Since the 1980s, a great attention has been paid to the advanced technique remote sensing in China, especially to development of satellite programs for marine environment. On September 7, 1988, China launched her first polar orbit satellite FY-1A for meteorological and oceanographic application (water color and temperature) and second satellite FY-1B two years later. In May 1999, China launched her second generation of environment satellite FY-1C with higher sensitivity, more channels and stable operation. The special ocean color satellite HY-1 has been in the orbit on May 15, 2002, whose main purpose is detection of marine environment of China Sea. HY-1 is a first Chinese ocean color satellite which was launched as a piggyback satellite on FY-1 satellite using Long March rocket. On the satellite there are two sensors, one is the Chinese Ocean Color and Temperature Scanner (COCTS), the other is CCD Coastal Zone Imager (CZI). The technique systems of ocean color remote sensing have been developed by Second Institute of Oceanography (SIO), State Oceanic Administration (SOA), in 1997 and by National Satellite Ocean Application Service (NSOAS) in 2002. Those systems include the functions of data receiving, processing, distribution, calibration, validation and application. SIO has capability to receive and process the FY-1 and AVHRR data since 1989. It is also a SeaWiFS scientific research station authorized by NASA, USA, to freely receive SeaWiFS data Since September 16, 1997. NSOAS has capability to receive and process the data of HY-1, AVHRR, MODIS and Geo satellite. In the recent years, some local algorithms of atmospheric correction and inversion of ocean color are developed for FY-1C , SeaWiFS and HY-1 to improve the accuracy of the measurement from satellites efficiently. The satellite data have being applied in monitoring marine environment, such as the spatial distribution of chlorophyll, primary products, suspended material, transparency and yellow substance, red tide detection and coastal current study.

China ocean satellite, HY-1, is the first one applied to ocean research and exploitation, which has two payloads. Multi-spectral CCD camera is one of two payloads. MS-CCD camera will be applied to seacoast dynamic observation and taking the messages of ocean color. The camera has four spectral band and can get images about 250 m GSD and 500 Km swath at the altitude of 798 Km. In this paper, we will introduce the main parameters of camera, such as, spectral band, resolution, dynamic range, SNR, MTF, registration accuracy and polarization.

RS (Remote Sensing), GIS (Geographic information System) and ES (Expert System) are used in many fields. They are powerful tools for obtaining, organizing, analyzing and displaying spatially referenced data, estimating resources, providing relevant information and so on. So their introduction to marine fisheries is essential to take sustainable development of marine fisheries in east China Sea into reality and improve marine fisheries management in China. Based on the marine fisheries information, using Geographic Information System and Expert System, we have established the Chinese Marine Fisheries Remote Sensing Information Service System. This system started in 1997. It extended the application of the advanced technology such as GIS, RS, ES to marine fisheries. In this paper, the recent works and improvement are introduced.

Remote sensing is an indispensable means for coastal band monitoring. Using satellite remote sensing data to monitor coastline variation and to analysis the eroding, depositing features and evolution process will be of great significance for the river mouth regulation, river course planning, coastal protective project program and trend prediction of coastal evolution. So, it is necessary to establish a coastline dynamic monitoring system. The system is mainly based on remote sensing and spatial information analysis techniques. In this paper, the system framework, design methodology and system functions are described in detail. The key techniques and methods involved in the system construction are particularly discussed, and they include the data preprocessing techniques, such as cloud identification and geometry fine correction, multi-scale coast edge extracting algorithm based on MRF model and coastline tide correction model with measured data or numerical simulation result as input, and coastline dynamic analysis method based on time series analysis and spatial topological analysis. Finally, an example to apply the system to the Yellow River mouth delta is given and the process flow diagram and procedures are described. The comparison of monitoring results with manually interpreted results has verified the favorable effect of the system.

A specially designed satellite receiving system for NOAA/AVHRR and FY-1C/MVISR started its operation in March 2002 at NPEC (Northwest Pacific Region Environmental Corporation Center, Toyama, Japan) envisaging the remote sensing application for marine pollution monitoring. While NOAA series and FY-1C/D are meteorological satellites and not marine pollution monitoring satellites, they are operational. By operating direct receiving system, we became privileged user like satellite owners and, in order to overview its feasibility, effectiveness or constraints, we implemented a conceptual analysis of overall space/ground system for satellite marine pollution monitoring.

SeaWiFS Data Analysis System (SeaDAS) provided by US NASA often fails on the atmospheric correction procedure in processing SeaWiFS data of the turbid coastal areas, case 2 waters, in China Sea. To overcome this problem, a new atmospheric correction algorithm has been developed in this study. In this algorithm, the radiance received by the satellite is decomposed into: Rayleigh scattering radiance, aerosol scattering radiance, sun glint radiance and water-leaving radiance. The values of radiance computed by this algorithm are compared with those computed by SeaDAS software as well as with in situ data. The results show that this algorithm is particularly effective and accurate for processing SeaWiFS data in China Sea.

A spectra-matching optimization algorithm, designed for hyperspectral sensors, has been implemented to process SeaWiFS-derived multi-spectral water-leaving radiance data. The algorithm has been tested over Southwest Florida coastal waters. The total spectral absorption and backscattering coefficients can be well partitioned with the inversion algorithm, resulting in RMS errors generally less than 5% in the modeled spectra. For extremely turbid waters that come from either river runoff or sediment resuspension, the RMS error is in the range of 5-15%. The bio-optical parameters derived in this optically complex environment agree well with those obtained in situ. Further, the ability to separate backscattering (a proxy for turbidity) from the satellite signal makes it possible to trace water movement patterns, as indicated by the total absorption imagery. The derived patterns agree with those from concurrent surface drifters. For waters where CDOM overwhelmingly dominates the optical signal, however, the procedure tends to regard CDOM as the sole source of absorption, implying the need for better atmospheric correction and for adjustment of some model coefficients for this particular region.

The atmospheric-correction of satellite ocean color data is fundamental for applications of the satellite data. The atmospheric-correction of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data is successful for open ocean waters, but fails for turbid coastal waters, when using the default algorithm of SeaWiFS Data Analyze System (SeaDAS), resulting in an over-correction of atmospheric effects. Based on the basic principle of atmospheric correction, a practical approach was developed for atmospheric correction of SeaWiFS imagery for turbid coastal waters. We took the assumption of spatial homogeneity of band7-band8 ratio of aerosol radiance and of water-leaving radiance over relatively small spatial scales (100-200 km), the two ratios were calculated from the processed results of SeaDAS standard atmospheric correction algorithm. The correction approach could reduce the errors of water-leaving radiance. In addition the water-leaving radiance in turbid water areas where the default SeaDAS algorithms added a mask for atmospheric correction failure could be retrieved. Then the results were compared with that of other atmospheric-correction method for turbid coastal waters.

It has been found that, at certain solar and sensor viewing geometries and for certain atmospheric conditions, some discontinuity lines appear in the retrieved atmospheric and ocean color products from measurements of Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Such discontinuity lines, which do not often happen in the SeaWiFS products, appear along lines with constant scattering angles between the solar and sensor viewing directions. The discontinuity lines are clearly not real. They are artifacts from the SeaWiFS atmospheric corrections. The atmospheric correction, which is the key data processing in the ocean color remote sensing, removes more than 90% of the sensor-measured signals that are contributed from atmosphere and ocean surface effects in the visible wavelengths. In this paper, a brief description of the SeaWiFS atmospheric correction algorithm, in particular, the technique that is used in retrieving the aerosol models and aerosol radiance contributions in the visible wavelengths, is provided. Results from some specific simulations that explain the causes of the discontinuity lines in the derived products are presented. We show that these discontinuities are results of the imperfect atmospheric correction due to some effects of the aerosol models that are used for the SeaWiFS data processing. A simple modification to the current atmospheric correction algorithm to correct such effects is proposed and tested with SeaWiFS data.

Satellite ocean-color algorithms generally use aerosol-mixture models to estimate and remove the atmospheric contribution to the measured signal. These models, based on aerosol samples, may or may not be realistic. In atmospheric correction, we are more interested in the optical behavior of the aerosols through the entire atmosphere. Comparisons of SeaWiFS-derived and measured aerosol optical thickness have revealed a systematic underestimation of the Angstrom coefficient, suggesting that the reference models may not be representative of actual conditions. To investigate the adequacy of the models and ultimately to improve atmospheric correction, we analyze atmospheric optics data collected by the AERONET project under a wide range of aerosol conditions at coastal and island sites. Using non-supervised classification techniques (self-organized mapping, hierarchical clustering), we determine the natural distribution of retreived aerosol properties of the total atmospheric column, i.e., the volume size distribution function and the refractive index, and more importantly identify clusters in this distribution. These clusters may be used as new aerosols mixtures in radiative transfer algorithms. We compare the clusters with the SeaWiFS reference models and, through application examples, conclude about their potential to improve atmospheric correction of satellite ocean color.

SeaWiFS observation of the East-Asian seas during the Aerosol Characterization Experiment-Asia shows large areas of under-estimated or even negative water-leaving radiance in the blue. To investigate it, three match-up stations were analyzed. An iterative radiative transfer simulation was carried out, in an attempt to reproduce the satellite measured top-of-atmosphere reflectance. The resulting water reflectance and aerosol optical thickness (AOT) agreed well with field measurements when the effect of sub-micron absorbing particles was considered in the simulation. The error in the retrieved water reflectance was much decreased, with average values of about 6% at 412nm and 443nm for the three stations. The effect of the Asian dust was also simulated in comparison with that of small absorptive aerosols. The under-estimation could not be solely attributed to Asian dust. It was also found that at one of the station, where the presence of dust aerosols was anticipated, an aerosol model mixed with both dust and soot improved the accuracy of the estimated AOT compared with the case of soot as the only absorptive aerosol. Sub-micron absorbing particles, in addition of the Asian dust, should be considered in the optical remote sensing of East-Asian waters.

The remote determination of the oceanic constituents in the upper ocean layer relies on the spectral information contained in the water leaving radiance. For waters of which the optical properties are mostly determined by phytoplankton and correlated degradation products ("case-I" waters), empirical or semi-empirical algorithms are successfully used to relate the water leaving radiance at two or more wavelengths to the chlorophyll concentration. These algorithms often fail in "case-II" waters where the water color is additionally influenced by sediments and non-autochtonous Colored Dissolved Organic Matter (CDOM). A promising method to derive chlorophyll concentration in case-II waters makes use of the sun-induced chlorophyll fluorescence (SICF) which is a feature specific to phytoplankton. The potential of the SICF for the space-borne retrieval of phytoplankton is reflected by the fact that several new satellite instruments (such as MERIS on ENVISAT) dispose of the required spectral channels to retrieve the SICF signal. In this article, we present an algorithm relating SICF to chlorophyll concentration in the topmost water layer. The algorithm has been derived from measurements gathered at more than 400 stations in different European waters and been applied to airborne imaging spectrometer data of European river plumes. Comparison with concurrent in situ measurements indicates that chlorophyll can be derived with a factor two error margin for the observed case-II waters. Recently, the algorithm was applied to one of the first available MERIS images and the retrieved chlorophyll concentration compared to results obtained from SeaWiFS data using the standard OC4v4 retrieval scheme.

After the successful launch of the Medium Resolution Imaging Spectrometer (MERIS) on board of the European Space Agency (ESA) Environmental Satellite (ENVISAT) on March 1st 2002, first MERIS data are available for validation purposes. The primary goal of the MERIS mission is to measure the color of the sea with respect to oceanic biology and marine water quality. We present an atmospheric correction algorithm for case-I waters based on the inverse modeling of radiative transfer calculations by artificial neural networks. The proposed correction scheme accounts for multiple scattering and high concentrations of absorbing aerosols (e.g. desert dust). Above case-I waters, the measured near infrared path radiance at Top-Of-Atmosphere (TOA) is assumed to originate from atmospheric processes only and is used to determine the aerosol properties with the help of an additional classification test in the visible spectral region. A synthetic data set is generated from radiative transfer simulations and is subsequently used to train different Multi-Layer-Perceptrons (MLP). The atmospheric correction scheme consists of two steps. First a set of MLPs is used to derive the aerosol optical thickness (AOT) and the aerosol type for each pixel. Second these quantities are fed into a further MLP trained with simulated data for various chlorophyll concentrations to perform the radiative transfer inversion and to obtain the water-leaving radiance. In this work we apply the inversion algorithm to a MERIS Level 1b data track covering the Indian Ocean along the west coast of Madagascar.

After correction of molecular scattering satellite radiance in the visible and near infrared may be linearly combined to retrieve surface chlorophyll abundance directly without explicit correction of aerosol scattering and absorption. The coefficients minimize the perturbing effects, which are modeled by a polynomial, and do not depend on geometry. The technique is developed for Global Imager (GLI) spectral bands centered at 443, 565, 667, and 866 nm, but is applicable to other sets of spectral bands. A wide range of geophysical and angular conditions is considered. Using a polynomial with exponents -2, -1, and 0 to determine the coefficients, the residual influence of the atmosphere on the linear combination is small compared with the corrected satellite radiance, generally within ±0.001, except at large view and sun angles, where it may reach 0.005 in magnitude. The resulting root mean squared (rms) error on chlorophyll abundance is 8.4%. Application of the method to GLI simulated imagery shows that estimated and actual chlorophyll abundance are in agreement, with an average rms difference of 32.1% and an average bias of -2.2% (slightly lower estimated values). The advantage of the method resides in its simplicity and rapidity of execution. Knowledge of aerosol amount and type is avoided. There is no need for look-up tables of aerosol optical properties. However, accuracy depends on the bio-optical model selected to relate the linear combination to chlorophyll abundance, which may vary depending on water type or biological province.

Apply a newly developed ocean-color inversion algorithm to measurements made in the west Florida Shelf and off the California coast, we derived the particle backscattering coefficient and the total absorption coefficient. From the derived total absorption coefficient, we calculated the absorption coefficients of the phytoplankton pigments and that of the gelbstoff (Colored Dissolved Organic Matter). From the derived pigment absorption coefficients, we further calculated the chlorophyll-a concentrations. These derived values were compared with those measured from water samples. It is found that the derived values are very consistent with those measured ones, suggesting that the inversio nmethods work very well for these coastal waters, and can be applied to satellite data for wide observations.

Scientists suggested that satellite remote sensing represent the most suitable technique for synoptic monitoring the change and extent of polluted water after late 80s. They try to establish the relationship of remote sensing parameters and oceanic components which are without optical activity. This technique permitted employ satellite-based data to estimate of regional and global phytoplankton primary production and provided a possible means for monitoring the spatial and seasonal variations of near-surface distribution of nutrient in water. Dugdale et al (1989) determined linkage between SST and nitrate in sea water of upwelling area: SST = F (NO₃), consequently the concentration and distribution of nitrate can be retrieved from the SST image. Robinson (1989) suggested that CDOM have direct relationship with polluted component in water as dissolved organism, so CDOM can be used as tracer in the mixing process of estuary water. Pattiaratchi et al (1994) determined the concentration of chl-a and the relationship betweeh chl-a and nutrient, further retrieved the distribution of nutrient. Arnone at al (2000) succeeded in establishing salinity distribution image from SeaWiFS image through acquiring the relationship between CDOM and salinity. Chen Zhiqiang (2000) found out strong positive correlation between CDOM and nitrate and slilicate, succeeded in retreiving nutrient distribution inverse model in Zhujiang River Estuary from CDOM image.

An algorithm was developed based on reflectance model of inherent properties of seawater. A digital camera was used to capture digital images of river estuaries of Prai, Muda, and Merbok from a low altitude flying light aircraft. Water samples were collected simultaneously with the airborne image acquisition and later analyzed in the laboratory. Vertical images were captured through a special hole at the floor of the aircraft. Atmospheric correction for multidate images was performed by selecting average digital number of grass as a reference. The digital colour images of the study areas were separated into three bands (red, green and blue) for multi-spectral analysis. The digital numbers for each band corresponding to the sea-truth locations were extracted and used to calibrate the algorithm. The calibrated total suspended solids (TSS) algorithm was then used to generate the water quality maps of the study areas. This study indicates that a digital camera can be a useful tool for airborne remote sensing. The newly developed algorithm can estimate TSS concentration with linear correlation coefficient square (R²) of 0.94.

The purpose of data merger activities undertaken by the National Aeronautic and Space Administration's (NASA) Sensor Intercomparison and Merger for Biological and Interdisciplinary Studies (SIMBIOS) Project is to create scientific quality ocean color data encompassing measurements from multiple satellite missions. The fusion of data from multiple satellites will improve the quality of ocean color products over single-mission data sets by expanding spatial and temporal coverage of the world's oceans and increasing statistical confidence in generated parameters. The merger will also support a variety of new applications by taking advantage of sensor-varying calibration, spectral, spatial, temporal, and ground coverage characteristics. Leading to the data merger goals, the SIMBIOS Project has established a thorough ocean color validation program and has been cross-comparing and cross-calibrating sensor data with in situ measurements and data among the missions. The SIMBIOS Science Team has been studying data merger algorithms based on spectral data assimilation and spatial interpolation. The SIMBIOS Project Office has implemented statistical objective analysis and regression techniques based on artificial neural networks and support vector machines. The accuracy of the merger methods will be evaluated using in situ data, statistical analyses, and simple chlorophyll means -- the method already implemented within the SIMBIOS Project. This paper defines challenges and suggests solutions for data merger based on the example of daily chlorophyll concentration products from Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS).

With rapid development of GIS techniques, GIS techniques have come into applied period in the field of natural science and other application fields. Because of complex marine structure with many dynamic changes, tight relationship among factors in body of water, fuzzy boundary and unintuitive structure character, it is especially difficult to apply GIS to the field of ocean science. Beginning with the ocean current GIS analysis, this paper tries to develop GIS application study of oceanography. It is evident that the first problem needing to be solved is GIS expression of current field. Therefore, main information types of ocean current data that many physical oceanography scientists are using are collected. Firstly, five expression of current field commonly used in physical oceanography are: section vector expression of average current speed, component expression of current field in large area, time series expression of fixed point and expression of current path. The main work of this paper is to give corresponding GIS expression respectively according to the above expressions of ocean current. Based on the above work, corresponding GIS operational cases are given to further prove the feasibility of GIS expressions of current field. Finally, the conclusions and further work are suggested.

The paper analyzes the generated mechanism of the reset noise when reading out the CCD video signal. I also states a sampling technique for CCD output video signal, the Correlative Double Sampling (CDS) technique, which is on the basis of noises canceled-each-other and the mathematics correlative theory. The paper introduces the oepration principle of the CDS technique and its filtering effects on the output noise of CCD (which includes the reset noise of CCD, the coupled cross-talk noise between the horizontal clock drive and the ground-wire of power supply, the white noise of output amplifier and the reset noise of 1/f noise). The paper gives an electric circuit of CDS that is applied practically. At last, it verified the conclusion that the output S/N of CCD signal can attain to 48 dB.

SeaDAS proposes the water leaving radiance as a level 2 product for the SeaWiFS sensor. This radiance results from the Gordon & Wang atmospheric correction scheme, applied on the measured Top Of Atmosphere radiance. We have access to ground-based measurements acquired by the CIMEL instrument at the SeaWiFS time overpass in different locations over European coastal waters. An in-house software package has been developed in order to derive from the CIMEL data the required inputs (optical thickness and phase function) to a radiative transfer code (RTC). Computations allow to retrieve the SeaWiFS water leaving radiances with the “actual” atmospheric optical properties. An extended comparison between these values and those proposed by SeaDAS is conducted.

The Pearl River system is mainly located in the Guangdong Province in southern China, with the length of 2214 km and total area of 453,690 km². The Pearl River estuary is the largest estuary in the South China Sea (SCS), with a mean annual discharge of 326 billion m³, of which are about 30 million tons of dissolved matters annually discharged into the estuary. The high concentration of suspended sediments and dissolved matters makes the optical properties of the coastal waters very complex. The spectral absorption coefficient of yellow substance [A_y(λ)] is one of the inherent optical properties that influence the reflectance (or water-leaving radiance) of the water body. It is essential to measure A_y(λ) and to quantify its contributions to the total absorption of the water body. In this study, the Gelbstoff Optical Analyse Laboratory System (GOALS), with spectral range from 200 to 850 nm and with spectral resolution of 0.37 nm per pixel, was used to measure A_y(λ) in the Pearl River estuary and in the adjacent coastal waters in July 2002. A_y(400) was around 1.5 m^-1 near the river mouth (zero salinity). It decreases with increasing salinity following an apparent non-linear mixing line. There is no apparent relationship between A_y(400) and dissolved organic carbon (DOC) concentration, indicating that the estuary is a complex, non-point source environment. This presents a great challenge to remote sensing study in this area.

A shipboard ocean optical profiling system (SOOPS) has been developed to meet the needs of ocean color remote sensing. This system is an integrated one that provide measurements of optical properies of seawater. Specifications of SOOPS are described. Shading errors are modeled by Monte Carlo simulation, the field experimental data and some optical properties derived from these data are described and analyzed. Also presented in this paper is an optical buoy system underdeveloped, which can provide time series observations of both inherent optical properties and apparent optical properties of sea water. This system consistents of two buoys, master buoy and slave bouy. Several optical instruments are mouted on the buoys or on the mooring cable of the buoys to provide optical measurements at depths up to 70m. Self shading of the buoy has been simulated via Monte Carlo method. Effective anti-biofouling techniques are used for protecting biofouling on the optical window. Bluetooth radio is used for the communication between the master buoy and the slave buoy. An Inmarsat satellite telemetry system is used to transmit data daily. These optical systems are useful for both verification of ocean color satellite data and understanding the time changes of physical, biological and optical parameters.

Bering Sea green belt is characterized by high productive region, with interactions of cyclonic and anti-cyclonic eddies. To study temporal and spatial variability of phytoplankton, we deployed two bio-optical drifters in a clockwise eddy in 2001 and 2002. The drifters were equipped with a spectroradiometer to measure upwelling radiance as same as Sea Wide Field-of-view Sensor (SeaWiFS) wavelength. SeaWiFS images were employed to monitor the spatial pattern of chlorophyll-a (chl-a). The drifter also measured sea surface temperature (SST). We compared SST with TOPEX/POSEIDON sea surface anomaly data and analyzed time and scale correlation of SST and phytoplankton distribution in some eddies. In 2001, a clockwise eddy trapped the drifter for 10 days. It represented relatively high chl-a concentration (about 1.0 mg m^-3) and low SST (about 8.5°C). After that it drifted to the Bering Sea slope current region along the shelf edge, and observed among 20 days. In 2002 we deployed a drifter in center of clockwise eddy, it was staying in this eddy for 14 days. There represented relatively low chl-a concentration (about 0.4 mg m^-3) and high SST (about 9.5°C). After that it drifted along Bering slope current similarly. The phytoplankton distribution was deferent from two years in spite of same kind of anti-cyclonic eddy. These deferent might be depending on deference of eddy's life stage.

This paper analyses the relation between data measured in situ and the NDVI derived from AVHRR of NOAA-14 during algal bloom in the Bohai sea in 1998 to establish surface biomass model of Ceratium furca(EHr.). This model is easy to utilize data received from multi-source satellite in operation, and gets directly the index of phytoplankton biomass. The area and distribution of high biomass is also presented. Based on this model, propagation speed of phytoplankton reveals progress of algal bloom development. The result of this model can discriminate algal bloom water from silt or suspended particle material (SPM).

SeaWiFS SeaWiFS Chl and AVHRR SST time-series in August, 1998 were used to evaluate short-term variability of Chl associated with upwelling events in the western Taiwan Strait. Extents of eutrophic waters (SeaWiFS Chlorophyll > 1mg/m³) and extents of colder than non-upwelling waters were calculated for the western strait and for the north and south portions, respectively. High extents of eutrophic waters were always accompanied by high extents of colder than nonupwelling waters, indicative of tight coupling of Chl with SST evolution and thus with upwelling activities. Only one-day lag of phytoplankton growth to upwelling was detected. The temporal patterns of upwelling events were found different in the northwestern and southwestern Taiwan Strait. In the north portion, a short relaxation of upwelling probably occurred between early and mid-August. One unique strong upwelling event was likely going from early through mid-August, peaking before Aug. 13^th in the south portion. It resulted in chlorophyll enhancement developing and reaching peaks not concurrently in these two upwelling zones. The duration of one upwelling event in the western Taiwan Strait in August was estimated to be ca. 12 days. Two distinctive upwelling systems located in the northwestern and southwestern Taiwan Strait were further inferred.

Satellite remote sensing technique has been used to detect and monitor red tide events in China since 1990s. In this paper we present the algorithms developed for extracting information about red tide events from NOAA AVHRR and Seastar SeaWiFS sensors. These algorithms include the multi-band ratio algorithms based on the spectral characteristics of the coastal waters, the ocean color-temperature algorithm that depends on the reflectance and temperature of the red tide waters, and the neural network model that employs the neural networks. The applications of the satellite remote sensing technique are given to the information extraction of the time (start and duration), the location and the spatial extent of the red tide events for red tide management and mitigation. Some examples are presented.

High resolution SeaWiFS data was used to detect a red tide event occurred in the Ariake Sound, Japan, in winter of 2000 to 2001. The area is small embayment surrounding by tidal flat, and it is known as one of the most productive areas in coast of Japan. The red tide event damaged to seaweed (Nori) culture, and the relation to the reclamation at the Isahaya Bay in the Sound has been discussed. SeaWiFS chlorophyll data showed the red tide started early December 2000, from the Isahaya Bay, although direct relationship to the reclamation was not clear. The red tide persisted to the end of February. Monthly average of SeaWiFS data from May 1998 to December 2001 indicated that the chlorophyll increased twice a year, early summer and fall after the rain. The red tide event was part of the fall bloom which started later and continued longer than other years. Ocean color is useful to detect the red tide; however, it is required to improve the algorithms to accurately estimate chlorophyll in high turbid water and to discriminate toxic flagellates.

Since 1998 unusual algal blooms of different toxic Raphidophyte species have been observed during April and beginning of May in the northeastern part of the North Sea including the Skagerrak as well as in the Kattegatt region. The algal blooms of Raphidophytes took place after the spring bloom, which normally occurs in this area during March, but before the anually reoccurring bloom of Phaeocystis, which usually is observed during May, when water temperatures exceed 15°C. The Raphidophyte blooms were mainly represented by two different Chattonella species and by Heterosigma akashiwo. The toxic algal blooms which have been identified in 1998, 2000 and 2001 can appear with maximum cell numbers of 24 mill. Cells/l (Backe-Hansen, 1999) and Chlorophyll values up to 80 μg/l. Satellite images of MOS and SeaWiFs show the beginning of the blooms west of Jutland (Denmark) and apparently were advected with the Jutland current towards the northeast. Later, the Raphidophyte blooms were observed along the Swedish and Norwegian west coast and extended along the Norwegian south coast up to 6°East, following the extensions of the Baltic current. The causative species of blooms, Chattonella sp., has shown strong phototactic behavior. In addition to 19'-butanoyloxyfucoxanthin, the Chattonella sp. contains three kind of carotenoids which other species do not have. Thus, the observations from microscopy and pigment profile from HPLC suggest that this species in the German Bight should be considered as a new HAB species. The reoccurrence of Chattonella blooms may indicate the response of algae to some kind of environmental change in the North Sea. Determination of the extend and the advection of toxic microalgae blooms as well as predictions through satellite remote sensing in the coastal areas of Denmark, Sweden and southern Norway, is also of great economic importance for the extensive mariculture ventures in this region, which repeatedly have suffered from the effects of toxic algal blooms.

The fine spectra data of red tide can be obtained by airborne hyperspectral red tide monitor. The identification of dominant species of red tide organism by airborne hyperspectral is of great significance for the red tide monitoring. By making spectral angle analysis and calculating the angle between reflectance of hyperspectral image pixel and that of reference spectra, the similarity of spectra of dominant species to be identified to reference spectra can be determined, and the species of red tide organism whose spectrum makes a smallest angle with the spectra of hyperspectral image pixel is chosen as dominant one. Reference spectra was measured from the red tide water body during two mesocosm ecosystem experiments and its surrounding water body in August 2002, and the spectra to be identified is the hyperspectral data collected from Bayuquan water body in the Liaodong Bay. By means of spectral angle analysis, red mesodinium rubrum is identified as the dominant species in the red tide on August 25, 2001, which is verified by the synchronous measured data at sea. It is shown from the study results that the airborne hyperspectral approach to identify the dominant species of red tide is feasible, and will offer valuable service for red tide monitoring.

Mesocosm ecosystem experiment with seawater enclosed of the red tide was carried out from July to September 2001. We got four species of biology whose quantities of bion are dominant in the red tide. During the whole process from the beginning to their dying out for every specie, in situ spectral measurements were carried out. After data processing, characteristic spectra of red tide of different dominant species are got. Via comparison and analysis of characteristics of different spectra, we find that in the band region between 685 and 735 nanometers, spectral characteristics of red tide is apparently different from that of normal water. Compared to spectra of normal water, spectra of red tide have a strong reflectance peak in the above band region. As to spectra of red tide dominated by different species, the situations of reflectance peaks are also different: the second peak of Mesodinium rubrum spectrum lies between 726~732 nm, which is more than 21nm away from the other dominant species spectra’s; Leptocylindrus danicus’s second spectral peak covers 686~694nm; that of Skeletonema costatum lies between 691~693 nm. Chattonella marina’s second spectral peak lies about 703~705 nm. Thus we can try to determine whether red tide has occurred according to its spectral data. In order to monitor the event of red tide and identify the dominant species by the application of the technology of hyperspectral remote sensing, acquiring spectral data of different dominant species of red tide as much as possible becomes a basic work to be achieved for spectral matching, information extraction and so on based on hyperspectral data.

The red tide spectrum database is the basis and prerequisite for red tide hyperspectral remote sensing, a technical support for the field investigation on red tide and the main technical measure for red tide data management and application. The data in the database mentioned in this paper come mainly from the red tide mesocosm experiment, and include the simultaneously collected biological, chemical, hydrographic and meteorological data besides the spectrum data of red tide dominant species. The database has not only the conventional functions for data query, retrieval and plotting, but also the algorithmic functions for the ground object spectrum data processing in the Visual FoxPro system environment and the biological information extraction using the ground object spectrum data. This system is not only an effective application system for detecting the red tide organism, identifying the red tide dominant species and analyzing the characteristic amount of red tide organism, but also a powerful tool for the marine environmental protection and the red tide disaster reduction in the future.

The Mascarene Plateau of the southwest Indian Ocean is studied for its primary production. The study is also aimed at demonstrating the feasibility of using remotely sensed satellite observation to characterize the chlorophyll 'a' distribution around the plateau and to depict any seasonal variation. The influence of other oceanographic parameters on primary production, like sea surface temperature and sea surface height anomaly are discussed. The sensors used are respectively, SeaWiFS, ATSR 2, and Topex/Poseidon during the period 1998 - 2000. The results show a seasonal variation with enhanced primary production occurring between the months of May and September. Although the Southern Indian Ocean is mainly oligotrophic, enhanced chlorophyll biomass around the Mascarene plateau was found with a maximum 0.3 mg/m³ during June 2000. The minimum production of around 0.1 mg/m³ was registered during March 1998. A general increase in primary production is observed from south to north and east to west of the Plateau with peaks corresponding to the shallow banks. The postulated explanation about a divergence zone on the western part of the Mascarene Plateau is substantiated by the detection of fronts, eddies and a 'relatively cooler sea surface temperature. Nutrients are thus upwelled closer to the euphotic zone enhancing primary production. The presence of a seasonal high-pressure center corresponding to the Southwest monsoon is shown and an analogy is drawn to a mini-monsoon where both the South Equatorial Current and the Southest Trade wind strengthened.

A primary productivity model for the turbid water is proposed using the remote sensing data. In previous studies, we proposed a time and depth resolved primary productivity model for a global scale, but results indicated significant errors on the East China Sea. A euphotic zone estimated in this model was based on a chlorophyll α concentration in the surface, which made errors on the turbid water. A photosynthetically available radiation and chlorophyll α concentration along the water column are defined as a function of the diffused attenuation coefficient and chlorophyll α concentration in the surface.

The feasibility of using digital camera imagery for estimating the concentration of total suspended sediments (TSS) in the Timah Tasoh reservoir was investigated. Digital images were captured from a low-altitude light aircraft. Three selected images were mosaiced to produce bigger image of the study area. Atmospheric corrections and mosaic sincronourization were performed by using the average digital number of grass in the images as a reference value. Water samples were collected simultaneously with the airborne image acquisition and later analyzed in the laboratory. The color mosaic image was separated into three bands assigned as red, green and blue bands and analysis separately. The digital numbers for each bands corresponding to the ground-truth locations were extracted and used for calibration of the water quality algorithm. A single band second order polynomial algorithm was used in this study due to limited ground-truth data. The calibrated algorithm was used to generate the water quality maps. The proposed algorithm can estimate TSS concentration with linear correlation coefficient square (R²) of 0.98.

The objective of this research is to explore a precise and fast way of water quality monitor. Water quality change in 1988 and 1996 are detected by remote sensing. One scene TM image in winter of 1996 was acquired and simultaneous in situ measurement, sampling and analysis were performed. Main methods include radiometric calibration of TM remote sensor, atmospheric correction to image data and model construction. The results indicate that satellite-based estimates and in situ measured water reflectance have very high correlation, and the root mean square difference between two kinds of indexes are close to 0.02-0.03 for each TM band in VI-NIR range. Quantity relationship between calibrated image data (average of 5x5 pixels) of TM bands and laboratory analyzed data of water samples indicated reflectance of TM band 1 to band 4 and organic pollution measurements such as TOC, BOD and COD had higher correlation. The same scene TM data in the same season of 1988 was processed in the same procedure. Results indicate water quality of most reservoirs has become worse. Water of eastern reservoirs near Dongjiang River is characterized with higher TOC and TSS, and water of western reservoirs is characterized with higher BOD and COD.

In this paper an artificial neural network (ANN) approach, which is based on flexible nonlinear models for a very broad class of transfer functions, is applied for multi-spectral data analysis and modeling of airborne laser fluorosensor in order to differentiate between classes of oil on water surface. We use three types of algorithm: Perceptron Network, Back-Propagation (B-P) Network and Self-Organizing feature Maps (SOM) Network. Using the data in form of 64-channel spectra as inputs, the ANN presents the analysis and estimation results of the oil type on the basis of the type of background materials as outputs. The ANN is trained and tested using sample data set to the network. The results of the above 3 types of network are compared in this paper. It is proved that the training has developed a network that not only fits the training data, but also fits real-world data that the network will process operationally. The ANN model would play a significant role in the ocean oil-spill identification in the future.

An experimental study in monitoring the hot wastewater which is discharged into sea by the Futtsu Power Plant on the east coast of Tokyo Bay, Japan, was carried out in August-September, 2001, by using airborne hyperspectral remote sensing (HRS) sensor OMIS (Operational Modular Imaging Spectrometer). The fundamental progress of experiment, features of OMIS HRS image, data progressing and information extraction technologies, and a primary but successful result are introduced in detail. A new algorithm to extract the features and the infection extension of hot wastewater is developed and suggested in this paper. The algorithm adequately uses the whole spectral range of OMIS according to the general spectral responding characters of water. The water in the whole area is extracted by its spectral features in VNIR at first and then the polluted water is picked out from it by combine-using the MIR and TIR information. As a result, a temperature distribution map is successfully achieved in a test area and some other abnormal points are popped out and therefore some other pollution sources are discovered successfully in the whole scopes. The relatively good results in this paper show that hyperspectral remote sensing technology has a great prospect in detecting ocean and coastal environment both in qualitatively and quantitatively, at least for the hot wastewater. And an OMIS system with the algorithm suggested in this paper is operational for monitoring the infection features of hot wastewater.

Theory of belt-oriented RADON transform is developed, and applied to extracting features from high-resolution remote sense images. By several typical experiments it is proved that belt-oriented Radon transform is powerful in extracting belt features, but Radon transform (line-oriented Radon transform called by author) is unavailable.

Based on the images processing of multi-temple remote sensing data of TM&ETM, different temporal remote sensing images were fused and the deposition and reclamation of the Congming dongtan were studied. Making use of the digitalized chart and erosion & deposition maps, the volume change of the North Branch of Yangtze river Estuary can be calculated, then the rate and amount of the riverbed accretion were obtained.

In this paper the authors analyzed the data collection of seabed terrain, the influence factors on measurement precision and the data computation in time or frequency domain. In order to estimate the noise embedded in the received data, the structure and algorithm of characteristic matching filter based on the entropy concept is developed and discussed in detail. It is shown that the noise data can be removed effectively and the high precision seabed terrain be simulated by the filtering method.

A possible mechanism to explain the correlation between submarine topography and the direct sunlight specially reflected from the sea surface with variable roughness caused by the bottom-current effect was suggested fifteen years ago by Henning et al. in International Journal of Remote Sensing, 9, 45-67, after comparing radar satellite image and Skylab satellite photograph of the North American east coast (Nantucket Shoals) with submarine relief features. A case study is carried out in the famous sand waves field located at the Taiwan banks of Taiwan Strait in August 1998. The TM images, either visible bands (TM1, TM2, TM3) or near infrared bands (TM4, TM5, TM7), shows submarine relief features for sand waves, with wavelength of 300 to 2000 meters, riding on the lager scale sand ridges and channel system. Sea truth data including 660 nm beam attenuation coefficient profiles were conducted in the same period. We compare signals of TM images, attenuation coefficient profiles, and sounding maps of the Taiwan Bands. The subsurface upwelling signals with contributions of the water column and the bottom, either estimated by single or quasi-single-scattering theory or revealed by the TM images after removing the contribution of direct sunlight reflected signals from sea surface, were too weak to distinguish the ridges and troughs of bedforms especially for red and near infrared bands. However, the direct sunlight specially reflected signals from the sea surface, approximately at same level in water-leaving reflectance not only for visible bands (TM1, TM2, TM3) but also for near infrared bands (TM4, TM5, TM7), was the major submarine bottom topography signals especially for those pixels towards the direction of the sun azimuth. Following a physical description for the lee waves appeared on free surface when the current flows round an underwater obstacle, the direct sunlight reflected signals related wave face slope, is dominated by the height and depth of sand waves and sand ridges, and current speed of the flows over those bedforms. The direct sunlight reflected signals from the sea surface could be regarded as a powerful tool to detect bedforms and other underwater obstacles.

The Hyperion instrument on-board the EO1 satellite is an imaging spectrometer capable of acquiring hyperspectral data with over 200 contiguous spectral bands of about 10 nm bandwidth. The instrument is not designed for ocean observation. Nevertheless, case 2 water near the coastal regions with high sediment loading usually has higher reflectance in the visible wavelength region than the clear case 1 water in the open oceans. Hence, the signal-to-noise ratio of Hyperion data over coastal waters may be sufficiently high, such that meaningful measurements of the optical properties of the coastal sea waters are possible. We tested the use of Hyperion imagery in retrieving and mapping the distributions of the coastal sea water optical parameters in the Singapore Strait. The Hyperion reflectance spectra were fitted to a coupled sea water reflectance and atmospheric transmission model. The water reflectance corrected for atmospheric effects could be computed from the fitting parameters. This method of inverse modeling by spectral fitting was able to separate the confounding effects due to scattering by suspended sediments and absorption by chlorophyll and dissolved organic matter. Spatial distributions of these three main constituents of coastal waters could be obtained.

Hyperspectral Remote Sensing has the potential to be used as an effective coral monitoring system from space. The problems to be addressed in hyperspectral imagery of coastal waters are related to the medium, clutter, and the object to be detected. In coastal waters the variability due to the interaction between the coast and the sea can bring significant disparity in the optical properties of the water column and the sea bottom. In terms of the medium, there is high scattering and absorption. Related to clutter we have the ocean floor, dissolved salt and gases, and dissolved organic matter. The object to be detected, in this case the coral reefs, has a weak signal, with temporal and spatial variation. In real scenarios the absorption and backscattering coefficients have spatial variation due to different sources of variability (river discharge, different depths of shallow waters, water currents) and temporal fluctuations. The retrieval of information about an object beneath some medium with high scattering and absorption properties requires the development of mathematical models and processing tools in the area of inversion, image reconstruction and detection. This paper presents the development of algorithms for retrieving information and its application to the recognition and classification of coral reefs under water with particles that provide high absorption and scattering. The data was gathered using a high resolution imaging spectrometer (hyperspectral) sensor. A mathematical model that simplifies the radiative transfer equation was used to quantify the interaction between the object of interest, the medium and the sensor. Tikhonov method of regularization was used in the inversion process to estimate the bottom albedo, ρ, of the ocean floor using a priori information. The a priori information is in the form of measured spectral signatures of objects of interest, such as sand, corals, and sea grass.

An automatic procedure has been developed for detection of sea surface fronts on satellite images based on the nature of sea surface fronts. The procedure includes the edge detection, edge tracking and the determination and presentation of sea surface fronts. Examples of detection of the sea surface fronts on synthetic aperture radar images by the procedure are illustrated. The results of the sea surface front detection have been compared with the visual interpretation. It is shown that the procedure works well.

The Tonkin Gulf is a semi-enclosed bay in the South China Sea with a shallow shelf. Historic observations indicate that the coastal and outer water masses converge here, which results in a complex hydrographic situation. The thermal front in ocean is a good indicator for connection between different water masses and acts as an important topic in the oceanography. Here the 8-year (1991 - 1998) Pathfinder sea surface temperature (SST) data have been applied to investigate the seasonal and interannual variability of the thermal front in the Tonkin Gulf. This paper tries a new methodology to describe the gradient of temperature using a pairs of orthogonal vector components. When the variability of the thermal fronts in the Tonkin Gulf is concerned, the signs of SST's anomalies (SSTA), the deviations of surface wind and surface heat fluxes are individually accounted for criterions of the causes. In the research domain, the order that the thermal frontal intensity varies with seasons from strongest to weakest is spring, then summer, winter and fall. There is a significant relationship between the frontal intesity and SSTA, which indicates a trend that when SSTA is negative, the fronts are strong, and the absolute value of SSTA shows a positive correlation with the frontal intensity. In winter, when abnormal northerly appears over the bay the front is stronger, whereas the front is weaker when anbnormal southerly occurs.

A methodology for using Landsat data to map sea surface temperature (SST) in a small coastal embayment is explored in this paper. Following a convective cooling event at Jervis Bay, New South Wales, Australia synoptic observations of SST were made at 31 stations across the bay. These observations were used to derive a linear regression model, which compared the observations of SST to pixel values measured by Landsat 5 Band 6. The Landsat image was captured simultaneously with the SST observations. The regression equation was then used to calibrate the digital numbers of the image to degrees Celsius. Comparisons were made between the calibrated image values of SST and those simulated by an existing three-dimensional hydrodynamic model of the bay. SST in the bay ranged from 14.4°C to 17.7°C and the corresponding digital numbers of Landsat Band 6 ranged from 111 to 116. The regression equation derived was T = 0.53DN - 44.2. A comparison of the calibrated image against the numerically simulated SST indicated that the method was adequate for mapping the gross distribution of temperature across the bay. It ws found, however, that the regression model provided a resolution of only 0.5°C. Accordingly, the calibrated image failed to show a small cold water mass in the northern shallow regions of the bay, which was critical in generating the bay circulation in response to the convective cooling.

The article is devoted to exploring the synthetic aperture radar (SAR) imaging theory of the ocean waves. Due to the orbital motion of the water particles associated with the long ocean surface waves the image formation called the velocity bunching mechanism, is mainly concerned. Buoy data measured by the National Data Buoy Center (NDBC), US, for wave height spectra is also obtained. The measured wave height spectra are applied in the imaging models. The linear and quasi-linear imaging models for simulating SAR image spectra of ocean waves are explored. The validation of the quasi-linear model is strongly dominated by the range/velocity ratio R/V. However, R/V is weak to the linear model. Besides, the velocity bunching MTF is well implemented by the quasi-linear model.

Synthetic Aperture Radar is a most useful instrument for internal wave observation. The northern of South China Sea (SCS) is one of interested sea areas to researchers, and the large amplitude and long-crested internal solitary waves in this area are often encountered in SAR images. The waves are generated by the interaction between the tidal current and shallow bottom topography in the Luzon Strait. The spatio-temporal distribution of internal solitary waves in the northern of SCS is studied by analyzing the ERS SAR images from 1995 to 2001. In the South China Sea internal wave occurs frequently from May to August, and infrequently from November to next March. The frequent occurring area of internal wave is located in north of coral reef Dongsha. Using an ERS-2 SAR image the amplitudes of internal waves in Xijiang oil field in Northern of South China Sea are estimated by one-dimensional model with good result compared with data in situ.

The amplitude of internal waves is very difficult to retrieve from satellite. In this paper, a method is given to estimate the amplitude of nonlinear internal waves from synthetic aperture radar (SAR) imagery. It is assumed that the observed groups of nonlinear internal wave packets on SAR imagery are generated by local semidiurnal tides. The mean distance between the leading crest of two successive wave packets has been used to derive the group velocity of the nonlinear internal waves. The amplitude of nonlinear internal waves has been calculated from a model which consists of the KdV equation, action balance equation and Bragg scattering model. Case studies in China Seas show reasonable results.

The problem of electromagnetic wave scattering from randomly rough surfaces has been studied using both low- and high-frequency approximations. It has been recognized that scattering at small incident angles seemed to follow the high-frequency solution based on the Kirchhoff approximation (KA), and at large incident angles the small perturbation method (SPM) appears to explain the measurements better. However, for very rough surfaces with large rms height and rms slopes around unity or more, both of them failed to give satisfactory results. In this paper the integral equation model (IEM) is introduced to solve the electromagnetic scattering from very rough surfaces. It can be shown that the IEM not only can describe the single scattering but can interpret the multiple scattering well. In addition, the upward and downward multiple scattered wave are identified when taking multiple scattering into consideration, therefore it is possible to assign the correct shadowing effect to multiple scattering calculation. By numerical calculation the phenomenon of backscattering enhancement can be observed and the results are in good agreement with experimental data.

The marine microwave remote sensing is based on the interaction between the EM wave and the small-scale wave with a wavelength comparable to that of the EM wave, so the most important in-situ work must be done to measure the structure of small-scale wave. The optical instrument for detecting microstructure of sea surface wave is used to obtain the pattern of fine scale wave, and a series of algorithm is developed to calculate the high frequency wave spectrum from the image data. The color-encoding method is used to measure the 2-D structure of water surface. The apparatus consists of 4 parts: the light source, a color-encoding plate, the Fresnel Lens, and 3CCD camera. The color-encoding plate is designed on the basis of the HSI Encoding method. The actual image size measured by the instrument is about 0.4 x 0.3m. The image’s sampling rate is 20Hz; the spatial resolution is 1mm with a dynamic slope range of ±45°. The system was successfully deployed in the water tank. The image processing is discussed to introduce how to get the wave number spectrum can be got from the original color slope image. The algorithm will provide a good opportunity for us to solve some problems in marine remote-sensing mechanism and oceanic dynamics.

During 1998 - 2000, sea surface height anomalies (SSHA) calculated from TOPEX/POSEIDON Merged Geophysical Data Record and The TOPEX/ERS2 SSHA maps (extracted from CCAR web site, http://ccar.colorado.edu/~realtime/bering/) were analyzed to understand the mesoscale eddy field along and across the shelf edge in the southeastern Bering Sea. The trace of the mesoscale eddy using SSHA maps showed the number and the occurrence of the mesoscale eddy. In 1998 to 1999, the number of the mesoscale eddy was low (244 ~ 256) and positive SSHA was prominent along the shelf edge. Especially, the eddy kinetic energy along the shelf edge was quite low inthe summer of 1999. In 2000 and 2001, however, the number of the mesoscale eddy relatively high (312 ~ 324) and the eddy kinetic energy was high in summer. TOPEX/POSEIDON SSHA ground track D-79 implies the change of the variability and the velocity of the positive SSHA field meaning anticyclonic eddy field along the shelf edge from 2000. These results indicate that the variability of the Bering Slope Current flux resulted in the occurrence of the mesoscale eddy field that has an influence on nutrient supply following high chlorophyll α distribution into the euphotic zone along the shelf edge. Mesoscale eddy field in the oceanic region migrated offshore or remained near the shelf break, not moved onto the shelf. A drifting buoy tracking Bering Sea eddies, however, observed the onshelf flow, in 2000. Results indicate that the horizontal mixing of mesoscale eddies along the shelf edge will play an important role in the Shelf-Slope exchange.

A new set of two optical spectral probes developed to measue content of organic and inorganic constituencies suspended and dissolved in natural water is proposed. The set is capable to measure spectral attenuation and absorption coefficients of light, total amounts of organic and terrigenic hydrosoles suspended in water, and amount of organic matter dissolved in natural water. It can be used to monitor water quality and measure optically active ingredients in oceans, lakes and other natural water basins.

This paper presents the methodological approach of the oil spill monitoring system that is being put into operation by the National Petroleum Agency (NPA) in Brazil. The methodology is based on integrated analysis of multi-sensor data which includes satellites products, such as, GOES and AVHRR Sea Surface Temperature (SST), SeaWiFs chlorophyll concentration, QuikScat near sea surface wind field, GOES and AVHRR convective rain areas, and Synthetic Aperture RADAR (SAR) data from RADARSAT-1 satellite. The methodology is implemented by means of a system composed by four subsystems called, data reception (SAR, GOES, NOAA and QuikScat), Integrator, hydrodynamic model and database. The methodology was applied to the accidental oil spill caused by PETROBRAS oil rig P-36. A RADARSAT-1 image was acquired during accident period at 21:07 (GMT) on 22nd of March 2001 and used. The results are presented and discussed.

This work provides a practical method of atmospheric correction for turbid coastal and inland waters where the negative water-leaving radiance occurs. The present method use the property that normalized water-leaving radiance at 412 nm is increase very little with the increasing of turbidity. Thus, in very turbid coastal and inland water, we can use Rayleigh-corrected reflectance at 412 nm to estimate the aerosol scattering reflectance at 865 nm. The performance of the new algorithm is tested with simulation for several cases. It is found that the retrieved remote sensing reflectance is usually in error by <10% for the first six bands of SeaWiFS. This new algorithm is also tested under various atmospheric conditions over the mouth of Changjiang river and Hangzhou bay where the sediment concentration is very high and the standard SeaWiFS atmospheric correction algorithm creates a mask due to atmospheric correction failure. The result proved the efficiency of this simple method in reducing the errors of the water-leaving radiance.

Ruddick et al. Applied Optics, 39, 897-912 (2000), have extended the standard SeaWiFS atmospheric correction algorithm for use over turbid coastal and inland waters; however, their assumption of a spatially homogeneous constant ratio for the water-leaving reflectances normalized by the sun-sea atmospheric transmittance at 765 and 865 nm, under the simple b_b/α model, can result in a significant inaccuracy for highly turbid water. Using the more accurate b_b/(α+b_b) model, which, more realistically, does not assume spatial homogeneity ratio, the calculated corresponding perturbation for this assumption is several times larger than what Ruddick et al. evaluated under b_b/α model. Such perturbation-related error could exceed 10% in highly turbid water with R⁽⁸⁾ > 0.05. We suggest using the modified assumption, 1/R⁽⁸⁾=α₀/R⁽⁷⁾ +(1-α₀)/f; instead of Ruddick's assumption, in SeaWiFS atmospheric correction algorithms for turbid waters. The Maclaurin seriers expansion of such modified assumption is expressed as, R⁽⁸⁾=α₀)^-1[R⁽⁷⁾+(α₀-1)α₀^-1f¹R⁽⁷⁾²+(α₀-1)²α₀^-2f²R⁽⁷⁾³+.....]; -1<(α₀-1)α₀^-1f¹R^(7)&lt;1 Calibration of α₀, an IOPs related regional parameters, is determined on an image-by-image basis from regressive empirical relationship of scatterplot of the-Rayleigh-corrected reflectances for these two bands. The calculated corresponding perturbation for Ruddick's second assumption is several times larger than what Ruddick et al. evaluated under simple b_b/α model. Such perturbation-related error could reach 20% for the highly turbid water over the Pearl River estuary.

In this paper, an improved semi-analytic Monte Carlo method is used to simulate the lidar received backscattering signals. The H-G function is used to approximate the scattering phase function of seawater, from which we can derive the scattering angle directly, and a modified H-G function is used to calculate the probability of the photons received by the receiver at each scattering point, which greatly improves the accuracy of the simulation. The simulation result shows that the different parameters of air-sea system of lidar, such as lidar’s field of view, attenuation coefficient and single scattering albedo of seawater, greatly influence the lidar received backscattering signal waveform. Multiple scattering is studied to explain these phenomena.

The space and time variability of chlorophyll concentration detected by the satellite-borne sea color sensor SeaWiFS over years 1998 to 2001 in the south western Pacific Ocean (150°E - 140°W, 0° - 40°S) is first described using Fourier's analysis. The region usually has low chlorophyll concentration, except near New Zealand. Seasonal variations are small. The main pattern of seasonal variation is a maximum in austral winter between 20°S and 40°S when cooling of surface waters reduces the vertical stability of the water column and favors the supply of nutrients from below, and subsequent phytoplankton growth. Some areas have high interannual variability, such as the surface waters near the equator that were affected by the 1997 - 98 El Nino, and had abnormally high pigments concentration when conditions returned to normal, and the region for Vanuatu to Fiji Islands where sporadic blooms of Cyanobacteria Trichodesmium are known to occur. Field data collected quarterly along the track of a merchant ship are used to characterize the phytoplankton populations in this region. Indeed, it is recognized that different phytoplankton populations may have different impact on the geochemistry of the ocean, such as the Coccolithophorids that carry out both biocalcification and photosynthesis, thus reducing the alkalinity of seawater, or Trichodesmium that use atmospheric N₂ to fufill its nitrogen requirements and thus is not dependent on inorganic nitrogen sources. Cells counts and pigments determinations show that the phytoplankton populations are dominated by the picoplankton (Prochlorococcus, Synechococcus and picoeucaryotes). High numbers of Synechococcus have sometimes been found Near New Zealand.

In this paper, using TOPEX/Poseidon (9~346cycle) and Geosat/ERM(1~60cycle) altimeter data, the author applies combined adjustment model for calculating the South China Sea geoid undulations after data preprocessing. The difference between calculation result and OSU91A model is 30cm (spatial resolution is 22km). In addition, 12’x12’ South China Sea gravity anomalies are calculated by using above geoid data and improved Stokes inverse formula. Contrasted with Scripps Institution of Oceanography gravity anomalies data, the accuracy of computation of gravity anomalies is 12´x10^-5m/s². These computations show that calculation speed is fast and calculation efficiency is high, so the method can calculate rapidly gravity anomalies in special sea area.

Much effort has been made in the radiometric calibration of the ocean scanning multispectral imager (OSMI) since after the successful launch of KOMPSAT-1 in 1999. A series of calibration coefficients for OSMI detectors were obtained in collaboration with the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary (SIMBIOS) project office. In this study, we compare the OSMI level-2 products (e.g., chlorophyll-a concentration) calculated from the NASA cross-calibration coefficients with the SeaWiFS counterparts. Sample study areas are some of diagonostic data sites recommended by the SIMBIOS working group. We will present the preliminary results of this comparative study.

As the spatial resolution is improved for "ocean color" satellite sensors, such observations become relevant to monitor water quality for lakes. The required atmospheric corrections can not be conducted using the standard algorithms developed for ocean: need to account for the lake elevation, high water turbidity... The new generation of sensors has more spectral bands which allow to characterize the aerosol over dark land pixels (vegetation in the blue and in the red). Dense vegetation is identified using a spectral index and its reflectance is known from auxiliary data. We then derive, from the top of atmosphere radiances in two spectral bands, the optical thickness and the size distribution for aerosol. Knowing the aerosol model in the lake vicinity, it is then possible to apply atmospheric corrections over inland waters. A specific difficulty arises from the contamination of the photons reflected by the surrounding land and scattered towards the sensor. A simple formulation to correct this adjacency effect can be used for the Rayleigh scattering. We force the 865 nm water reflectance to be equal to zero to derive for each water pixel a function describing the aerosol adjacency effect. Assuming that the aerosol phase function does not vary much with the wavelength, we can correct all the spectral bands. The different stages of this new algorithm are illustrated on SeaWiFS.

Operational MERIS (MEdium Resolution Imaging Spectrometer) level-2 processing uses auxiliary data generated by two radiative transfer tools. These two codes simulate upwelling radiances within a coupled 'Atmosphere-Ocean' system, using different approaches based on the matrix-operator method (MOMO) and the successive orders (SO) technique. Intervalidation of these two radiative transfer codes was performed in order to implement them in the MERIS level-2 processing. MOMO and SO simulations were then conducted on a set of representative test cases. Results stressed both for all test cases good agreements were observed. The scattering processes are retrieved within a few tenths of a percent. Nevertheless, some substantial discrepancies occurred if the polarization is not taken into account mainly in the Rayleigh scattering computations. A preliminary study indicates that the impact of the code inaccuracy in the water leaving radiances retrieval (a level-2 MERIS product) is large, up to 50% in relative difference. Applying the OC2 algorithm, the effect on the retrieval chlorophyll concentration is less than 10%.

The first "ocean colour" sensor, Coastal Zone Color Scanner (CZCS), was launched in 1978. Oceanographers learnt a lot from CZCS but it remained a purely scientific sensor. In recent years, a new generation of satellite-borne earth observation (EO) instruments has been brought into space. These instruments combine high spectral and spatial resolution with revisiting rates of the order of one per day. More instruments with further increased spatial, spectral and temporal resolution will be available within the next years. In the meantime, evaluation procedures taking advantage of the capabilities of the new instruments were derived, allowing the retrieval of ecologically important parameters with higher accuracy than before. Space agencies are now able to collect and to process satellite data in real time and to disseminate them via the Internet. It is therefore meanwhile possible to envisage using EO operationally. In principle, a significant demand for EO data products on terrestrial or marine ecosystems exists both with public authorities (environmental protection, emergency management, natural resources management, national parks, regional planning, etc) and private companies (tourist industry, insurance companies, water suppliers, etc). However, for a number of reasons, many data products that can be derived from the new instruments and methods have not yet left the scientific community towards public or private end users. It is the intention of the proposed SISCAL (Satellite-based Information System on Coastal Areas and Lakes) project to contribute to the closure of the existing gap between space agencies and research institutions on one side and end users on the other side. To do so, we intend to create a data processor that automatically derives and subsequently delivers over the Internet, in Near-Real-Time (NRT), a number of data products tailored to individual end user needs. The data products will be generated using a Geographical Information System (GIS), combining satellite data, evaluation algorithms and value-adding ancillary digital information. This prevents the end user from investing funds into expensive equipment or to hire specialized personnel. The data processor shall be a generic tool, which may be applied to a large variety of operationally gathered satellite data. In the frame of SISCAL, the processor shall be applied to remotely sensed data of selected coastal areas and lakes in Central Europe and the Eastern Mediterranean, according to the needs of the end users within the SISCAL consortium. A number of measures are required to achieve the objective of the proposed project: (1) Identification and specification of the SISCAL end user needs for NRT water related data products accessible to EO techniques. (2) Selection of the most appropriate instruments, evaluation algorithms and ancillary data bases required to provide the identified data products. (3) Development of the actual Near-Real-Time data processor for the specified EO data products. (4) Development of the GIS processor adding ancillary digital information to the satellite images and providing the required geographical projections. (5) Development of a product retrieval and management system to handle ordering and distribution of data products between the SISCAL server and the end users, including payment and invoicing. (6) Evaluation of the derived data products in terms of accuracy and usefulness by comparison with available in-situ measurements and by making use of the local expertise of the end users. (7) Establishing an Internet server dedicated to internal communication between the consortium members as well as presenting the SISCAL project to a larger public. (8) Marketing activities, presentation of data processor to potential external customers, identification of their exact needs. The innovative aspect of the SISCAL project consists in the generation of NRT data products on water quality parameters from EO data. This article mainly deals with the identification of the end user requirements within the SISCAL consortium and the methods employed to realize them. Details on the technical implementation of the SISCAL processor are provided by Fell et al. (this issue).

The aerosol climatology used in the atmospheric correction algorithms may not be representative enough of the coastal areas. We take advantage of a network of ground-based measurements of aerosol optical properties (the CIMEL instrument in AERONET) to validate these aerosol models. From space, the selection of the aerosol model is based on the spectral dependency of the aerosol path radiances between the red and infrared. A similar scheme is applied on the CIMEL extinction measurements. Knowing the standard aerosol model and the optical thickness, we simulated the sky radiances and the atmospheric transmittances. An extensive comparison between these simulations and the CIMEL measurements is conducted for two sites in the European waters. The impact of the use of the standard aerosol climatology on the retrieval of the water leaving radiances over coastal areas is also evaluated.

SISCAL (Satellite-based Information System on Coastal Areas and Lakes) is a pan-European project dedicated to develop facilities to provide end-users with customized and easy-to-use data for environmental monitoring of coastal areas and lakes. The main task will be to create a software system providing Near-Real-Time information on the aquatic environment (using instruments such as AVHRR, MODIS or MERIS) and ancillary GIS-data. These products will be tailored to individual customers needs, allowing them to exploit Earth Observation (EO) data without extensive in-house knowledge. This way, SISCAL aims at closing the gap between research institutes, satellite data providers and the actual end-users. Data and information exchange will entirely take place over the internet, from the acquisition of satellite data raw from the providers to the dissemination of finalized data products to the end-users. The focus of SISCAL is set on the optimal integration of existing techniques. The co-operation between the ten SISCAL partners, including four end-users representative of public authorities from local to national scale, aims at strengthening the operational use of EO data in the management of coastal areas and lakes.

Remote sensed chlorophyll α (chlα) maps are useful to proceed to phytoplankton dynamics study and primary production modelization in coastal waters. However, chlα remote sensing depend on the bio-optical characteristics of waters masses which are site-specific and highly variable according to space and time in coastal waters. In order to study the seasonal variability of phytoplankton and bio-optic parameters as well as the factors controlling their spatio-temporal distributions, five mesoscale cruises (BIOPTEL) were carried out in the eastern English Channel during the spring 2000 (between February and October). Phytoplankton absorption spectrum showed a high variability according to space and time due to the algal community composition and the physiological state. Considering these scales of variation, a local model was defined. The variability of the two other components of marine absorption: yellow substances and non algal particles are also presented and related to exogenous parameters such as river flow, temperature and hydrodynamism. Furthermore, in order to appreciate how important are the local IOPs (Inherent Optical Properties) variability on AOPs (Apparent Optical Properties) restitution a sensitivity analysis was realized. In the frame of biomass estimation, marine reflectance were simulated considering the local absorption coefficients rather than the standard ones.

The Pearl River estuary and Hong Kong's coastal waters were selected to study the ocean color categories related to water quality. Three ocean color sensitive parameters: turbidity, suspended sediments (SS) and chlorophyll-a concentration (Chl-a), in 58 monitoring stations were selected to evaluate the water quality. A dataset with 88 samples was picked up from the monitoring stations and the successfully retrieved points of SS and Chl-a from SeaWiFS, 66 of the 88 samples were used at training data and the other 22 as testing data. The normalized difference water index was extracted from the Landsat TM image on Dec. 22, 1998 and the threshold segmentation was used to retrieve the waters from the image for further analysis. The methods of maximum likelihood, neural network and support vector machine were employed for ocean color classification of the selected Landsat TM image. Five classes of water quality could be well interpreted for all the methods. The results showed spatial variation from the west turbid waters to the east relative clear waters and suggested that the turbid wsters could be well classified using Landsat TM data.

Algal chlorophyll measurement is usually used to assess trophic status of lakes. The development of satellite remote sensing technology make it possible to detect spectral features of algal chlorophyll and to map the spatial distribution of algae in large lakes. In this paper, NOAA satellite data were utilized to monitor the blue-green algae waterbloom in Chaohu Lake, together with the water sampling for concentrations of chlorophhyll-a analysis and spectral measuring simultaneously. The result indicates that: if there are chlorophylls of blue-green algae, the water reflectance in the near infrared band will obviously increase. Based on this spectral characteristic and the features of blue-green algae' float, meteorological satellite NOAA/AVHRR data can be used to monitor the blue-green algae waterbloom in large badly contaminated inland lakes.

Data of wind field of satellite scatterometer, height abnormality of altimeter and sea surface temperature of radiometer were used to analyze the seasonal variations of monsoon, circulation and surface temperature in South China Sea as well as the interaction among monsoon, circulation and heat radiation. It is proved from long time series data that South China Sea is prevailed with northeast monsoon in winter and there are two stable or one merged cyclonic circulations. In summer, southwest monsoon prevails and the seasonal circulation is consisted of two stable anticyclonic circulations, while the contours of surface temperature is in northeast-southwest direction corresponding with the direction of monsoon either in winter or summer, in addition there is a cold water tongue in sea areas south to Indo-Chinese Peninsula. There is significant resonant relationship among the fields of sea surface height, temperature and the wind field of monsoon in South China Sea in periods of annual scale, it can be concluded that the stable and strong monsoon is one of the major driving forces for circulation and sea surface heat exchange in South China Sea.