Lake of Poyang Lake was higher than South Lake, which was due to the sand dredging activities from2009-2011.
4. Dredging area delineation with HJ-1A/1B CCD imagery. With the TSM estimates using remote sensing data, the changes in annual TSM distributions were obtained, from which the sand dredging area in Poyang Lake was delineated during each year from2009to2011. Results showed that the total dredged sand close to the Songmen Mountain of Poyang Lake were more than60million tons from2009-2011, and the dredging activities appeared an increasing trend.
1. HJ-1A/1BCCD总悬浮物指数法遥感监测。考虑内陆水体复杂特性,综合对比分析不同卫星光学遥感器数据,以鄱阳湖浑浊水体为典型研究区域,选用了较高时间、空间分辨的HJ-1A/1B卫星CCD数据,尝试遥感监测鄱阳湖水体总悬浮物浓度。提出了一种总悬浮物指数TSMI (Total Suspended Matter Index)的遥感监测方法,以CCD瑞利散射校正后的遥感反射率结果作为数据输入,分析CCD红光通道指数在不同浑浊程度水体中总悬浮物浓度所表现的基线高度的变化,有效解决了浑浊水体传统水色遥感大气校正处理中分子-气溶胶多次散射信号剔除困难的问题,能达到较高的监测精度,提高了非水色遥感器在浑浊水体区域的遥感应用潜力。
2.考虑悬浮物粒径分布的TSMI旨数总悬浮物浓度反演。以2008年、2009年和2011年三个航次的鄱阳湖野外LISST (Laser In-Situ Scattering and Transmissometry)激光粒径分析仪现场数据为基础,综合分析基于HJ-1A/1B CCD传感器数据TSMI指数与悬浮物浓度之间的关系。重点考虑水体不同粒径分布的悬浮颗粒物对光谱的敏感程度与总悬浮物质量浓度的影响,并应用实测数据对反演结果进行精度验证和评价。该方法能有效避免传统浑浊水体遥感大气校正和总悬浮物浓度反演相结合的多级模型误差的累积效应,能有效提高约10%的总悬浮物浓度遥感反演精度。
3.鄱阳湖总悬浮物浓度时空变化规律研究。选取鄱阳湖151景无云HJ-1A/1B卫星CCD传感器数据,应用TSMI总悬浮物浓度遥感反演结果,分析鄱阳湖近4年来水体总悬浮物浓度时空分布格局及其变化趋势。实验结果显示：从2009年-2011年鄱阳湖水体总悬浮物浓度具有明显的季节性特征,枯水期总悬浮物浓度较高,丰水期较低。鄱阳湖南北两个湖区水体总悬浮物浓度空间分布差异较大,分析总悬浮物浓度的日、季相、年际变化特征,南湖区水体总悬浮物浓度年际变化不大,北湖区持续升高,南北湖区差异有增加的趋势,主要原因是位于鄱阳湖中部的主采砂区近几年来采砂活动频繁和采砂强度增加的影响。
4.基于HJ-1A/1B CCD数据的采砂区遥感监测。结合鄱阳湖总悬浮物浓度遥感反演时序统计结果,分析鄱阳湖南北湖区水体总悬浮物浓度时空分布差异特征,考虑水体总悬浮物浓度空间分布年际差异变化,确定采砂区范围并分析采砂活动强度,结合采砂区实测水深数据,估算采砂量。结果显示：从2009-2011年间,位于鄱阳湖松门山岛的主采砂区年采砂量在6000万吨以上,采砂强度有逐年增加的趋势。
Poyang Lake is the largest freshwater lake in china, where the inundation area shows great inter-annual variability and the Total suspended matter (TSM) has significant tempo-spatial distribution. Being a new technique in acquiring the large-scale data, remote sensing could play a critical role in monitoring the water dynamics, while the traditional filed measurement is impossible to fulfill this task. High frequent remote sensing data is particularly suitable in monitoring TSM concentration. This study choose the high temporal and spatial resolution data-HJ-1A/1B satellite Charge Coupled Device (CCD) data to investigate the change of TSM variations in Poyang Lake, the main achievements are as follows:
1. A novel index for TSM retrieval was proposed, namely Total Suspended Matter Index (TMSI). Considering the dynamic nature of its inundation area, HJ-1A/IB CCD, with high temporal and spatial resolution, was selected as the main data source to monitor the total suspended matter concentration of Poyang Lake. A novel approach index was developed to retrieve the total suspended matter (TSM) concentration. For turbid waters, standard atmospheric correction method often failed in removing the molecule-aerosol multiple scattering from the satellite imagery, while the TSMI was proven to be more effective in detecting total suspended matter than other methods, which is primarily due to that most of the aerosol effects are removed by the baseline subtraction, and TSMI is insensitive to changes in solar/viewing geometry. The TSM estimates showed a satisfied accuracy, and this method could improve the potential of land-oriented sensors in water color applications.
2. Considering the particle size distribution when using TSMI method to retrieve TSM concentration. Particle size distribution measurements of LISST (Laser In-Situ Scattering and Transmissomentry) were collected from three cruises in2008,2009and2011. The different contribution to the reflectance and the quality concentration of total suspended matter is partly due to different particle sizes. A remote sensing inversion model was presented using the empirical relationship between the LISST total suspended concentration data and HJ-1A/1B CCD total suspended matter index. Validation of various methods showed that the TSMI method is particularly suitable for monitoring turbid waters in Poyang Lake.
3. The spatial and temporal distribution of total suspended matter in Poyang Lake. In total,151cloud-free HJ-1A/1B CCD images were selected from September2008to December2011, which has a spatial resolution of30m and temporal resolution of2days. Diurnal and seasonal variations of TSM in Poyang Lake were analyzed. Then, the change frequency of the TSM concentration was also studied to discuss the possible wet season and dry season seasonal changes in Poyang Lake, and the human interference to the TSM changes was also indentified. The most important finding is that the total suspended matter concentration in North Lake of Poyang Lake was higher than South Lake, which was due to the sand dredging activities from2009-2011.
4. Dredging area delineation with HJ-1A/1B CCD imagery. With the TSM estimates using remote sensing data, the changes in annual TSM distributions were obtained, from which the sand dredging area in Poyang Lake was delineated during each year from2009to2011. Results showed that the total dredged sand close to the Songmen Mountain of Poyang Lake were more than60million tons from2009-2011, and the dredging activities appeared an increasing trend.
引文
[1]Agrawal, Y.C.,& Pottsmith, H.C. Instruments for particle size and settling velocity observations in sediment transport [J]. Marine Geology,2000,168,89-114.
[2]Agrawal, Y.C.,& Traykovski, P. Particles in the bottom boundary layer:Concentration and size dynamics through events [J]. Journal of Geophysical Research-Oceans, 2001,106,9533-9542.
[3]Antoine, D.,& Morel, A.A multiple scattering algorithm for atmospheric correction of remotely sensed ocean colour (MERIS instrument):principle and implementation for atmospheres carrying various aerosols including absorbing ones [J]. International Journal of Remote Sensing,1999,20,1875-1916.
[4]Arnone, R.A., Oriol, R.A., Trees, C.C.,& Mueller, J.L. Bottom reflectance discrimination using water leaving radiance from coastal zone color scanner. In (pp. 612-623). Orlando, FL, USA:Publ by Int Soc for Optical Engineering,1999.
[5]Babin, M., Morel, A., Fournier-Sicre, V., Fell, F.,& Stramski, D.Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration [J]. Limnology and Oceanography,2003,48,843-859.
[6]Breon FM, Henriot N, Spaceborne observations of ocean glint reflectance and modeling of wave slope distributions [J]. JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS,2006,111.
[7]Bryant, R.G.,& Rainey, M.P.Investigation of flood inundation on playas within the Zone of Chotts, using a time-series of AVHRR [J]. Remote Sensing of Environment. 2002,82,360-375.
[8]Bunt, J. Light and photosynthesis in aquatic ecosystems:J.T.O. Kirk, Cambridge University Press,111-112.1994.
[9]Chavez P.S Jr, Image-based atmospheric corrections--revisited and revised [J]. Photogrammetric Engineering and Remote Sensing,1996,62(9):1025-1036.
[10]Chen WJ, Tseng CY, Liu GR, Huang SJ, The effect of the atmosphere on the OCI channels:Rayleigh scattering [J]. TERRESTRIAL ATMOSPHERIC AND OCEANIC SCIENCES,1999,115-126.
[11]Chomko, R., and H. R. Gordon, Atmospheric correction of ocean color imagery:use of the Junge power-law aerosol size distribution with variables refractive index to handle aerosol absorption [J], Appl. Opt,1998,37,5560-5572.
[12]Chomko, R.M.,& Gordon, H.R. Atmospheric Correction of Ocean Color Imagery:Test of the Spectral Optimization Algorithm with the Sea-Viewing Wide Field-of-View Sensor [J]. Appl. Opt.,2001,40,2973-2984.
[13]Cox C. and Munk W., Measurement of the roughness of the sea surface from photographs of the sun's glitter [J]. Journal of the optical society of America,1954,44 (11):838-850.
[14]Daguerre, Louis. History and Practice of the Photogenic Drawing on the True Principles of the Daguerreotype with the New Method of Dioramic Painting. 1839,London:Stewart and Murray.
[15]Ding, K.,& Gordon, H.R. Analysis of the influence of O2 A-band absorption on atmospheric correction of ocean-color imagery [J]. Appl. Opt.,1995,34,2068-2080.
[16]Ding, K.Y.,& Gordon, H.R. ATMOSPHERIC CORRECTION OF OCEAN-COLOR SENSORS-EFFECTS OF THE EARTHS CURVATURE [J]. Applied Optics,1994, 33,7096-7106.
[17]Duane Nellis, M., Harrington Jr, J.A.,& Wu, J. Remote sensing of temporal and spatial variations in pool size, suspended sediment, turbidity, and Secchi depth in Tuttle Creek Reservoir [J]. Kansas. Geomorphology,1993,21,281-293.
[18]Emecen EG, Kara G, Erdogmus F, Gardashov R, The determination of sunglint locations on the ocean surface by observation from geostationary satellites [J]. TERRESTRIAL ATMOSPHERIC AND OCEANIC SCIENCES,2006,17 (1): 253-261.
[19]FARGION G S, MUELLER J L. Ocean optics protocols for satellite ocean color sensor validation [R]. Revs ion 3.NASA/TM22002221004,2002.
[20]Fukushima, H.,& Toratani, M. Asian dust aerosol:Optical effect on satellite ocean color signal and a scheme of its correction [J]. J. Geophys. Res.,1997,102, 17119-17130.
[21]Gao, B.C., Montes, M.J., Ahmad, Z.,& Davis, CO. Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space [J]. Applied Optics,2000, 39,887-896.
[22]Gordon H R, Wang M H. Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS:a preliminary algorithm [J]. Applied Optics, 1994,33:443-452.
[23]GORDON Howard R, JAMES W Brown, ROBERT H Evans, Exact Rayleigh scattering calculations for use with the Nimbus-7 coastal zone color scanner [J].Applied Optics,1988,27 (5):862-871.
[24]Gordon HR. Radiative transfer in the atmosphere for correction of ocean color remote sensing. In Ocean Color:Theory and Applications in a Decade of CZCS Experience,1993:33.
[25]Gordon, H. R, Menghua Wang, Surface-roughness considerations for atmospheric correction of ocean color sensors. Ⅱ:Error in the retrieved water-leaving radiance.
[26]Gordon, H. R, Menghua Wang, Surface-roughness considerations for atmospheric correction of ocean color sensors.I:The Rayleigh-scattering component.
[27]Gordon, H. R., T. Zhang, F. He, and K. Ding, Effects of stratospheric aerosols and thin cirrus clouds on the atmospheric correction of ocean color imagery:simulations [J]. Appl. Opt.,1997,36,682-697.
[28]Gordon, H.R. Radiative transfer:a technique for simulating the ocean in satellite remote sensing calculations [J]. Appl. Opt.,1976,15,1974-1979.
[29]Gordon, H.R. Removal of atmospheric effects from satellite imagery of the oceans [J]. Appl. Opt.,1978,17,1631-1636.
[30]Gordon, H.R. Remote sensing of ocean color:a methodology for dealing with broad spectral bands and significant out-of-band response [J]. Appl. Opt.,1995,34, 8363-8374.
[31]Gordon, H.R.,& Castano, D.J. Aerosol analysis with the Coastal Zone Color Scanner: a simple method for including multiple scattering effects [J]. Appl. Opt.,1989,28, 1320-1326.
[32]Gordon, H.R.,& Clark, D.K. Clear water radiances for atmospheric correction of coastal zone color scanner imagery [J]. Appl. Opt.,1981,20,4175-4180.
[33]Gordon, H.R.,& Wang, M. Influence of oceanic whitecaps on atmospheric correction of ocean-color sensors [J]. Appl. Opt.,1994a,33,7754-7763.
[34]Gordon, H.R.,& Wang, M.H. SURFACE-ROUGHNESS CONSIDERATIONS FOR ATMOSPHERIC CORRECTION OF OCEAN COLOR SENSORS.1. THE RAYLEIGH-SCATTERING COMPONENT. Applied Optics [J],1992a,31, 4247-4260.
[35]Gordon, H.R.,& Wang, M.H. SURFACE-ROUGHNESS CONSIDERATIONS FOR ATMOSPHERIC CORRECTION OF OCEAN COLOR SENSORS.2. ERROR IN THE RETRIEVED WATER-LEAVING RADIANCE. Applied Optics [J],1992b,31, 4261-4267.
[36]Gordon, H.R.,& Wang, M.H. RETRIEVAL OF WATER-LEAVING RADIANCE AND AEROSOL OPTICAL-THICKNESS OVER THE OCEANS WITH SEAWIFS-A PRELIMINARY ALGORITHM. Applied Optics [J],1994b,33,443-452.
[37]Gordon, H.R., Brown, J.W.,& Evans, R.H. Exact Rayleigh scattering calculations for use with the Nimbus-7 Coastal Zone Color Scanner. Appl. Opt. [J],1988,27,862-871.
[38]Gordon, H.R., Du, T.,& Zhang, T. Remote sensing of ocean color and aerosol properties:resolving the issue of aerosol absorption. Appl. Opt. [J],1997,36, 8670-8684.
[39]Gower, J.F.R., Doerffer, R.,& Borstad, G.A. Interpretation of the 685 nm peak in water-leaving radiance spectra in terms of fluorescence, absorption and scattering, and its observation by MERIS [J]. International Journal of Remote Sensing,1999,20, 1771-1786.
[40]Guo H, Hu Q, Jiang T. Annual and seasonal streamflow responses to climate and land-cover changes in the Poyang Lake basin, China [J]. Journal of Hydrology,2008, 355(1-4):106-122.
[41]He XQ, Pan DL, Bai Y, Gong F, General purpose exact Rayleigh scattering look-up table for ocean color remote sensing [J], ACTA OCEANOLOGICA SINICA,2006, 25(1):48-56.
[42]Hu Chuanmin, Carder Kendall L, Muller Karger. Frank E.Atomospheric Correction of SeaWiFS Imagery over Turbid Coastal Waters [J]. Remote sensing of Environmen, 2000,74(2):195-206.
[43]Hu, CM. A novel ocean color index to detect floating algae in the global oceans [J]. Remote Sensing of Environment,2009,113,2118-2129.
[44]Hu, CM., Cannizzaro, J., Carder, K.L., Muller-Karger, F.E.,& Hardy, R. Remote detection of Trichodesmium blooms in optically complex coastal waters:Examples with MODIS full-spectral data [J]. Remote Sensing of Environment,2010,114, 2048-2058.
[45]Hu, CM., Carder, K.L.,& Muller-Karger, F.E. Atmospheric correction of SeaWiFS imagery over turbid coastal waters:A practical method [J]. Remote Sensing of Environment,2000,74,195-206.
[46]Hu, CM., Chen, Z.Q., Clayton, T.D., Swarzenski, P., Brock, J.C,& Muller-Karger, F.E. Assessment of estuarine water-quality indicators using MODIS medium-resolution bands:Initial results from Tampa Bay, FL [J]. Remote Sensing of Environment,2004, 93,423-441.
[47JILEC&UNEP, World lake vision:a call to action, International Lake Environment Committee Foundation and United Nations Environment Programme, Kusatsu, Japan,2OO3.
[48]IOCCG. Remote Sensing Of Ocean Color in Coastal, and Other Optically-Complex Waters; Report No.3,2000.
[49]Kaufman YJ, Martins JV, Remer LA, Schoeberl MR, Yamasoe MA, Satellite retrieval of aerosol absorption over the oceans using sunglint [J]. GEOPHYSICAL RESEARCH LETTERS,2002,29(19).
[50]Keiner, L.E.,& Yan, X.-H. A Neural Network Model for Estimating Sea Surface Chlorophyll and Sediments from Thematic Mapper Imagery [J]. Remote Sensing of Environment,1998,66,153-165.
[51]Larsen NF, Stamnes K, Methane detection from space:use of sunglint [J], OPTICAL ENGINEERING,2006,45 (1).
[52]Lavender, S.J., Pinkerton, M.H., Moore, G.F., Aiken, J.,& Blondeau-Patissier, D. Modification to the atmospheric correction of SeaWiFS ocean colour images over turbid waters [J]. Continental Shelf Research,2005,25,539-555.
[53]Li Rong-Rong, Kaufman Y. J., Gao Bo-Cai, Davis C. O.. Remote sensing of suspended sediments and shallow coastal waters [J]. IEEE Transactions on Geoscience and Remote Sensing.2003,41(3),559-566.
[54]Mao, Z., Chen, J., Pan, D., Tao, B.,& Zhu, Q. A regional remote sensing algorithm for total suspended matter in the East China Sea [J]. Remote Sensing of Environment, 2012,124,819-831.
[55]Markham B.L, and J.L. Barker, Landsat MSS and TM post-calibration dynamic ranges, exoatmospheric reflectances and at-satellite temperatures. EOSAT Technical Note, August 1986.
[56]Mikkelsen, O.A.,& Pejrup, M. In situ particle size spectra and density of particle aggregates in a dredging plume [J]. Marine Geology,2000,170,443-459.
[57]Mikkelsen, O.A.,& Pejrup, M. The use of a LISST-100 laser particle sizer for in-situ estimates of flee size, density and settling velocity [J]. Geo-Marine Letters,2001,20, 187-195.
[58]Miller, R.L.,& McKee, B.A. Using MODIS Terra 250 m imagery to map concentrations of total suspended matter in coastal waters [J]. Remote Sensing of Environment,2004,93,259-266.
[59]Min, J.-E., Ryu, J.-H., Lee, S.,& Son, S. Monitoring of suspended sediment variation using Landsat and MODIS in the Saemangeum coastal area of Korea [J]. Marine Pollution Bulletin,2012,64,382-390.
[60]MOBLEY C D. Estimation of the remote sensing reflectance from above surface measurements [J]. Applied Optics,1999,38:7442-7455.
[61]Mohan M, Chauhan P, Simulations for optimal payload tilt to avoid sunglint in IRS-P4 Ocean Colour Monitor (OCM) data around the Indian subcontinent [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2001,22 (1):185-190.
[62]Moore, G.F., Aiken, J.,& Lavender, S.J. The atmospheric correction of water colour and the quantitative retrieval of suspended particulate matter in Case II waters: application to MERIS [J]. International Journal of Remote Sensing,1999,20, 1713-1733.
[63]Morel, A.,& Gentili, B. Diffuse reflectance of oceanic waters. III. Implication of bidirectionality for the remote-sensing problem [J]. Appl. Opt.,1996,35,4850-4862.
[64]Moulin, C, Gordon, H.R., Chomko, R.M., Banzon, V.F.,& Evans, R.H. Atmospheric correction of ocean color imagery through thick layers of Saharan dust [J]. Geophysical Research Letters,2001,28,5-8.
[65]Neumann A, K.H., Walzel T. A complex approach to quantitative interpretation of spectral high resolution imagery[M]. In, Third Thematic Conference on Remote Sensing for Marine and Coastal Environments, Seattle, USA (pp.11-641-11-652),1995.
[66]Niang A, Badran F, Moulin C, Crepon M, Thiria S, Retrieval of aerosol type and optical thickness over the Mediterranean from SeaWiFS images using an automatic neural classification method [J]. Remote Sensing of Environment,2006,100 (1), 82-94.
[67]Rouse, J.W., Haas, R.H., Schell, J.A.,& Deering, D.W. Monitoring vegetation systems in the Great Plains with ERTS [M]. In, Proceedings of the Third ERTS Symposium, 1973,309-317. Washington DC.
[68]Ruddick, K. G., F. Ovidio, and M. Rijkeboer, Atmospheric correction of SeaWiFS imagery for turbid and inland waters [J]. Appl. Opt.,2000,39,897-912.
[69]SAKAMOTO,#160, Toshihiro, NGUYEN, V., Nhan, KOTERA, Akihiko, OHNO, Hiroyuki, ISHITSUKA, Naoki,& YOKOZAWA. Detecting temporal changes in the extent of annual flooding within the cambodia and the Vietnamese mekong delta from MODIS time-series imagery. New York, NY, ETATS-UNIS:Elsevier,2007.
[70]Schiller, H.,& Doerffer, R.. Neural network for emulation of an inverse model- operational derivation of Case Ⅱ water properties from MERIS data [J]. International Journal of Remote Sensing,1999,20,1735-1746.
[71]Shi, W.,& Wang, M. Detection of turbid waters and absorbing aerosols for the MODIS ocean color data processing [J]. Remote Sensing of Environment,2007,110,149-161.
[72]Siegel, D.A., Wang, M.H., Maritorena, S.,& Robinson, W. Atmospheric correction of satellite ocean color imagery:the black pixel assumption [J]. Applied Optics,2000,39, 3582-3591.
[73]Sipelgas, L., Raudsepp, U.,& Kouts, T. Operational monitoring of suspended matter distribution using MODIS images and numerical modelling [J]. Advances in Space Research,2006,38,2182-2188.
[74]Sturm, B.,& Zibordi, G. SeaWiFS atmospheric correction by an approximate model and vicarious calibration [J]. International Journal of Remote Sensing,2002,23, 489-501.
[75]Su WY, Charlock TP, Rutledge K. Observations of reflectance distribution around sunglint from a coastal ocean platform [J]. APPLIED OPTICS,2002,41 (35): 7369-7383.
[76]Traykovski, P., Latter, R.J.,& Irish, J.D. A laboratory evaluation of the laser in situ scattering and transmissometery instrument using natural sediments [J]. Marine Geology,1999,159,355-367.
[77]Tyler, A.N., Svab, E., Preston, T, Presing, M.,& Kovacs, W.A. Remote sensing of the water quality of shallow lakes:A mixture modelling approach to quantifying phytoplankton in water characterized by high-suspended sediment [J]. International Journal of Remote Sensing,2006,27,1521-1537.
[78]Wang MH, A refinement for the Rayleigh radiance computation with variation of the atmospheric pressure [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2005,26 (24):5651-5663.
[79]Wang MH, The Rayleigh lookup tables for the SeaWiFS data processing:accounting for the effects of oceansurface roughness [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2002,23 (13):2693-2702.
[80]Wang, M. A Sensitivity Study of the SeaWiFS Atmospheric Correction Algorithm: Effects of Spectral Band Variations [J]. Remote Sensing of Environment,1999a,67, 348-359.
[81]Wang, M.,& Shi,W.. The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing [J]. Optics Express,2007,15,15722-15733.
[82]Wang, M.H. Atmospheric correction of ocean color sensors:computing atmospheric diffuse transmittance [J]. Applied Optics,1999b,38,451-455.
[83]Wang, M.H. The Rayleigh lookup tables for the SeaWiFS data processing:accounting for the effects of ocean surface roughness [J]. International Journal of Remote Sensing, 2002,23,2693-2702.
[84]Wang, M.H.,& Shi, W. Cloud masking for ocean color data processing in the coastal regions [J]. Ieee Transactions on Geoscience and Remote Sensing,2006,44, 3196-3205.
[85]Wang, M.H.,& Shi, W. The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing [J]. Optics Express,2007,15,15722-15733.
[86]Wang, M.H., Knobelspiesse, K.D.,& McClain, C.R. Study of the Sea-Viewing Wide FieId-of-View Sensor (SeaWiFS) aerosol optical property data over ocean in combination with the ocean color products [J]. Journal of Geophysical Research-Atmospheres,2005,110.
[87]Wang, M.H., Tang, J.W.,& Shi, W. MODIS-derived ocean color products along the China east coastal region [J]. Geophysical Research Letters,2007,34.
[88]Xianqiang, H., Delu, P.,& Zhihua, M. Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters [J]. ACTA OCEANOLOGICA SINICA,2004,23,7.
[89]Yan, B.H., Stamnes, K., Li, W., Chen, B.Q., Stamnes, J.J.,& Tsay, S.C. Pitfalls in atmospheric correction of ocean color imagery:how should aerosol optical properties be computed? [J]. Applied Optics,2002,41,412-423.
[90]Yang, H.,& Gordon, H.R. Remote sensing of ocean color:assessment of water-leaving radiance bidirectional effects on atmospheric diffuse transmittance [J]. Appl. Opt., 1997,36,7887-7897.
[91]Zhao, X., Stein, A., Chen, X.,& Feng, L. Modeling spatial-temporal change of Poyang Lake marshland based on an uncertainty theory-random sets [J]. Procedia Environmental Sciences,2011,3,105-110.
[92]陈莉琼,陈晓玲,田礼乔,等.鄱阳湖水体悬浮颗粒物散射光谱分解方法研究[J].光谱学与光谱分析,2012,32(3)：729-733.
[93]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[J].科技导报,2007,25(6)：19-22.
[94]陈勇,韩震,杨丽君,等.长江口水体表层悬浮泥沙时空分布对环境演变的响应[J].海洋学报,2012,34(1)：145-152.
[95]丁静,唐军武,宋庆君,&王晓梅.中国近岸浑浊水体大气修正的迭代与优化算法[J].遥感学报,2006,10,732-741
[96]何贤强,潘德炉,白雁,等.通用型海洋水色遥感精确瑞利散射查找表[J].海洋学报(中文版),2006,28(1)：47-55.
[97]何贤强,潘德炉,尹中林,等.水色遥感卫星姿态对瑞利散射计算的影响[J].遥感学报,2005,9(3)：242-246.
[98]马荣华,唐军武,段洪涛,等.湖泊水色遥感研究进展[J].湖泊科学,2009(02)：143-158.
[99]毛志华、郭德方、潘德炉,航空水色遥感中太阳耀光信息提取及消除方法的研究[J].遥感技术与应用,1996,11(4)：15-20
[100]刘大召,陈楚群,刘汾汾,等.利用混合光谱分解估测珠江口悬浮泥沙浓度[J].热带海洋学报,2009,28(5)：43-48.
[101]宋召军,黄海军,杜廷芹,等.南黄海辐射沙洲附近海域悬浮体的研究[J].海洋地质与第四纪地质,2006,26(6)：19-25.
[102]Liu, Can-De, He, et al. QUANTITATIVE MODELING OF SUSPENDED SEDIMENT IN MIDDLE CHANGJIANG RIVER FROM MODIS [J].中国地理科学：英文版,2006,16(1).
[103]李四海,唐军武,等.河口悬浮泥沙浓度SeaWiFS遥感定量模式研究[J].海洋学报,2002,24(2)：51-58.
[104]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[J]. 西北农林科技大学学报：自然科学版,2005,33(4)：117-121.
[105]李淑菁、毛天明、潘德炉,太阳反射光对海洋水色卫星遥感的影响研究[J],热带海洋,1997,16(4)：76-82
[106]刘茜,David, G,等.基于高光谱数据和MODIS影像的鄱阳湖悬浮泥沙浓度估算[J].遥感技术与应用,2008,23(1)：7-11.
[107]潘德炉,Doerffer R海洋水色卫星的辐射模拟图像研究[J].海洋学报,1997,19：43-55
[108]潘德炉,马荣华.湖泊水质遥感的几个关键问题[J].湖泊科学,2008,20(2)：139-144.
[109]江辉.基于遥感的鄱阳湖水体总悬浮物对水文特征的响应分析[J].安徽农业科学,2012,40(12)：7339-7341.
[110]唐军武.海洋光学特性模拟与遥感模型[D].中国科学院遥感应用技术研究所中国科学院遥感应用研究所,1999.
[111]赵崴,林明森,唐军武,等.水色遥感的精确Rayleigh散射算法研究[J].高技术通讯,2006,16(8)：876-880.
[112]Guo H, Hu Q, Jiang T. Annual and seasonal streamflow responses to climate and land-cover changes in the Poyang Lake basin [J], China. Journal of Hydrology, 2008,355(1-4):106-122.
[113]唐军武,田国良,汪小勇,等.水体光谱测量与分析Ⅰ：水面以上测量法[J].遥感学报,2004(01)：37-44.
[114]程江,何青,王元叶.利用LISST观测絮凝体粒径、有效密度和沉速的垂线分布[J].泥沙研究,2005(1)：33-39.
[115]李秀文,朱博章.长江口大面积水域絮凝体粒径分布规律研究[J].人民长江,2010,41(19)：60-63.
[116]朱进,蒋建平,石照泉,等.现场激光粒度分析仪光程缩短器的安装及检查方法[J].今日科苑,2010(21)：121.
[117]陈松生,李海源LISST测沙仪及其比测试验[J].水利水电快报,2000,21(20)：6-8.
[118]程天文,赵楚年。我国主要河流入海经流量、输沙量及对沿岸的影响[J]。海洋学报,1985,(4)：460-471
[119]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(17)：1892.
[120]王苏民,张振克.中国湖泊沉积与环境演变研究的新进展[J].科学通报,1999,44(6)：579-587.
[121]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[J].科学通报,2006,51(2)：204-210.
[122]李小曼,王刚,田杰.TM影像中水体提取方法研究[J].西南农业大学学报.2006,28(4)：580-582.
[123]李英奎,倪晋仁,李秀霞等。泥沙灾害与泥沙灾害链的分类分级[J]。自然灾害学报,2005,14(1)：15-24
[124]刘晨洲,施建成,高帅,等.基于改进混合像元方法的MODIS影像水体提取研究[J].遥感信息.2010(1)：84-88.
[125]刘茜,Rossiter DG,基于高光谱数据和MODIS影像的鄱阳湖悬浮泥沙浓度估算[J]。遥感技术与应用,2008,23(1)：7-12。
[126]梁志勇,李文学,吕文堂等。黄河下游泥沙灾害与减灾对策(Ⅰ)——泥沙灾害分类与侵蚀型泥沙灾害[J]。自然灾害学报,2002,11：126-130。
[127]马丹.基于MODIS数据的水体提取研究[J].地理空间信息.2008,6(1)：25-28.
[128]孟令奎,郭善听,李爽.遥感影像水体提取与洪水监测应用综述[J].水利信息化.2012(3)：18-25.
[129]曲伟,路京选,李琳,等.环境减灾小卫星影像水体和湿地自动提取方法研究[J].遥感信息.2011(4)：28-33.
[130]席晓燕,沈楠,李小娟.ETM+影像水体提取方法研究[J].计算机工程与设计.2009(4)：993-996.
[131]王秋燕,陈仁喜,徐佳,等.环境一号卫星影像中水体信息提取方法研究[J].科学技术与工程.2012,12(13)：3051-3056.
[132]王随霞,张行南,朱辰华,等.基于MODIS数据的黄河水体提取方法研究[J].人民黄河.2007,29(3)：27-28.
[133]吴文渊,沈晓华,邹乐君,等.基于Landsat ETM+影像的水体信息综合提取方法[J].科技通报.2008,24(2)：252-259,271.
[134]杨莹,阮仁宗.a基于TM影像的平原湖泊水体信息提取的研究[J].遥感信息.2010(3)：60-64.
[135]仝彩荣,马海州,周笃珺.基于MODIS数据的西台吉乃尔盐湖水体提取及水域面积的监测[J].盐湖研究.2008,16(4)：27-31.
[136]邬国锋,崔丽娟,纪伟涛.基于时间序列MODIS影像的鄱阳湖丰水期悬浮泥沙浓度反演及变化[J].湖泊科学,2009,21(2)：288-297.
[137]张伟,陈晓玲,田礼乔,等.鄱阳湖HJ-1-A/B卫星CCD传感器悬浮泥沙遥感监测[J].武汉大学学报(信息科学版),2010(12)：1466-1469.
[138]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[J].自然资源学报,2008,23(1)：150-160.
[2]Agrawal, Y.C.,& Traykovski, P. Particles in the bottom boundary layer:Concentration and size dynamics through events [J]. Journal of Geophysical Research-Oceans, 2001,106,9533-9542.
[3]Antoine, D.,& Morel, A.A multiple scattering algorithm for atmospheric correction of remotely sensed ocean colour (MERIS instrument):principle and implementation for atmospheres carrying various aerosols including absorbing ones [J]. International Journal of Remote Sensing,1999,20,1875-1916.
[4]Arnone, R.A., Oriol, R.A., Trees, C.C.,& Mueller, J.L. Bottom reflectance discrimination using water leaving radiance from coastal zone color scanner. In (pp. 612-623). Orlando, FL, USA:Publ by Int Soc for Optical Engineering,1999.
[5]Babin, M., Morel, A., Fournier-Sicre, V., Fell, F.,& Stramski, D.Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration [J]. Limnology and Oceanography,2003,48,843-859.
[6]Breon FM, Henriot N, Spaceborne observations of ocean glint reflectance and modeling of wave slope distributions [J]. JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS,2006,111.
[7]Bryant, R.G.,& Rainey, M.P.Investigation of flood inundation on playas within the Zone of Chotts, using a time-series of AVHRR [J]. Remote Sensing of Environment. 2002,82,360-375.
[8]Bunt, J. Light and photosynthesis in aquatic ecosystems:J.T.O. Kirk, Cambridge University Press,111-112.1994.
[9]Chavez P.S Jr, Image-based atmospheric corrections--revisited and revised [J]. Photogrammetric Engineering and Remote Sensing,1996,62(9):1025-1036.
[10]Chen WJ, Tseng CY, Liu GR, Huang SJ, The effect of the atmosphere on the OCI channels:Rayleigh scattering [J]. TERRESTRIAL ATMOSPHERIC AND OCEANIC SCIENCES,1999,115-126.
[11]Chomko, R., and H. R. Gordon, Atmospheric correction of ocean color imagery:use of the Junge power-law aerosol size distribution with variables refractive index to handle aerosol absorption [J], Appl. Opt,1998,37,5560-5572.
[12]Chomko, R.M.,& Gordon, H.R. Atmospheric Correction of Ocean Color Imagery:Test of the Spectral Optimization Algorithm with the Sea-Viewing Wide Field-of-View Sensor [J]. Appl. Opt.,2001,40,2973-2984.
[13]Cox C. and Munk W., Measurement of the roughness of the sea surface from photographs of the sun's glitter [J]. Journal of the optical society of America,1954,44 (11):838-850.
[14]Daguerre, Louis. History and Practice of the Photogenic Drawing on the True Principles of the Daguerreotype with the New Method of Dioramic Painting. 1839,London:Stewart and Murray.
[15]Ding, K.,& Gordon, H.R. Analysis of the influence of O2 A-band absorption on atmospheric correction of ocean-color imagery [J]. Appl. Opt.,1995,34,2068-2080.
[16]Ding, K.Y.,& Gordon, H.R. ATMOSPHERIC CORRECTION OF OCEAN-COLOR SENSORS-EFFECTS OF THE EARTHS CURVATURE [J]. Applied Optics,1994, 33,7096-7106.
[17]Duane Nellis, M., Harrington Jr, J.A.,& Wu, J. Remote sensing of temporal and spatial variations in pool size, suspended sediment, turbidity, and Secchi depth in Tuttle Creek Reservoir [J]. Kansas. Geomorphology,1993,21,281-293.
[18]Emecen EG, Kara G, Erdogmus F, Gardashov R, The determination of sunglint locations on the ocean surface by observation from geostationary satellites [J]. TERRESTRIAL ATMOSPHERIC AND OCEANIC SCIENCES,2006,17 (1): 253-261.
[19]FARGION G S, MUELLER J L. Ocean optics protocols for satellite ocean color sensor validation [R]. Revs ion 3.NASA/TM22002221004,2002.
[20]Fukushima, H.,& Toratani, M. Asian dust aerosol:Optical effect on satellite ocean color signal and a scheme of its correction [J]. J. Geophys. Res.,1997,102, 17119-17130.
[21]Gao, B.C., Montes, M.J., Ahmad, Z.,& Davis, CO. Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space [J]. Applied Optics,2000, 39,887-896.
[22]Gordon H R, Wang M H. Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS:a preliminary algorithm [J]. Applied Optics, 1994,33:443-452.
[23]GORDON Howard R, JAMES W Brown, ROBERT H Evans, Exact Rayleigh scattering calculations for use with the Nimbus-7 coastal zone color scanner [J].Applied Optics,1988,27 (5):862-871.
[24]Gordon HR. Radiative transfer in the atmosphere for correction of ocean color remote sensing. In Ocean Color:Theory and Applications in a Decade of CZCS Experience,1993:33.
[25]Gordon, H. R, Menghua Wang, Surface-roughness considerations for atmospheric correction of ocean color sensors. Ⅱ:Error in the retrieved water-leaving radiance.
[26]Gordon, H. R, Menghua Wang, Surface-roughness considerations for atmospheric correction of ocean color sensors.I:The Rayleigh-scattering component.
[27]Gordon, H. R., T. Zhang, F. He, and K. Ding, Effects of stratospheric aerosols and thin cirrus clouds on the atmospheric correction of ocean color imagery:simulations [J]. Appl. Opt.,1997,36,682-697.
[28]Gordon, H.R. Radiative transfer:a technique for simulating the ocean in satellite remote sensing calculations [J]. Appl. Opt.,1976,15,1974-1979.
[29]Gordon, H.R. Removal of atmospheric effects from satellite imagery of the oceans [J]. Appl. Opt.,1978,17,1631-1636.
[30]Gordon, H.R. Remote sensing of ocean color:a methodology for dealing with broad spectral bands and significant out-of-band response [J]. Appl. Opt.,1995,34, 8363-8374.
[31]Gordon, H.R.,& Castano, D.J. Aerosol analysis with the Coastal Zone Color Scanner: a simple method for including multiple scattering effects [J]. Appl. Opt.,1989,28, 1320-1326.
[32]Gordon, H.R.,& Clark, D.K. Clear water radiances for atmospheric correction of coastal zone color scanner imagery [J]. Appl. Opt.,1981,20,4175-4180.
[33]Gordon, H.R.,& Wang, M. Influence of oceanic whitecaps on atmospheric correction of ocean-color sensors [J]. Appl. Opt.,1994a,33,7754-7763.
[34]Gordon, H.R.,& Wang, M.H. SURFACE-ROUGHNESS CONSIDERATIONS FOR ATMOSPHERIC CORRECTION OF OCEAN COLOR SENSORS.1. THE RAYLEIGH-SCATTERING COMPONENT. Applied Optics [J],1992a,31, 4247-4260.
[35]Gordon, H.R.,& Wang, M.H. SURFACE-ROUGHNESS CONSIDERATIONS FOR ATMOSPHERIC CORRECTION OF OCEAN COLOR SENSORS.2. ERROR IN THE RETRIEVED WATER-LEAVING RADIANCE. Applied Optics [J],1992b,31, 4261-4267.
[36]Gordon, H.R.,& Wang, M.H. RETRIEVAL OF WATER-LEAVING RADIANCE AND AEROSOL OPTICAL-THICKNESS OVER THE OCEANS WITH SEAWIFS-A PRELIMINARY ALGORITHM. Applied Optics [J],1994b,33,443-452.
[37]Gordon, H.R., Brown, J.W.,& Evans, R.H. Exact Rayleigh scattering calculations for use with the Nimbus-7 Coastal Zone Color Scanner. Appl. Opt. [J],1988,27,862-871.
[38]Gordon, H.R., Du, T.,& Zhang, T. Remote sensing of ocean color and aerosol properties:resolving the issue of aerosol absorption. Appl. Opt. [J],1997,36, 8670-8684.
[39]Gower, J.F.R., Doerffer, R.,& Borstad, G.A. Interpretation of the 685 nm peak in water-leaving radiance spectra in terms of fluorescence, absorption and scattering, and its observation by MERIS [J]. International Journal of Remote Sensing,1999,20, 1771-1786.
[40]Guo H, Hu Q, Jiang T. Annual and seasonal streamflow responses to climate and land-cover changes in the Poyang Lake basin, China [J]. Journal of Hydrology,2008, 355(1-4):106-122.
[41]He XQ, Pan DL, Bai Y, Gong F, General purpose exact Rayleigh scattering look-up table for ocean color remote sensing [J], ACTA OCEANOLOGICA SINICA,2006, 25(1):48-56.
[42]Hu Chuanmin, Carder Kendall L, Muller Karger. Frank E.Atomospheric Correction of SeaWiFS Imagery over Turbid Coastal Waters [J]. Remote sensing of Environmen, 2000,74(2):195-206.
[43]Hu, CM. A novel ocean color index to detect floating algae in the global oceans [J]. Remote Sensing of Environment,2009,113,2118-2129.
[44]Hu, CM., Cannizzaro, J., Carder, K.L., Muller-Karger, F.E.,& Hardy, R. Remote detection of Trichodesmium blooms in optically complex coastal waters:Examples with MODIS full-spectral data [J]. Remote Sensing of Environment,2010,114, 2048-2058.
[45]Hu, CM., Carder, K.L.,& Muller-Karger, F.E. Atmospheric correction of SeaWiFS imagery over turbid coastal waters:A practical method [J]. Remote Sensing of Environment,2000,74,195-206.
[46]Hu, CM., Chen, Z.Q., Clayton, T.D., Swarzenski, P., Brock, J.C,& Muller-Karger, F.E. Assessment of estuarine water-quality indicators using MODIS medium-resolution bands:Initial results from Tampa Bay, FL [J]. Remote Sensing of Environment,2004, 93,423-441.
[47JILEC&UNEP, World lake vision:a call to action, International Lake Environment Committee Foundation and United Nations Environment Programme, Kusatsu, Japan,2OO3.
[48]IOCCG. Remote Sensing Of Ocean Color in Coastal, and Other Optically-Complex Waters; Report No.3,2000.
[49]Kaufman YJ, Martins JV, Remer LA, Schoeberl MR, Yamasoe MA, Satellite retrieval of aerosol absorption over the oceans using sunglint [J]. GEOPHYSICAL RESEARCH LETTERS,2002,29(19).
[50]Keiner, L.E.,& Yan, X.-H. A Neural Network Model for Estimating Sea Surface Chlorophyll and Sediments from Thematic Mapper Imagery [J]. Remote Sensing of Environment,1998,66,153-165.
[51]Larsen NF, Stamnes K, Methane detection from space:use of sunglint [J], OPTICAL ENGINEERING,2006,45 (1).
[52]Lavender, S.J., Pinkerton, M.H., Moore, G.F., Aiken, J.,& Blondeau-Patissier, D. Modification to the atmospheric correction of SeaWiFS ocean colour images over turbid waters [J]. Continental Shelf Research,2005,25,539-555.
[53]Li Rong-Rong, Kaufman Y. J., Gao Bo-Cai, Davis C. O.. Remote sensing of suspended sediments and shallow coastal waters [J]. IEEE Transactions on Geoscience and Remote Sensing.2003,41(3),559-566.
[54]Mao, Z., Chen, J., Pan, D., Tao, B.,& Zhu, Q. A regional remote sensing algorithm for total suspended matter in the East China Sea [J]. Remote Sensing of Environment, 2012,124,819-831.
[55]Markham B.L, and J.L. Barker, Landsat MSS and TM post-calibration dynamic ranges, exoatmospheric reflectances and at-satellite temperatures. EOSAT Technical Note, August 1986.
[56]Mikkelsen, O.A.,& Pejrup, M. In situ particle size spectra and density of particle aggregates in a dredging plume [J]. Marine Geology,2000,170,443-459.
[57]Mikkelsen, O.A.,& Pejrup, M. The use of a LISST-100 laser particle sizer for in-situ estimates of flee size, density and settling velocity [J]. Geo-Marine Letters,2001,20, 187-195.
[58]Miller, R.L.,& McKee, B.A. Using MODIS Terra 250 m imagery to map concentrations of total suspended matter in coastal waters [J]. Remote Sensing of Environment,2004,93,259-266.
[59]Min, J.-E., Ryu, J.-H., Lee, S.,& Son, S. Monitoring of suspended sediment variation using Landsat and MODIS in the Saemangeum coastal area of Korea [J]. Marine Pollution Bulletin,2012,64,382-390.
[60]MOBLEY C D. Estimation of the remote sensing reflectance from above surface measurements [J]. Applied Optics,1999,38:7442-7455.
[61]Mohan M, Chauhan P, Simulations for optimal payload tilt to avoid sunglint in IRS-P4 Ocean Colour Monitor (OCM) data around the Indian subcontinent [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2001,22 (1):185-190.
[62]Moore, G.F., Aiken, J.,& Lavender, S.J. The atmospheric correction of water colour and the quantitative retrieval of suspended particulate matter in Case II waters: application to MERIS [J]. International Journal of Remote Sensing,1999,20, 1713-1733.
[63]Morel, A.,& Gentili, B. Diffuse reflectance of oceanic waters. III. Implication of bidirectionality for the remote-sensing problem [J]. Appl. Opt.,1996,35,4850-4862.
[64]Moulin, C, Gordon, H.R., Chomko, R.M., Banzon, V.F.,& Evans, R.H. Atmospheric correction of ocean color imagery through thick layers of Saharan dust [J]. Geophysical Research Letters,2001,28,5-8.
[65]Neumann A, K.H., Walzel T. A complex approach to quantitative interpretation of spectral high resolution imagery[M]. In, Third Thematic Conference on Remote Sensing for Marine and Coastal Environments, Seattle, USA (pp.11-641-11-652),1995.
[66]Niang A, Badran F, Moulin C, Crepon M, Thiria S, Retrieval of aerosol type and optical thickness over the Mediterranean from SeaWiFS images using an automatic neural classification method [J]. Remote Sensing of Environment,2006,100 (1), 82-94.
[67]Rouse, J.W., Haas, R.H., Schell, J.A.,& Deering, D.W. Monitoring vegetation systems in the Great Plains with ERTS [M]. In, Proceedings of the Third ERTS Symposium, 1973,309-317. Washington DC.
[68]Ruddick, K. G., F. Ovidio, and M. Rijkeboer, Atmospheric correction of SeaWiFS imagery for turbid and inland waters [J]. Appl. Opt.,2000,39,897-912.
[69]SAKAMOTO,#160, Toshihiro, NGUYEN, V., Nhan, KOTERA, Akihiko, OHNO, Hiroyuki, ISHITSUKA, Naoki,& YOKOZAWA. Detecting temporal changes in the extent of annual flooding within the cambodia and the Vietnamese mekong delta from MODIS time-series imagery. New York, NY, ETATS-UNIS:Elsevier,2007.
[70]Schiller, H.,& Doerffer, R.. Neural network for emulation of an inverse model- operational derivation of Case Ⅱ water properties from MERIS data [J]. International Journal of Remote Sensing,1999,20,1735-1746.
[71]Shi, W.,& Wang, M. Detection of turbid waters and absorbing aerosols for the MODIS ocean color data processing [J]. Remote Sensing of Environment,2007,110,149-161.
[72]Siegel, D.A., Wang, M.H., Maritorena, S.,& Robinson, W. Atmospheric correction of satellite ocean color imagery:the black pixel assumption [J]. Applied Optics,2000,39, 3582-3591.
[73]Sipelgas, L., Raudsepp, U.,& Kouts, T. Operational monitoring of suspended matter distribution using MODIS images and numerical modelling [J]. Advances in Space Research,2006,38,2182-2188.
[74]Sturm, B.,& Zibordi, G. SeaWiFS atmospheric correction by an approximate model and vicarious calibration [J]. International Journal of Remote Sensing,2002,23, 489-501.
[75]Su WY, Charlock TP, Rutledge K. Observations of reflectance distribution around sunglint from a coastal ocean platform [J]. APPLIED OPTICS,2002,41 (35): 7369-7383.
[76]Traykovski, P., Latter, R.J.,& Irish, J.D. A laboratory evaluation of the laser in situ scattering and transmissometery instrument using natural sediments [J]. Marine Geology,1999,159,355-367.
[77]Tyler, A.N., Svab, E., Preston, T, Presing, M.,& Kovacs, W.A. Remote sensing of the water quality of shallow lakes:A mixture modelling approach to quantifying phytoplankton in water characterized by high-suspended sediment [J]. International Journal of Remote Sensing,2006,27,1521-1537.
[78]Wang MH, A refinement for the Rayleigh radiance computation with variation of the atmospheric pressure [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2005,26 (24):5651-5663.
[79]Wang MH, The Rayleigh lookup tables for the SeaWiFS data processing:accounting for the effects of oceansurface roughness [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2002,23 (13):2693-2702.
[80]Wang, M. A Sensitivity Study of the SeaWiFS Atmospheric Correction Algorithm: Effects of Spectral Band Variations [J]. Remote Sensing of Environment,1999a,67, 348-359.
[81]Wang, M.,& Shi,W.. The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing [J]. Optics Express,2007,15,15722-15733.
[82]Wang, M.H. Atmospheric correction of ocean color sensors:computing atmospheric diffuse transmittance [J]. Applied Optics,1999b,38,451-455.
[83]Wang, M.H. The Rayleigh lookup tables for the SeaWiFS data processing:accounting for the effects of ocean surface roughness [J]. International Journal of Remote Sensing, 2002,23,2693-2702.
[84]Wang, M.H.,& Shi, W. Cloud masking for ocean color data processing in the coastal regions [J]. Ieee Transactions on Geoscience and Remote Sensing,2006,44, 3196-3205.
[85]Wang, M.H.,& Shi, W. The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing [J]. Optics Express,2007,15,15722-15733.
[86]Wang, M.H., Knobelspiesse, K.D.,& McClain, C.R. Study of the Sea-Viewing Wide FieId-of-View Sensor (SeaWiFS) aerosol optical property data over ocean in combination with the ocean color products [J]. Journal of Geophysical Research-Atmospheres,2005,110.
[87]Wang, M.H., Tang, J.W.,& Shi, W. MODIS-derived ocean color products along the China east coastal region [J]. Geophysical Research Letters,2007,34.
[88]Xianqiang, H., Delu, P.,& Zhihua, M. Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters [J]. ACTA OCEANOLOGICA SINICA,2004,23,7.
[89]Yan, B.H., Stamnes, K., Li, W., Chen, B.Q., Stamnes, J.J.,& Tsay, S.C. Pitfalls in atmospheric correction of ocean color imagery:how should aerosol optical properties be computed? [J]. Applied Optics,2002,41,412-423.
[90]Yang, H.,& Gordon, H.R. Remote sensing of ocean color:assessment of water-leaving radiance bidirectional effects on atmospheric diffuse transmittance [J]. Appl. Opt., 1997,36,7887-7897.
[91]Zhao, X., Stein, A., Chen, X.,& Feng, L. Modeling spatial-temporal change of Poyang Lake marshland based on an uncertainty theory-random sets [J]. Procedia Environmental Sciences,2011,3,105-110.
[92]陈莉琼,陈晓玲,田礼乔,等.鄱阳湖水体悬浮颗粒物散射光谱分解方法研究[J].光谱学与光谱分析,2012,32(3)：729-733.
[93]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[J].科技导报,2007,25(6)：19-22.
[94]陈勇,韩震,杨丽君,等.长江口水体表层悬浮泥沙时空分布对环境演变的响应[J].海洋学报,2012,34(1)：145-152.
[95]丁静,唐军武,宋庆君,&王晓梅.中国近岸浑浊水体大气修正的迭代与优化算法[J].遥感学报,2006,10,732-741
[96]何贤强,潘德炉,白雁,等.通用型海洋水色遥感精确瑞利散射查找表[J].海洋学报(中文版),2006,28(1)：47-55.
[97]何贤强,潘德炉,尹中林,等.水色遥感卫星姿态对瑞利散射计算的影响[J].遥感学报,2005,9(3)：242-246.
[98]马荣华,唐军武,段洪涛,等.湖泊水色遥感研究进展[J].湖泊科学,2009(02)：143-158.
[99]毛志华、郭德方、潘德炉,航空水色遥感中太阳耀光信息提取及消除方法的研究[J].遥感技术与应用,1996,11(4)：15-20
[100]刘大召,陈楚群,刘汾汾,等.利用混合光谱分解估测珠江口悬浮泥沙浓度[J].热带海洋学报,2009,28(5)：43-48.
[101]宋召军,黄海军,杜廷芹,等.南黄海辐射沙洲附近海域悬浮体的研究[J].海洋地质与第四纪地质,2006,26(6)：19-25.
[102]Liu, Can-De, He, et al. QUANTITATIVE MODELING OF SUSPENDED SEDIMENT IN MIDDLE CHANGJIANG RIVER FROM MODIS [J].中国地理科学：英文版,2006,16(1).
[103]李四海,唐军武,等.河口悬浮泥沙浓度SeaWiFS遥感定量模式研究[J].海洋学报,2002,24(2)：51-58.
[104]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[J]. 西北农林科技大学学报：自然科学版,2005,33(4)：117-121.
[105]李淑菁、毛天明、潘德炉,太阳反射光对海洋水色卫星遥感的影响研究[J],热带海洋,1997,16(4)：76-82
[106]刘茜,David, G,等.基于高光谱数据和MODIS影像的鄱阳湖悬浮泥沙浓度估算[J].遥感技术与应用,2008,23(1)：7-11.
[107]潘德炉,Doerffer R海洋水色卫星的辐射模拟图像研究[J].海洋学报,1997,19：43-55
[108]潘德炉,马荣华.湖泊水质遥感的几个关键问题[J].湖泊科学,2008,20(2)：139-144.
[109]江辉.基于遥感的鄱阳湖水体总悬浮物对水文特征的响应分析[J].安徽农业科学,2012,40(12)：7339-7341.
[110]唐军武.海洋光学特性模拟与遥感模型[D].中国科学院遥感应用技术研究所中国科学院遥感应用研究所,1999.
[111]赵崴,林明森,唐军武,等.水色遥感的精确Rayleigh散射算法研究[J].高技术通讯,2006,16(8)：876-880.
[112]Guo H, Hu Q, Jiang T. Annual and seasonal streamflow responses to climate and land-cover changes in the Poyang Lake basin [J], China. Journal of Hydrology, 2008,355(1-4):106-122.
[113]唐军武,田国良,汪小勇,等.水体光谱测量与分析Ⅰ：水面以上测量法[J].遥感学报,2004(01)：37-44.
[114]程江,何青,王元叶.利用LISST观测絮凝体粒径、有效密度和沉速的垂线分布[J].泥沙研究,2005(1)：33-39.
[115]李秀文,朱博章.长江口大面积水域絮凝体粒径分布规律研究[J].人民长江,2010,41(19)：60-63.
[116]朱进,蒋建平,石照泉,等.现场激光粒度分析仪光程缩短器的安装及检查方法[J].今日科苑,2010(21)：121.
[117]陈松生,李海源LISST测沙仪及其比测试验[J].水利水电快报,2000,21(20)：6-8.
[118]程天文,赵楚年。我国主要河流入海经流量、输沙量及对沿岸的影响[J]。海洋学报,1985,(4)：460-471
[119]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(17)：1892.
[120]王苏民,张振克.中国湖泊沉积与环境演变研究的新进展[J].科学通报,1999,44(6)：579-587.
[121]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[J].科学通报,2006,51(2)：204-210.
[122]李小曼,王刚,田杰.TM影像中水体提取方法研究[J].西南农业大学学报.2006,28(4)：580-582.
[123]李英奎,倪晋仁,李秀霞等。泥沙灾害与泥沙灾害链的分类分级[J]。自然灾害学报,2005,14(1)：15-24
[124]刘晨洲,施建成,高帅,等.基于改进混合像元方法的MODIS影像水体提取研究[J].遥感信息.2010(1)：84-88.
[125]刘茜,Rossiter DG,基于高光谱数据和MODIS影像的鄱阳湖悬浮泥沙浓度估算[J]。遥感技术与应用,2008,23(1)：7-12。
[126]梁志勇,李文学,吕文堂等。黄河下游泥沙灾害与减灾对策(Ⅰ)——泥沙灾害分类与侵蚀型泥沙灾害[J]。自然灾害学报,2002,11：126-130。
[127]马丹.基于MODIS数据的水体提取研究[J].地理空间信息.2008,6(1)：25-28.
[128]孟令奎,郭善听,李爽.遥感影像水体提取与洪水监测应用综述[J].水利信息化.2012(3)：18-25.
[129]曲伟,路京选,李琳,等.环境减灾小卫星影像水体和湿地自动提取方法研究[J].遥感信息.2011(4)：28-33.
[130]席晓燕,沈楠,李小娟.ETM+影像水体提取方法研究[J].计算机工程与设计.2009(4)：993-996.
[131]王秋燕,陈仁喜,徐佳,等.环境一号卫星影像中水体信息提取方法研究[J].科学技术与工程.2012,12(13)：3051-3056.
[132]王随霞,张行南,朱辰华,等.基于MODIS数据的黄河水体提取方法研究[J].人民黄河.2007,29(3)：27-28.
[133]吴文渊,沈晓华,邹乐君,等.基于Landsat ETM+影像的水体信息综合提取方法[J].科技通报.2008,24(2)：252-259,271.
[134]杨莹,阮仁宗.a基于TM影像的平原湖泊水体信息提取的研究[J].遥感信息.2010(3)：60-64.
[135]仝彩荣,马海州,周笃珺.基于MODIS数据的西台吉乃尔盐湖水体提取及水域面积的监测[J].盐湖研究.2008,16(4)：27-31.
[136]邬国锋,崔丽娟,纪伟涛.基于时间序列MODIS影像的鄱阳湖丰水期悬浮泥沙浓度反演及变化[J].湖泊科学,2009,21(2)：288-297.
[137]张伟,陈晓玲,田礼乔,等.鄱阳湖HJ-1-A/B卫星CCD传感器悬浮泥沙遥感监测[J].武汉大学学报(信息科学版),2010(12)：1466-1469.
[138]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[J].自然资源学报,2008,23(1)：150-160.
© 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 |