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
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.Wi...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-1B)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
China has great progress in the technology and application of ocean color remote sensing during 2004-2006. In this report, firstly, four major technical advances are displaying, including (1) the vector radiative tran...China has great progress in the technology and application of ocean color remote sensing during 2004-2006. In this report, firstly, four major technical advances are displaying, including (1) the vector radiative transfer numerical model of coupled ocean-atmosphere system; (2) the atmospheric correction algorithm specialized on Chinese high turbid water; (3) systematical research of hyper-spectrum ocean color remote sensing; (4) local algorithms of oceanic parameters, like ocean color components, ocean primary productivity, water transparency, water quality parameters, etc. On the foundation of technical advances, ocean color remote sensing takes effect on ocean environment monitoring, with four major kinds of application systems, namely, (1) the automatic multi-satellites data receiving, processing and application system; (2) the shipboard satellite data receiving and processing system for fishery ground information; (3) Coastal water quality monitoring system, integrating satellite and airborne remote sensing technology and ship measurement; (4) the preliminary system of airborne ocean color remote sensing application system. Finally, the prospective development of Chinese ocean color remote sensing is brought forward. With Chinese second ocean color satellite (HY-1B) orbiting, great strides will take place in Chinese ocean color information accumulation and application.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
Dissolved organic carbon(DOC)and particulate organic carbon(POC)are basic variables for the ocean carbon cycle.Knowledge of the distribution and inventory of these variables is important for a better estimation and un...Dissolved organic carbon(DOC)and particulate organic carbon(POC)are basic variables for the ocean carbon cycle.Knowledge of the distribution and inventory of these variables is important for a better estimation and understanding of the global carbon cycle.Owing to its considerable advantages in spatial and temporal coverage,remote sensing data provide estimates of DOC and POC inventories,which are able to give a synthetic view for the distribution and transportation of carbon pools.To estimate organic carbon inventories using remote sensing involves integration of the surface concentration and vertical profile models,and the development of these models is critical to the accuracy of estimates.Hence,the distribution and control factors of DOC and POC in the ocean first are briefly summarized,and then studies of DOC and POC inventories and flux estimations are reviewed,most of which are based on field data and few of which consider the vertical distributions of POC or DOC.There is some research on the estimation of POC inventory by remote sensing,mainly in the open ocean,in which three kinds of vertical profile models have been proposed:the uniform,exponential decay,and Gauss models.However,research on remote-sensing estimation of the DOC inventory remains lacking.A synthetic review of approaches used to estimate the organic carbon inventories is offered and the future development of methods is discussed for such estimates using remote sensing data in coastal waters.展开更多
A new method for measuring ocean wave length and direction from SEASAT SyntheticAperture Radar (SAR)remote sensing image is presented in the paper. In the new method, an ocean waveimage is sampled in certain direction...A new method for measuring ocean wave length and direction from SEASAT SyntheticAperture Radar (SAR)remote sensing image is presented in the paper. In the new method, an ocean waveimage is sampled in certain directions, the samples are then analyzed by using one dimensional FourierTransformation to calculate the ocean wave correlation function. Finally the ocean wave length and direc-tion are determined from the ocean wave correlation function. The new method is better than the tradition-al two-dimensional Fourier Transformation method in both consuming time and precision .展开更多
This paper is divided into three parts.In the first part,it describes the major objects of o-cean monitoring and investigation by means of satellite remote sensing technology,including the observation of dynamic pheno...This paper is divided into three parts.In the first part,it describes the major objects of o-cean monitoring and investigation by means of satellite remote sensing technology,including the observation of dynamic phenomena of ocean,ocean color and sea surface temperature as well as mapping of coastal zone and islands.In the second part,some research results of oceanic environment which were obtained in the past decade in China are presented.In the third part,some fundamental technologies are described,to which we should pay attention in order to make great contribution to marine environment by using satellite remote sensing technology in the coming few years in China.展开更多
Requirements for monitoring the coastal zone environment are first summarized.Then the application of hyperspectral remote sensing to coast environment investigation is introduced,such as the classification of coast b...Requirements for monitoring the coastal zone environment are first summarized.Then the application of hyperspectral remote sensing to coast environment investigation is introduced,such as the classification of coast beaches and bottom matter,target recognition,mine detection,oil spill identification and ocean color remote sensing.Finally,what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.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 the b...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,R rs( λ B)/ R rs(555). The best error statistics among the considered formulas were produced using the power function POC(mg/m 3)=262.173 [ R rs(443)/ R rs(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-toblue 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
An important goal in ocean colour remote sensing is to accurately detect different phytoplank- ton groups with the potential uses including the validation of multi-phytoplankton carbon cycle models; synoptically monit...An important goal in ocean colour remote sensing is to accurately detect different phytoplank- ton groups with the potential uses including the validation of multi-phytoplankton carbon cycle models; synoptically monitoring the health of our oceans, and improving our understanding of the bio-geochemical interactions between phytoplankton and their environment. In this paper a new algorithm is developed for detecting three dominant phytoplankton size classes based on distinct differences in their optical signatures. The technique is validated against an independent cou- pled satellite reflectance and in situ pigment dataset and run on the 10-year NASA Sea viewing Wide Field of view Sensor (SeaWiFS) data series. Results indicate that on average 3.6% of the global oceanic surface layer is dominated by microplankton, 18.0% by nanoplankton and 78.4% by picoplankton. Results, however, are seen to vary depending on season and ocean basin.展开更多
For the application of soil moisture and ocean salinity(SMOS)remotely sensed sea surface salinity(SSS)products,SMOS SSS global maps and error characteristics have been investigated based on quality control information...For the application of soil moisture and ocean salinity(SMOS)remotely sensed sea surface salinity(SSS)products,SMOS SSS global maps and error characteristics have been investigated based on quality control information.The results show that the errors of SMOS SSS products are distributed zonally,i.e.,relatively small in the tropical oceans,but much greater in the southern oceans in the Southern Hemisphere(negative bias)and along the southern,northern and some other oceanic margins(positive or negative bias).The physical elements responsible for these errors include wind,temperature,and coastal terrain and so on.Errors in the southern oceans are due to the bias in an SSS retrieval algorithm caused by the coexisting high wind speed and low temperature;errors along the oceanic margins are due to the bias in a brightness temperature(TB)reconstruction caused by the high contrast between L-band emissivities from ice or land and from ocean;in addition,some other systematic errors are due to the bias in TB observation caused by a radio frequency interference and a radiometer receivers drift,etc.The findings will contribute to the scientific correction and appropriate application of the SMOS SSS products.展开更多
Traditional methods of extracting the ocean wave eddy information from remotely sensed imagery mainly use the edge detection technology such as Canny and Hough operators. However, due to the complexities of ocean eddi...Traditional methods of extracting the ocean wave eddy information from remotely sensed imagery mainly use the edge detection technology such as Canny and Hough operators. However, due to the complexities of ocean eddies and image itself, it is sometimes difficult to successfully detect ocean eddies using these methods. A multifractal filtering technology is proposed for extraction of ocean eddies and demonstrated using NASA MODIS,SeaWiFS and NOAA satellite data set in the typical area, such as ocean west boundary current. Results showed that the new method has a superior performance over the traditional methods.展开更多
Based on the in situ optical measurements in the Bohai Sea of China, which belongs to a typical case-2 water area, we studied the characteristics of DCM (deep chlorophyll maximum) such as its spatial distribution, ver...Based on the in situ optical measurements in the Bohai Sea of China, which belongs to a typical case-2 water area, we studied the characteristics of DCM (deep chlorophyll maximum) such as its spatial distribution, vertical profile, etc. We found that when the depth of the chlorophyll maximum is comparatively small, even in turbid coastal water regions, there is always a good correlation between the concentrations of chlorophyll maximum and the satellite-received signals in blue-green spectral bands; the correlation is even better than that between the surface chlorophyll concentrations and the satellite-received signals. The strong correlation existing even in turbid coastal water regions indicates that an ocean color model to retrieve the concentration of DCM can be constructed for coastal waters if a comprehensive knowledge of the vertical distribution of chlorophyll concentration in the Bohai Sea of China is available.展开更多
Remote sensing techniques have the potential to provide information on agricultural crops quantitstively,instantaneously and above all nondestrctively over large areas.Crop simulation models describe the relationship ...Remote sensing techniques have the potential to provide information on agricultural crops quantitstively,instantaneously and above all nondestrctively over large areas.Crop simulation models describe the relationship between physiological process in plants and environmental growing conditions.The integration between remote sensing data and crop growth simulation model is an important trent for yield estirmation and prediction,since remote sensing can provide information on the actual status of the agricultural crop.In this study,a new model(Rice-SRS) was developed based mainly on ORYZA1 model and modified to accept remote sensing data as input from different sources.The modelc an accept three kinds of NDVI,data.NOAA AVHRR(LAC)-NDVI,NOAA AVHRR(GAC)-NDVI and radiometric measurements-HDVI,The integration between NOAA AVHRR(LAC) data and simulation model as applied to Rice-SPS resulted in accurate estimates for rice yield in the Shaoxing area.reduced the estimating error to 1.027%,0.794% and (-0.787%) for early,single,and late season repectively.Utilizing NDVI data derived from NOAA AVHRR(GAC) as input in Rice-SRS can yield good estimation for rice yield with the average error (-7.43%) .Testing the new model for radiometric meassurements showed that the average estimation error for 10 varieties under early rice conditions was less than 1%.展开更多
The precision of Aster data is higher than that of Landsat series of multispectral remote sensing data,which can more accurately reveal the distribution of altered minerals.It plays an important role in prospecting,bu...The precision of Aster data is higher than that of Landsat series of multispectral remote sensing data,which can more accurately reveal the distribution of altered minerals.It plays an important role in prospecting,but it is rarely used in areas with complex terrain and high vegetation coverage.Based on this purpose,this study used Aster remote sensing data,and took Gongchangling iron deposit as a case study.It combined the mineral spectrum theory and the basic geologic data of the study area,using the model of principal component analysis(PCA)and color synthesis to extract abnormal altered minerals.The results show that the distribution of identified anomalies is basically consistent with the existing geological data in this study area,which provides a reliable reference for the mineral resources ex-ploration and delineation of mining areas.展开更多
In this paper,technological progress for China's microwave remote sensing is intro-duced.New developments of the microwave remote sensing instruments for meteorological satellite FY-3,ocean dynamic measurement sat...In this paper,technological progress for China's microwave remote sensing is intro-duced.New developments of the microwave remote sensing instruments for meteorological satellite FY-3,ocean dynamic measurement satellite(HY-2),environment small SAR satellite(HJ-1C) and China's lunar exploration satellite(Chang'E-1),geostationary orbit meteorological satellite FY-4M,are reported.展开更多
The greatest advantage of remote sensing over conventional measurements lies in the opportunity to carry out detailed spatio-temporal analysis of land and ocean features on a very frequent basis. This paper analyses t...The greatest advantage of remote sensing over conventional measurements lies in the opportunity to carry out detailed spatio-temporal analysis of land and ocean features on a very frequent basis. This paper analyses the contribution of satellite imagery to atmospheric, geophysical and ocean studies and management in West Africa since the early 1980s.The detailed application of data from optical sensors (e.g. Meteosat,NOAA/AVHRR, SPOT,L andsat TM, etc.) for weather prediction, hydrogeological, landuse/cover and cartographic studies has been acknowledged. However, the use of microwave (e.g. SAR) and optical data for ocean monitoring and studies in the sub-region is still very limited. Even though sufficient remote sensing expertise and infrastructure is perceived in the region, no clearly defined networking or database exists.展开更多
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 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-1B)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.
文摘China has great progress in the technology and application of ocean color remote sensing during 2004-2006. In this report, firstly, four major technical advances are displaying, including (1) the vector radiative transfer numerical model of coupled ocean-atmosphere system; (2) the atmospheric correction algorithm specialized on Chinese high turbid water; (3) systematical research of hyper-spectrum ocean color remote sensing; (4) local algorithms of oceanic parameters, like ocean color components, ocean primary productivity, water transparency, water quality parameters, etc. On the foundation of technical advances, ocean color remote sensing takes effect on ocean environment monitoring, with four major kinds of application systems, namely, (1) the automatic multi-satellites data receiving, processing and application system; (2) the shipboard satellite data receiving and processing system for fishery ground information; (3) Coastal water quality monitoring system, integrating satellite and airborne remote sensing technology and ship measurement; (4) the preliminary system of airborne ocean color remote sensing application system. Finally, the prospective development of Chinese ocean color remote sensing is brought forward. With Chinese second ocean color satellite (HY-1B) orbiting, great strides will take place in Chinese ocean color information accumulation and application.
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The 973 Program Grant of China under contract No.2009CB421202the Public Science and Technology Research Funds Projects of Ocean under contract No.200905012+1 种基金the National Natural Science Foundation of China under contract Nos 41271378 and 41271417863 Program of China under contract Nos 2007AA092201 and 2008AA09Z104
文摘Dissolved organic carbon(DOC)and particulate organic carbon(POC)are basic variables for the ocean carbon cycle.Knowledge of the distribution and inventory of these variables is important for a better estimation and understanding of the global carbon cycle.Owing to its considerable advantages in spatial and temporal coverage,remote sensing data provide estimates of DOC and POC inventories,which are able to give a synthetic view for the distribution and transportation of carbon pools.To estimate organic carbon inventories using remote sensing involves integration of the surface concentration and vertical profile models,and the development of these models is critical to the accuracy of estimates.Hence,the distribution and control factors of DOC and POC in the ocean first are briefly summarized,and then studies of DOC and POC inventories and flux estimations are reviewed,most of which are based on field data and few of which consider the vertical distributions of POC or DOC.There is some research on the estimation of POC inventory by remote sensing,mainly in the open ocean,in which three kinds of vertical profile models have been proposed:the uniform,exponential decay,and Gauss models.However,research on remote-sensing estimation of the DOC inventory remains lacking.A synthetic review of approaches used to estimate the organic carbon inventories is offered and the future development of methods is discussed for such estimates using remote sensing data in coastal waters.
文摘A new method for measuring ocean wave length and direction from SEASAT SyntheticAperture Radar (SAR)remote sensing image is presented in the paper. In the new method, an ocean waveimage is sampled in certain directions, the samples are then analyzed by using one dimensional FourierTransformation to calculate the ocean wave correlation function. Finally the ocean wave length and direc-tion are determined from the ocean wave correlation function. The new method is better than the tradition-al two-dimensional Fourier Transformation method in both consuming time and precision .
基金Supported by the High Technology Research and Development Programme of China （2001AA135091） and the National Natural Science Foundation of China （60375008）.
文摘This paper is divided into three parts.In the first part,it describes the major objects of o-cean monitoring and investigation by means of satellite remote sensing technology,including the observation of dynamic phenomena of ocean,ocean color and sea surface temperature as well as mapping of coastal zone and islands.In the second part,some research results of oceanic environment which were obtained in the past decade in China are presented.In the third part,some fundamental technologies are described,to which we should pay attention in order to make great contribution to marine environment by using satellite remote sensing technology in the coming few years in China.
基金The National "973" Program of China under contract No.2009CB723902the Key Projects of the Knowledge Innovation Program of Chinese Academy of Sciences under contract No.KZCX1-YW-14-2.
文摘Requirements for monitoring the coastal zone environment are first summarized.Then the application of hyperspectral remote sensing to coast environment investigation is introduced,such as the classification of coast beaches and bottom matter,target recognition,mine detection,oil spill identification and ocean color remote sensing.Finally,what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.
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,R rs( λ B)/ R rs(555). The best error statistics among the considered formulas were produced using the power function POC(mg/m 3)=262.173 [ R rs(443)/ R rs(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-toblue 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funded by the National Environmental Research Council, UK, through a PhD studentship at the Centre for observation of Air-Sea Interactions & fluXes (CASIX)the National Centre for Earth Observation and NERC Oceans 2025 programme (Themes 6 and 10)
文摘An important goal in ocean colour remote sensing is to accurately detect different phytoplank- ton groups with the potential uses including the validation of multi-phytoplankton carbon cycle models; synoptically monitoring the health of our oceans, and improving our understanding of the bio-geochemical interactions between phytoplankton and their environment. In this paper a new algorithm is developed for detecting three dominant phytoplankton size classes based on distinct differences in their optical signatures. The technique is validated against an independent cou- pled satellite reflectance and in situ pigment dataset and run on the 10-year NASA Sea viewing Wide Field of view Sensor (SeaWiFS) data series. Results indicate that on average 3.6% of the global oceanic surface layer is dominated by microplankton, 18.0% by nanoplankton and 78.4% by picoplankton. Results, however, are seen to vary depending on season and ocean basin.
基金The National Natural Science Fund of China under contact No.41276088the National Natural Science Fund for Young Scholars of China under contact Nos 41206002 and 41306010
文摘For the application of soil moisture and ocean salinity(SMOS)remotely sensed sea surface salinity(SSS)products,SMOS SSS global maps and error characteristics have been investigated based on quality control information.The results show that the errors of SMOS SSS products are distributed zonally,i.e.,relatively small in the tropical oceans,but much greater in the southern oceans in the Southern Hemisphere(negative bias)and along the southern,northern and some other oceanic margins(positive or negative bias).The physical elements responsible for these errors include wind,temperature,and coastal terrain and so on.Errors in the southern oceans are due to the bias in an SSS retrieval algorithm caused by the coexisting high wind speed and low temperature;errors along the oceanic margins are due to the bias in a brightness temperature(TB)reconstruction caused by the high contrast between L-band emissivities from ice or land and from ocean;in addition,some other systematic errors are due to the bias in TB observation caused by a radio frequency interference and a radiometer receivers drift,etc.The findings will contribute to the scientific correction and appropriate application of the SMOS SSS products.
文摘Traditional methods of extracting the ocean wave eddy information from remotely sensed imagery mainly use the edge detection technology such as Canny and Hough operators. However, due to the complexities of ocean eddies and image itself, it is sometimes difficult to successfully detect ocean eddies using these methods. A multifractal filtering technology is proposed for extraction of ocean eddies and demonstrated using NASA MODIS,SeaWiFS and NOAA satellite data set in the typical area, such as ocean west boundary current. Results showed that the new method has a superior performance over the traditional methods.
文摘Based on the in situ optical measurements in the Bohai Sea of China, which belongs to a typical case-2 water area, we studied the characteristics of DCM (deep chlorophyll maximum) such as its spatial distribution, vertical profile, etc. We found that when the depth of the chlorophyll maximum is comparatively small, even in turbid coastal water regions, there is always a good correlation between the concentrations of chlorophyll maximum and the satellite-received signals in blue-green spectral bands; the correlation is even better than that between the surface chlorophyll concentrations and the satellite-received signals. The strong correlation existing even in turbid coastal water regions indicates that an ocean color model to retrieve the concentration of DCM can be constructed for coastal waters if a comprehensive knowledge of the vertical distribution of chlorophyll concentration in the Bohai Sea of China is available.
文摘Remote sensing techniques have the potential to provide information on agricultural crops quantitstively,instantaneously and above all nondestrctively over large areas.Crop simulation models describe the relationship between physiological process in plants and environmental growing conditions.The integration between remote sensing data and crop growth simulation model is an important trent for yield estirmation and prediction,since remote sensing can provide information on the actual status of the agricultural crop.In this study,a new model(Rice-SRS) was developed based mainly on ORYZA1 model and modified to accept remote sensing data as input from different sources.The modelc an accept three kinds of NDVI,data.NOAA AVHRR(LAC)-NDVI,NOAA AVHRR(GAC)-NDVI and radiometric measurements-HDVI,The integration between NOAA AVHRR(LAC) data and simulation model as applied to Rice-SPS resulted in accurate estimates for rice yield in the Shaoxing area.reduced the estimating error to 1.027%,0.794% and (-0.787%) for early,single,and late season repectively.Utilizing NDVI data derived from NOAA AVHRR(GAC) as input in Rice-SRS can yield good estimation for rice yield with the average error (-7.43%) .Testing the new model for radiometric meassurements showed that the average estimation error for 10 varieties under early rice conditions was less than 1%.
基金Supported by projects of Institute of Geology,Chinese Academy of Geological Sciences(No.DD20160121)the National Key Research and Development Program of China(No.2020YFA0714103).
文摘The precision of Aster data is higher than that of Landsat series of multispectral remote sensing data,which can more accurately reveal the distribution of altered minerals.It plays an important role in prospecting,but it is rarely used in areas with complex terrain and high vegetation coverage.Based on this purpose,this study used Aster remote sensing data,and took Gongchangling iron deposit as a case study.It combined the mineral spectrum theory and the basic geologic data of the study area,using the model of principal component analysis(PCA)and color synthesis to extract abnormal altered minerals.The results show that the distribution of identified anomalies is basically consistent with the existing geological data in this study area,which provides a reliable reference for the mineral resources ex-ploration and delineation of mining areas.
文摘In this paper,technological progress for China's microwave remote sensing is intro-duced.New developments of the microwave remote sensing instruments for meteorological satellite FY-3,ocean dynamic measurement satellite(HY-2),environment small SAR satellite(HJ-1C) and China's lunar exploration satellite(Chang'E-1),geostationary orbit meteorological satellite FY-4M,are reported.
基金Supported by the Excellent Young Teachers Program of MOE, P. R. C(EYTP)
文摘The greatest advantage of remote sensing over conventional measurements lies in the opportunity to carry out detailed spatio-temporal analysis of land and ocean features on a very frequent basis. This paper analyses the contribution of satellite imagery to atmospheric, geophysical and ocean studies and management in West Africa since the early 1980s.The detailed application of data from optical sensors (e.g. Meteosat,NOAA/AVHRR, SPOT,L andsat TM, etc.) for weather prediction, hydrogeological, landuse/cover and cartographic studies has been acknowledged. However, the use of microwave (e.g. SAR) and optical data for ocean monitoring and studies in the sub-region is still very limited. Even though sufficient remote sensing expertise and infrastructure is perceived in the region, no clearly defined networking or database exists.
