After many years＇ endeavor of research and application practice, the ocean color remote sensing in China has been growing into a new technique with valuable practicality from its initiate stage of trial research. Wit...After many years＇ endeavor of research and application practice, the ocean color remote sensing in China has been growing into a new technique with valuable practicality from its initiate stage of trial research. With the aim of operational service, several kinds of ocean color remote sensing application systems have been developed and realized the long-term marine environmental monitoring utilizing the real-time or near real-time satellite and airborne remote sensing data. New progresses in the technology and application of ocean color remote sensing in China are described, including the research of key techniques and the development of various application systems. Meanwhile, according to the application status and demand, the prospective development of Chinese ocean color remote sensing is brought forward. With Chinese second ocean color satellite （ HY-1 B） orbiting on 11 April 2007 and the development of airborne ocean color remote sensing system for Chinese surveillance planes, great strides will take place in Chinese ocean color remote sensing application with the unique function in marine monitoring, resources management and national security, etc.展开更多
A method to estimate the thickness of the sea ice of the Bohai Sea is proposed using geostationary ocean color imager （GOCI） data and then applied to the dynamic monitoring of the sea ice thickness in the Bohal Sea ...A method to estimate the thickness of the sea ice of the Bohai Sea is proposed using geostationary ocean color imager （GOCI） data and then applied to the dynamic monitoring of the sea ice thickness in the Bohal Sea during the winter of 2014 to 2015. First of all, a model is given between the GOCI shortwave broadband albedo and the reflectance of each band with high temporal resolution GOCI data. Then, the relationship model between the sea ice thickness and the GOCI shortwave broadband albedo is established and applied to the thickness extraction of the sea ice in the Bohai Sea. Finally, the sea ice thickness extraction method is tested by the results based on the MODIS data, thermodynamic empirical models （Lebedev and Zubov）, and the in situ ice thickness data. The test results not only indicated that the sea ice thickness retrieval method based on the GOCI data was a good correlation （r2〉0.66） with the sea ice thickness retrieved by the MODIS and thermodynamic empirical models, but also that the RMS is only 6.82 cm different from the thickness of the sea ice based on the GOCI and in situ data.展开更多
Coastal water environment is essentially enhanced by ocean color which is basically decided by substances concentration in water such as chlorophyll, suspended material and yellow substance. It is very difficult, even...Coastal water environment is essentially enhanced by ocean color which is basically decided by substances concentration in water such as chlorophyll, suspended material and yellow substance. It is very difficult, even not possible, to detect water color by expensive ship routing, because of its temporal and spatial variety of feature and scales in the very complicated dynamical system of coastal water. With the development of satellite technique in the last 20 a, space sensors can be applied to detect ocean color by measuring the spectra of water leaving radiance.It is proven that ocean color remote sensing is a powerful tool for understanding the process of oceanic biology and physics. Since the 1980s, great attention has been paid to the advanced remote sensing technique in China, especially to development of satellite programs for the coastal water environment. On 7 September 1988, China launched her first polar orbit satellite FY-1A for meteorological and oceanographic application (water color and temperature) and the second satellite FY-1B two years later. In May 1999, China launched her second generation environment satellite FY-1C with higher sensitivies, more channels and stable operation. The special ocean color satellite HY-1 is planned to be in the orbit in 2001, whose main purpose is to detect the coastal water environment of China seas. China is also developing a very advantageous sensor termed as Chinese moderate imaging spectra radiometer (CMODIS) with 91 channels, which will be a good candidate of the third generation satellite FY-3 in 2003. The technical system of ocean color remote sensing was developed by the Second Institute of Oceanography (SIO), State Oceanic Administration (SOA) in 1997. The system included data receiving, processing, distribution, calibration, validation and application units. The Hangzhou Station of SIO, SOA has the capability to receive FY-1 and AVHRR data since 1989. It was also a SeaWiFS scientific research station authorized by NASA,USA to free receive SeaWiFS data from 16 September 1997. In the recent years, the local algorithms of atmospheric correction and inversion of ocean color have been developed for FY-1C and SeaWiFS, to improve the accuracy of the measurement from satellites efficiently. The satellite data are being applied to monitor coastal water environment, such as the spatial distribution of chlorophyll, suspended material and yellow substance, red tide detection and coastal current study. The results show that the ocean color remote sensing has latent capacity in the detection of coastal water environment.In consideration of the update technique progress of ocean color remote sensing and its more important role in the detection of coastal water in the 2000s, some suggestions are set forth, which would be beneficial to the design of a cheaper but practical coastal water detection system for marine environment preservation.展开更多
Waters along China coast are very turbid with high concentrations of suspended sediment nearly all the time,especially at the Hangzhou Bay,the Changjiang （Yangtze） River Estuary and the shoal along Jiangsu Province....Waters along China coast are very turbid with high concentrations of suspended sediment nearly all the time,especially at the Hangzhou Bay,the Changjiang （Yangtze） River Estuary and the shoal along Jiangsu Province.In these turbid and optically complex waters,the standard MODIS ocean color products tend to have invalid values.Because the water-leaving radiances in the near-infrared （NIR） are significant resulting from the strong scattering of suspended particles,the standard MODIS atmospheric correction algorithm often gets no results or produces significant errors.And because of the complex water optical properties,the OC3 model used in the standard MODIS data processing tends to get extremely high chlorophyll-a （Chl-a） concentrations.In this paper,we present an atmospheric correction approach using MODIS short wave infrared （SWIR） bands based on the fact that water-leaving radiances are negligible in the SWIR region because of the extreme strong absorption of water even in turbid waters.A regional Chl-a concentration estimation model is also constructed for MODIS from in situ data.These algorithms are applied to MODIS Aqua data processing in the China coastal regions.In situ data collected in the Yellow Sea and the East China Sea in spring and autumn,2003 are used to validate the performance.Reasonably good results have been obtained.It is noted that water-leaving reflectance in the NIR bands are significant in waters along the China coast with high sediment loadings.The satellite derived and in-situ reflectance spectra can match in the turbid waters along China coast,and there is relatively good linear relationship between satellite derived and in-situ reflectance.The RMSE value of Rrs（λ） is 0.0031 sr ？1 for all the nine ocean color bands （412 to 869 nm）.The satellite-derived Chl-a value is in the reasonable range and the root mean square percentage difference is 46.1%.展开更多
The current exact Rayleigh scattering calculation of ocean color remote sensing uses the look-up table （LUT）, which is usually created for a special remote sensor and cannot be applied to other sensors. For practica...The current exact Rayleigh scattering calculation of ocean color remote sensing uses the look-up table （LUT）, which is usually created for a special remote sensor and cannot be applied to other sensors. For practical application, a general purpose Rayleigh scattering LUT which can be applied to all ocean color remote sensors is generated. An adding-doubling method to solve the vector radiative transfer equation in the plane-parallel atmosphere is deduced in detail. Compared with the exact Rayleigh scattering radiance derived from the MODIS exact Rayleigh scattering LUT, it is proved that the relative error of Rayleigh scattering calculation with the adding-doubling method is less than 0.25%, which meets the required accuracy of the atmospheric correction of ocean color remote sensing. Therefore, the adding-doubling method can be used to generate the exact Rayleigh scattering LUT for the ocean color remote sensors. Finally, the general purpose exact Rayleigh scattering LUT is generated using the adding-doubling method. On the basis of the general purpose LUT, the calculated Rayleigh scattering radiance is tested by comparing with the LUTs ofMODIS, SeaWiFS and the other ocean color sensors, showing that the relative errors are all less than 0.5%, and this general purpose LUT can be applied to all ocean color remote sensors.展开更多
A medium resolution spectral imager （MERSI） on-board the first spacecraft of the second generation of Chinas polar-orbit meteorological satellites FY-3A, is a MODIS-like sensor with 20 bands covering visible to ther...A medium resolution spectral imager （MERSI） on-board the first spacecraft of the second generation of Chinas polar-orbit meteorological satellites FY-3A, is a MODIS-like sensor with 20 bands covering visible to thermal infrared spectral region. FY-3A/MERSI is capable of making continuous global observations, and ocean color application is one of its main targets. The objective is to provide information about the ocean color products of FY-3A/MERSI, including sensor calibration, ocean color algorithms, ocean color prod- ucts validation and applications. Although there is a visible on-board calibration device, it cannot realize the on-board absolute radiometric calibration in the reflective solar bands. A multisite vicarious calibration method is developed, and used for monitoring the in-flight response change and providing post-launch cal- ibration coefficients updating. FY-3A/MERSI ocean color products consist of the water-leaving reflectance retrieved from an atmospheric correction algorithm, a chlorophyll a concentration （CHL1） and a pigment concentration （PIG1） from global empirical models, the chlorophyll a concentration （CHL2）, a total sus- pended mater concentration （TSM） and the absorption coefficient of CDOM and NAP （YS443） from Chi- na＇s regional empirical models. The atmospheric correction algorithm based on lookup tables and ocean color components concentration estimation models are described. By comparison with in situ data, the FY-3A/MERSI ocean color products have been validated and preliminary results are presented. Some suc- cessful ocean color applications such as algae bloom monitoring and coastal suspended sediment variation have demonstrated the usefulness of FY-3A/MERSI ocean color products.展开更多
Abstract A real-time photo-realistic rendering algorithm of ocean color is introduced in the paper, which considers the impact of ocean bio-optical model. The ocean bio-optical model mainly involves the phytoplankton,...Abstract A real-time photo-realistic rendering algorithm of ocean color is introduced in the paper, which considers the impact of ocean bio-optical model. The ocean bio-optical model mainly involves the phytoplankton, colored dissolved organic material （CDOM）, inorganic suspended particle, etc., which have different contributionsto absorption and scattering of light. We decompose the emergent light of the ocean surface into the reflected light from the sun and the sky, and the subsurface scattering light. We estab- lish an ocean surface transmission model based on ocean bidirectional reflectance distribution function （BRDF） and the Fresnel law, and this model＇s outputs would be the incident light parameters of subsurface scattering. Using ocean subsurface scattering algorithm combined with bio-optical model, we compute the scattering light emergent radiation in different directions. Then, we blend the re- flection of sunlight and sky light to implement the real-time ocean color rendering in graphics processing unit （GPU）. Finally, we use two kinds of radiance reflectance calculated by Hydrolight radiative transfer model and our algorithm to validate the physical reality of our method, and the results show that our algorithm can achieve real-time highly realistic ocean color scenes.展开更多
We examined regional empirical equations for estimating the surface concentration of particulate organic carbon （POC） in the South China Sea. These algorithms are based on the direct relationships between POC and th...We examined regional empirical equations for estimating the surface concentration of particulate organic carbon （POC） in the South China Sea. These algorithms are based on the direct relationships between POC and the blue-to-green band ratios of spectral remotely sensed reflectance, Rrs（λB）/Rrs（555）. The best error statistics among the considered formulas were produced using the power function POC （rag/ m3）=262.173 [Rrs（443）/Rrs（555）]^-0.940. This formula resulted in a small mean bias of approximately -2.52%, a normalized root mean square error of 31.1%, and a determination coefficient of 0.91. This regional empirical equation is different to the results of similar studies in other oceanic regions. Our validation results suggest that our regional empirical formula performs better than the global algorithm, in the South China Sea. The feasibility of this band ratio algorithm is primarily due to the relationship between POC and the green-to- blue ratio of the particle absorption coefficient. Colored dissolved organic matter can be an important source of noise in the band ratio formula. Finally, we applied the empirical algorithm to investigate POC changes in the southwest of Luzon Strait.展开更多
This paper demonstrates an atmospheric correction method to process MODIS/Aqua (Moderate-resolution Imaging Spectroradiometer) ocean color imagery over turbid coastal waters with the aid of concurrent CALIOP (Cloud-Ae...This paper demonstrates an atmospheric correction method to process MODIS/Aqua (Moderate-resolution Imaging Spectroradiometer) ocean color imagery over turbid coastal waters with the aid of concurrent CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) aerosol data, assuming that there exists "nonturbid" water in the study area where MODIS aerosol optical properties can be retrieved accurately. Aerosol properties from CALIOP measurements were obtained and related to those from MODIS. This relationship, combined with CALIOP aerosol data, was extended to turbid water to derive MODIS aerosol properties, where atmospheric correction using MODIS data alone often fails. By combining MODIS and CALIOP data, aerosol signals were separated from the total signals at the satellite level, and water-leaving radiances in turbid waters were subsequently derived. This method was tested on several MODIS/Aqua ocean color images over South China turbid waters. Comparison with field data shows that this method was effective in reducing the errors in the retrieved water-leaving radiance values to some extent. In the Zhujiang (Pearl) River Estuary, this method did not overestimate the aerosol effects as severely, and provided far fewer negative water-leaving radiance values than the NASA (National Aeronautics and Space Administration) default methods that used MODIS data alone.展开更多
Consistent bio-optical properties across multiple ocean color satellites are the key prerequisite to merging products from these satellites,thereby enhancing spatial coverage and extending temporal spans.However,due t...Consistent bio-optical properties across multiple ocean color satellites are the key prerequisite to merging products from these satellites,thereby enhancing spatial coverage and extending temporal spans.However,due to factors such as sensor specifics and separate data processing algorithms,bio-optical properties(e.g.,remote sensing reflectance,R_(rs))from different ocean color missions exhibit varying discrepancies in oceanic,coastal,and inland waters.Here,we introduce a cross-satellite atmospheric correction(CSAC)scheme,which could greatly improve the consistency of R_(rs)products between MODIS-Aqua and other satellite ocean color missions.Specifically,using an inclusive high-quality R_(rs)dataset of oceanic waters obtained from MODIS-Aqua as the reference,and as an example,top-of-atmosphere reflectance from SeaWiFS(Sea-Viewing Wide Field-of-View Sensor)is directly processed to MODIS-Aqua-equivalent R_(rs)(R^(MA−eqv)_(rs))via CSAC.As a demonstration,for independent space-time matched measurements between MODIS-Aqua and SeaWiFS,the mean absolute percent difference(MAPD)between RMA−eqv rs and MODIS-Aqua R_(rs)ranges from 5.9%to 22.2%across wavelengths from 412 to 667 nm.In contrast,the MAPD values between the NASA standard SeaWiFS and MODIS-Aqua R_(rs)products range from 10.1%to 55.1%for the same spectral bands.These results highlight the potential of CSAC in obtaining consistent R_(rs)products and,subsequently,R_(rs)-derived bio-optical properties,from various ocean color satellites,facilitating extensive and long-term ocean color observations of the global ocean.展开更多
In this paper, a new approach to the optimal retrieval of the ocean color based on the variational method is developed by setting up a rational target functional combining with the Broydor Fletcher, Goldfarb, Shanno ...In this paper, a new approach to the optimal retrieval of the ocean color based on the variational method is developed by setting up a rational target functional combining with the Broydor Fletcher, Goldfarb, Shanno （BFGS） optimal algorithm. The numerical tests and the exemplary retrievals are carried out and compared with the statistical retrievals and the optimal retrievals based on the genetic algorithm. The results show that this approach enjoys a higher accuracy as compared to the statistical method and a higher efficiency as compared to the genetic algorithm. The optimal retrieval method presented in this paper provides a new idea for the ocean color inversion and could also be used as a reference for the direct assimilation of the satellite data into the ecological models.展开更多
Using the techniques of quantitative ocean color sensing, the in-water ocean color algorithms for sediment and chlorophyll-a retrieval are established for CBERS-02 CCD broad spectral bands based on in situ data. The r...Using the techniques of quantitative ocean color sensing, the in-water ocean color algorithms for sediment and chlorophyll-a retrieval are established for CBERS-02 CCD broad spectral bands based on in situ data. The remote sensing reflectance of water is derived from CCD radiance data by a clear water atmospheric correction algorithm. Then, the sediment and chlorophyll-a concentrations are retrieved from CCD image. The sediment retrieval is quite satisfactory, but the chlorophyll-a retrieval is not so good because of the broadband width and low signal-to-noise ratio of the CCD camera.展开更多
The recently developed quasi-analytical algo-rithm (QAA) is a promising algorithm for deriving inherentoptical properties from ocean color. Unlike the conventionalsemi-analytical algorithm, QAA does not need a priorik...The recently developed quasi-analytical algo-rithm (QAA) is a promising algorithm for deriving inherentoptical properties from ocean color. Unlike the conventionalsemi-analytical algorithm, QAA does not need a prioriknowledge of the spectral shape of chlorophyll absorption.However, several empirical relations, which may not be uni-versally applicable and can result in low noise tolerance, areinvolved in QAA. In this study, the Bayesian inversion theoryis introduced to improve the performance of QAA. In theestimation of total absorption coefficient at the referencewavelength, instead of empirical algorithms used in the QAAthe Bayesian approach is employed in combination with anoptical model that uses separate parameters to account ex-plicitly for the contribution of molecular and particle scat-terings to remote sensing reflectance, a priori knowledgeproduced by the QAA, the Akaike’s Bayesian informationcriterion (ABIC) for choosing the optimal regularizationparameter, and genetic algorithms for global optimization.Coefficients at other wavelengths are then derived using anempirical estimate of particle backscattering spectral shape.When applied to a simulated dataset synthesized by IOCCG,the Bayesian algorithm outperforms QAA algorithm, espe-cially in higher chlorophyll concentration waters. The rootmean square errors (RMSEs) between the true and the de-rived a(440) and bb(440) are reduced from 0.918 and 0.039m–1 for QAA-555 to 0.367 and 0.023 m–1 for Bayes-555, 0.205and 0.007 m–1 for QAA-640 to 0.092 and 0.005 m–1 forBayes-640, and 0.207 and 0.007 m–1 for QAA-blending to0.096 and 0.005 m–1 for Bayes-blending. Results of noise sen-sitivity analysis show that the Bayesian algorithm is morerobust than QAA.展开更多
Water clarity(Secchi disk depth, Z_(SD)) and Forel-Ule Index(FUI) are critical ecological indicators for assessing water quality. Although satellite remote sensing serves as a vital tool for large-scale and long-term ...Water clarity(Secchi disk depth, Z_(SD)) and Forel-Ule Index(FUI) are critical ecological indicators for assessing water quality. Although satellite remote sensing serves as a vital tool for large-scale and long-term water quality monitoring,low accuracy, coarse resolution, and incomplete spatial coverage of existing satellite Z_(SD) and FUI products hindered the reliable ecological assessment of water quality. Here, a long-term(2003-2023) satellite dataset of monthly Z_(SD) and FUI was developed by applying the advanced high-accuracy retrieval algorithms and reconstruction method to 35 546Moderate-resolution Imaging Spectroradiometer(MODIS) images over China coastal waters. The new dataset exhibited superior performance compared to the existing one, in terms of higher accuracy(Mean Absolute Percentage Error,MAPE = 28.89% for Z_(SD) and MAPE = 34.46% for FUI), spatio-temporal resolution(monthly, 1 km), and spatial coverage(99.53%), with the most significant improvement found in the nearshore turbid waters. By leveraging this dataset, the ecological impact of human activities on water quality was accurately revealed, as indicated by the significant Z_(SD) improvements during terrestrial pollution control, which was misinterpreted by previous satellite products.Besides, natural factor-induced water quality variability was also successfully captured, particularly the seasonal dynamics of suspended sediment plumes in the East China Sea. The new dataset and adopted methods may provide essential support for the accurate monitoring, ecological assessment, and sustainable management of marine ecosystems.展开更多
基金the National Natural Science Foundation of China under contract Nos 40706061 and 40506036High Tech Research and Development (863) Program of China under contract Nos 2008AA09Z104 and 2007AA12Z137
文摘After many years＇ endeavor of research and application practice, the ocean color remote sensing in China has been growing into a new technique with valuable practicality from its initiate stage of trial research. With the aim of operational service, several kinds of ocean color remote sensing application systems have been developed and realized the long-term marine environmental monitoring utilizing the real-time or near real-time satellite and airborne remote sensing data. New progresses in the technology and application of ocean color remote sensing in China are described, including the research of key techniques and the development of various application systems. Meanwhile, according to the application status and demand, the prospective development of Chinese ocean color remote sensing is brought forward. With Chinese second ocean color satellite （ HY-1 B） orbiting on 11 April 2007 and the development of airborne ocean color remote sensing system for Chinese surveillance planes, great strides will take place in Chinese ocean color remote sensing application with the unique function in marine monitoring, resources management and national security, etc.
基金The National Natural Science Foundation of China under contract No.41306193the Research and Development Special Foundation for Public Welfare Industry under of China contract No.201105016the Basic Research of First Institute of Oceanography,State Oceanic Administration under contract No.GY2014T03
文摘A method to estimate the thickness of the sea ice of the Bohai Sea is proposed using geostationary ocean color imager （GOCI） data and then applied to the dynamic monitoring of the sea ice thickness in the Bohal Sea during the winter of 2014 to 2015. First of all, a model is given between the GOCI shortwave broadband albedo and the reflectance of each band with high temporal resolution GOCI data. Then, the relationship model between the sea ice thickness and the GOCI shortwave broadband albedo is established and applied to the thickness extraction of the sea ice in the Bohai Sea. Finally, the sea ice thickness extraction method is tested by the results based on the MODIS data, thermodynamic empirical models （Lebedev and Zubov）, and the in situ ice thickness data. The test results not only indicated that the sea ice thickness retrieval method based on the GOCI data was a good correlation （r2〉0.66） with the sea ice thickness retrieved by the MODIS and thermodynamic empirical models, but also that the RMS is only 6.82 cm different from the thickness of the sea ice based on the GOCI and in situ data.
文摘Coastal water environment is essentially enhanced by ocean color which is basically decided by substances concentration in water such as chlorophyll, suspended material and yellow substance. It is very difficult, even not possible, to detect water color by expensive ship routing, because of its temporal and spatial variety of feature and scales in the very complicated dynamical system of coastal water. With the development of satellite technique in the last 20 a, space sensors can be applied to detect ocean color by measuring the spectra of water leaving radiance.It is proven that ocean color remote sensing is a powerful tool for understanding the process of oceanic biology and physics. Since the 1980s, great attention has been paid to the advanced remote sensing technique in China, especially to development of satellite programs for the coastal water environment. On 7 September 1988, China launched her first polar orbit satellite FY-1A for meteorological and oceanographic application (water color and temperature) and the second satellite FY-1B two years later. In May 1999, China launched her second generation environment satellite FY-1C with higher sensitivies, more channels and stable operation. The special ocean color satellite HY-1 is planned to be in the orbit in 2001, whose main purpose is to detect the coastal water environment of China seas. China is also developing a very advantageous sensor termed as Chinese moderate imaging spectra radiometer (CMODIS) with 91 channels, which will be a good candidate of the third generation satellite FY-3 in 2003. The technical system of ocean color remote sensing was developed by the Second Institute of Oceanography (SIO), State Oceanic Administration (SOA) in 1997. The system included data receiving, processing, distribution, calibration, validation and application units. The Hangzhou Station of SIO, SOA has the capability to receive FY-1 and AVHRR data since 1989. It was also a SeaWiFS scientific research station authorized by NASA,USA to free receive SeaWiFS data from 16 September 1997. In the recent years, the local algorithms of atmospheric correction and inversion of ocean color have been developed for FY-1C and SeaWiFS, to improve the accuracy of the measurement from satellites efficiently. The satellite data are being applied to monitor coastal water environment, such as the spatial distribution of chlorophyll, suspended material and yellow substance, red tide detection and coastal current study. The results show that the ocean color remote sensing has latent capacity in the detection of coastal water environment.In consideration of the update technique progress of ocean color remote sensing and its more important role in the detection of coastal water in the 2000s, some suggestions are set forth, which would be beneficial to the design of a cheaper but practical coastal water detection system for marine environment preservation.
基金The National Natural Science Foundation project of China under contract No.40606043the National Basic Research Program of China under contract No.2006CB403702
文摘Waters along China coast are very turbid with high concentrations of suspended sediment nearly all the time,especially at the Hangzhou Bay,the Changjiang （Yangtze） River Estuary and the shoal along Jiangsu Province.In these turbid and optically complex waters,the standard MODIS ocean color products tend to have invalid values.Because the water-leaving radiances in the near-infrared （NIR） are significant resulting from the strong scattering of suspended particles,the standard MODIS atmospheric correction algorithm often gets no results or produces significant errors.And because of the complex water optical properties,the OC3 model used in the standard MODIS data processing tends to get extremely high chlorophyll-a （Chl-a） concentrations.In this paper,we present an atmospheric correction approach using MODIS short wave infrared （SWIR） bands based on the fact that water-leaving radiances are negligible in the SWIR region because of the extreme strong absorption of water even in turbid waters.A regional Chl-a concentration estimation model is also constructed for MODIS from in situ data.These algorithms are applied to MODIS Aqua data processing in the China coastal regions.In situ data collected in the Yellow Sea and the East China Sea in spring and autumn,2003 are used to validate the performance.Reasonably good results have been obtained.It is noted that water-leaving reflectance in the NIR bands are significant in waters along the China coast with high sediment loadings.The satellite derived and in-situ reflectance spectra can match in the turbid waters along China coast,and there is relatively good linear relationship between satellite derived and in-situ reflectance.The RMSE value of Rrs（λ） is 0.0031 sr ？1 for all the nine ocean color bands （412 to 869 nm）.The satellite-derived Chl-a value is in the reasonable range and the root mean square percentage difference is 46.1%.
基金supported by the National Natural Science Foundation of China under contract No.40506036the High Tech Research and Development"863"Program of China under contract No.2003AA131160-04the Science and Technology Plan of Zhejiang Province of China under contract Nos 2004E60054 and 2004C13027.
文摘The current exact Rayleigh scattering calculation of ocean color remote sensing uses the look-up table （LUT）, which is usually created for a special remote sensor and cannot be applied to other sensors. For practical application, a general purpose Rayleigh scattering LUT which can be applied to all ocean color remote sensors is generated. An adding-doubling method to solve the vector radiative transfer equation in the plane-parallel atmosphere is deduced in detail. Compared with the exact Rayleigh scattering radiance derived from the MODIS exact Rayleigh scattering LUT, it is proved that the relative error of Rayleigh scattering calculation with the adding-doubling method is less than 0.25%, which meets the required accuracy of the atmospheric correction of ocean color remote sensing. Therefore, the adding-doubling method can be used to generate the exact Rayleigh scattering LUT for the ocean color remote sensors. Finally, the general purpose exact Rayleigh scattering LUT is generated using the adding-doubling method. On the basis of the general purpose LUT, the calculated Rayleigh scattering radiance is tested by comparing with the LUTs ofMODIS, SeaWiFS and the other ocean color sensors, showing that the relative errors are all less than 0.5%, and this general purpose LUT can be applied to all ocean color remote sensors.
基金The National Basic Research Program (973 Program) of China under contract No.2010CB950803National Meteorological Special Project of China under contract No.GYHY200906036
文摘A medium resolution spectral imager （MERSI） on-board the first spacecraft of the second generation of Chinas polar-orbit meteorological satellites FY-3A, is a MODIS-like sensor with 20 bands covering visible to thermal infrared spectral region. FY-3A/MERSI is capable of making continuous global observations, and ocean color application is one of its main targets. The objective is to provide information about the ocean color products of FY-3A/MERSI, including sensor calibration, ocean color algorithms, ocean color prod- ucts validation and applications. Although there is a visible on-board calibration device, it cannot realize the on-board absolute radiometric calibration in the reflective solar bands. A multisite vicarious calibration method is developed, and used for monitoring the in-flight response change and providing post-launch cal- ibration coefficients updating. FY-3A/MERSI ocean color products consist of the water-leaving reflectance retrieved from an atmospheric correction algorithm, a chlorophyll a concentration （CHL1） and a pigment concentration （PIG1） from global empirical models, the chlorophyll a concentration （CHL2）, a total sus- pended mater concentration （TSM） and the absorption coefficient of CDOM and NAP （YS443） from Chi- na＇s regional empirical models. The atmospheric correction algorithm based on lookup tables and ocean color components concentration estimation models are described. By comparison with in situ data, the FY-3A/MERSI ocean color products have been validated and preliminary results are presented. Some suc- cessful ocean color applications such as algae bloom monitoring and coastal suspended sediment variation have demonstrated the usefulness of FY-3A/MERSI ocean color products.
基金jointly supported by the International Cooperation and Exchange Projects of the National Natural Science Foundation of China (No.61361163001)the National Key Scientific Instrument and Equipment Development Projects of National Natural Science Foundation of China (No.41527901)the National High-Tech R&D Program (863 Program) (No.2013AA09A505)
文摘Abstract A real-time photo-realistic rendering algorithm of ocean color is introduced in the paper, which considers the impact of ocean bio-optical model. The ocean bio-optical model mainly involves the phytoplankton, colored dissolved organic material （CDOM）, inorganic suspended particle, etc., which have different contributionsto absorption and scattering of light. We decompose the emergent light of the ocean surface into the reflected light from the sun and the sky, and the subsurface scattering light. We estab- lish an ocean surface transmission model based on ocean bidirectional reflectance distribution function （BRDF） and the Fresnel law, and this model＇s outputs would be the incident light parameters of subsurface scattering. Using ocean subsurface scattering algorithm combined with bio-optical model, we compute the scattering light emergent radiation in different directions. Then, we blend the re- flection of sunlight and sky light to implement the real-time ocean color rendering in graphics processing unit （GPU）. Finally, we use two kinds of radiance reflectance calculated by Hydrolight radiative transfer model and our algorithm to validate the physical reality of our method, and the results show that our algorithm can achieve real-time highly realistic ocean color scenes.
基金Supported by the National Natural Science Foundation of China(Nos.41376042,41176035)the Natural Science for Youth Foundation(No.41206029)+2 种基金the Youth Foundation by South China Sea Institute of Oceanology,Chinese Academy of Sciences(No.SQ201102)the Open Research Fund of State Key Laboratory of Estuarine and Coastal Research(No.SKLEC-KF201302)the Open Project Program of State Key Laboratory of Tropical Oceanography,South China Sea Institute of Oceanology,Chinese Academy of Sciences(No.LTOZZ1201)
文摘We examined regional empirical equations for estimating the surface concentration of particulate organic carbon （POC） in the South China Sea. These algorithms are based on the direct relationships between POC and the blue-to-green band ratios of spectral remotely sensed reflectance, Rrs（λB）/Rrs（555）. The best error statistics among the considered formulas were produced using the power function POC （rag/ m3）=262.173 [Rrs（443）/Rrs（555）]^-0.940. This formula resulted in a small mean bias of approximately -2.52%, a normalized root mean square error of 31.1%, and a determination coefficient of 0.91. This regional empirical equation is different to the results of similar studies in other oceanic regions. Our validation results suggest that our regional empirical formula performs better than the global algorithm, in the South China Sea. The feasibility of this band ratio algorithm is primarily due to the relationship between POC and the green-to- blue ratio of the particle absorption coefficient. Colored dissolved organic matter can be an important source of noise in the band ratio formula. Finally, we applied the empirical algorithm to investigate POC changes in the southwest of Luzon Strait.
基金Supported by the National Basic Research Program of China (973 Program, Nos. 2009CB723905, 2006CB701300)the National High Technology Research and Development Program of China (863 Program, No. 2007AA12Z161)+3 种基金the NSFC (Nos. 40676094, 40721001, 40706060)MOST, China (No. 2007BAC23B05)Open Fund of Nanchang University (No. Z03975)the Open Fund of Ocean University of China for visiting Ph. D students.
文摘This paper demonstrates an atmospheric correction method to process MODIS/Aqua (Moderate-resolution Imaging Spectroradiometer) ocean color imagery over turbid coastal waters with the aid of concurrent CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) aerosol data, assuming that there exists "nonturbid" water in the study area where MODIS aerosol optical properties can be retrieved accurately. Aerosol properties from CALIOP measurements were obtained and related to those from MODIS. This relationship, combined with CALIOP aerosol data, was extended to turbid water to derive MODIS aerosol properties, where atmospheric correction using MODIS data alone often fails. By combining MODIS and CALIOP data, aerosol signals were separated from the total signals at the satellite level, and water-leaving radiances in turbid waters were subsequently derived. This method was tested on several MODIS/Aqua ocean color images over South China turbid waters. Comparison with field data shows that this method was effective in reducing the errors in the retrieved water-leaving radiance values to some extent. In the Zhujiang (Pearl) River Estuary, this method did not overestimate the aerosol effects as severely, and provided far fewer negative water-leaving radiance values than the NASA (National Aeronautics and Space Administration) default methods that used MODIS data alone.
基金support from the National Natural Science Foundation of China(#42430107 and#42250710150)the National Key Research and Development Program of China(2022YFC3104903)Fujian Satellite Data Development,Co.,Ltd.,and Fujian Haisi Digital Technology Co.,Ltd.
文摘Consistent bio-optical properties across multiple ocean color satellites are the key prerequisite to merging products from these satellites,thereby enhancing spatial coverage and extending temporal spans.However,due to factors such as sensor specifics and separate data processing algorithms,bio-optical properties(e.g.,remote sensing reflectance,R_(rs))from different ocean color missions exhibit varying discrepancies in oceanic,coastal,and inland waters.Here,we introduce a cross-satellite atmospheric correction(CSAC)scheme,which could greatly improve the consistency of R_(rs)products between MODIS-Aqua and other satellite ocean color missions.Specifically,using an inclusive high-quality R_(rs)dataset of oceanic waters obtained from MODIS-Aqua as the reference,and as an example,top-of-atmosphere reflectance from SeaWiFS(Sea-Viewing Wide Field-of-View Sensor)is directly processed to MODIS-Aqua-equivalent R_(rs)(R^(MA−eqv)_(rs))via CSAC.As a demonstration,for independent space-time matched measurements between MODIS-Aqua and SeaWiFS,the mean absolute percent difference(MAPD)between RMA−eqv rs and MODIS-Aqua R_(rs)ranges from 5.9%to 22.2%across wavelengths from 412 to 667 nm.In contrast,the MAPD values between the NASA standard SeaWiFS and MODIS-Aqua R_(rs)products range from 10.1%to 55.1%for the same spectral bands.These results highlight the potential of CSAC in obtaining consistent R_(rs)products and,subsequently,R_(rs)-derived bio-optical properties,from various ocean color satellites,facilitating extensive and long-term ocean color observations of the global ocean.
基金Project supported by the National Natural Science Foundation of China(Grant No. 41105012)Startup Fund Scientific Research from the Institute of Meteorology, PLA University of Science and Technology(Grant No. 2009QX08)
文摘In this paper, a new approach to the optimal retrieval of the ocean color based on the variational method is developed by setting up a rational target functional combining with the Broydor Fletcher, Goldfarb, Shanno （BFGS） optimal algorithm. The numerical tests and the exemplary retrievals are carried out and compared with the statistical retrievals and the optimal retrievals based on the genetic algorithm. The results show that this approach enjoys a higher accuracy as compared to the statistical method and a higher efficiency as compared to the genetic algorithm. The optimal retrieval method presented in this paper provides a new idea for the ocean color inversion and could also be used as a reference for the direct assimilation of the satellite data into the ecological models.
文摘Using the techniques of quantitative ocean color sensing, the in-water ocean color algorithms for sediment and chlorophyll-a retrieval are established for CBERS-02 CCD broad spectral bands based on in situ data. The remote sensing reflectance of water is derived from CCD radiance data by a clear water atmospheric correction algorithm. Then, the sediment and chlorophyll-a concentrations are retrieved from CCD image. The sediment retrieval is quite satisfactory, but the chlorophyll-a retrieval is not so good because of the broadband width and low signal-to-noise ratio of the CCD camera.
基金This work was supported by the“863”Program of China(Grant No.2004AA639860)the National Natural Science Foundation of China(Grant No.40306028)the Guangdong Natural Science Foundation(Grant No.32616).
文摘The recently developed quasi-analytical algo-rithm (QAA) is a promising algorithm for deriving inherentoptical properties from ocean color. Unlike the conventionalsemi-analytical algorithm, QAA does not need a prioriknowledge of the spectral shape of chlorophyll absorption.However, several empirical relations, which may not be uni-versally applicable and can result in low noise tolerance, areinvolved in QAA. In this study, the Bayesian inversion theoryis introduced to improve the performance of QAA. In theestimation of total absorption coefficient at the referencewavelength, instead of empirical algorithms used in the QAAthe Bayesian approach is employed in combination with anoptical model that uses separate parameters to account ex-plicitly for the contribution of molecular and particle scat-terings to remote sensing reflectance, a priori knowledgeproduced by the QAA, the Akaike’s Bayesian informationcriterion (ABIC) for choosing the optimal regularizationparameter, and genetic algorithms for global optimization.Coefficients at other wavelengths are then derived using anempirical estimate of particle backscattering spectral shape.When applied to a simulated dataset synthesized by IOCCG,the Bayesian algorithm outperforms QAA algorithm, espe-cially in higher chlorophyll concentration waters. The rootmean square errors (RMSEs) between the true and the de-rived a(440) and bb(440) are reduced from 0.918 and 0.039m–1 for QAA-555 to 0.367 and 0.023 m–1 for Bayes-555, 0.205and 0.007 m–1 for QAA-640 to 0.092 and 0.005 m–1 forBayes-640, and 0.207 and 0.007 m–1 for QAA-blending to0.096 and 0.005 m–1 for Bayes-blending. Results of noise sen-sitivity analysis show that the Bayesian algorithm is morerobust than QAA.
基金The National Key Research and Development Program of China under contract No.2023YFB3905305。
文摘Water clarity(Secchi disk depth, Z_(SD)) and Forel-Ule Index(FUI) are critical ecological indicators for assessing water quality. Although satellite remote sensing serves as a vital tool for large-scale and long-term water quality monitoring,low accuracy, coarse resolution, and incomplete spatial coverage of existing satellite Z_(SD) and FUI products hindered the reliable ecological assessment of water quality. Here, a long-term(2003-2023) satellite dataset of monthly Z_(SD) and FUI was developed by applying the advanced high-accuracy retrieval algorithms and reconstruction method to 35 546Moderate-resolution Imaging Spectroradiometer(MODIS) images over China coastal waters. The new dataset exhibited superior performance compared to the existing one, in terms of higher accuracy(Mean Absolute Percentage Error,MAPE = 28.89% for Z_(SD) and MAPE = 34.46% for FUI), spatio-temporal resolution(monthly, 1 km), and spatial coverage(99.53%), with the most significant improvement found in the nearshore turbid waters. By leveraging this dataset, the ecological impact of human activities on water quality was accurately revealed, as indicated by the significant Z_(SD) improvements during terrestrial pollution control, which was misinterpreted by previous satellite products.Besides, natural factor-induced water quality variability was also successfully captured, particularly the seasonal dynamics of suspended sediment plumes in the East China Sea. The new dataset and adopted methods may provide essential support for the accurate monitoring, ecological assessment, and sustainable management of marine ecosystems.
