Ocean sand ridge signatures in the Bohai Sea observed by satellite ocean color and synthetic aperture radar measurements

Satellite measurements from Synthetic Aperture Radar (SAR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua platform are used to study the ocean sand ridges in the eastern Bohai Sea in China. Even though the imaging mechanisms for SAR and MODIS-Aqua remote sensing are different, the sand ridges are shown to have exactly the same patterns in images from both sensors. Therefore, the location, extension and coverage of the ocean sand ridges can be detected and cross-examined by both SAR and MODIS-Aqua observations. Satellite images show quite different sand ridge distribution pattern from the published bathymetry map (based on in situ data) that shows six sand ridges in the area. 10 finger-shaped sand ridges are identified from satellite observations. The tidal-current/sand-ridge interaction driven physical and optical changes are assessed and evaluated. The existence of sand ridges causes enhanced water diffuse attenuation coefficient K_d(490) and elevated normalized water-leaving radiance at the red and near-infrared (NIR) wavelengths. The sea surface over the sand ridges experiences significant seasonal variability of water turbidity and shows remarkable differences from nearby ocean regions. During winter, K_d(490) values are about 2-3 m^− 1 over the ridges, while the maximum K_d(490) in the neighboring oceans is approximately 1.5 m^− 1. In summer, the enhancement of the sea surface turbidity is less significant than that which occurs in winter.     

Satellite observations of optical and biological properties in the Korean dump site of the Yellow Sea

With the standard near-infrared (NIR) atmospheric correction algorithm for ocean color data processing, a high chlorophyll-a concentration patch was consistently observed from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua platform in the middle of the Yellow Sea during the spring (end of March to early May). This prominent patch was not observed in the historical ocean color satellite imageries in late 1970s to early 1980s, and a location corresponding to this patch has been used as a Korean dump site since 1988. At the same time, MODIS chlorophyll-a concentrations derived using the shortwave infrared (SWIR) atmospheric correction algorithm developed for the ocean color satellite data in turbid coastal or high-productive ocean waters were significantly reduced.Comparison between in situ and MODIS chlorophyll-a measurements shows that the chlorophyll-a from the MODIS-Aqua products using the standard-NIR atmospheric correction algorithm is significantly overestimated. The images of the MODIS-derived normalized water-leaving radiance spectra and water diffuse attenuation coefficient data using the NIR-SWIR-based atmospheric correction approach show that absorption and scattering by organic and inorganic matter dumped in the Korean dump site have strongly influenced the satellite-derived chlorophyll-a data. Therefore, the biased high chlorophyll-a patch in the region is in fact an overestimation of chlorophyll-a values due to large errors from the standard-NIR atmospheric correction algorithm. Using the NIR-SWIR algorithm for MODIS-Aqua ocean color data processing, ocean color products from 2002 to 2008 for the Korean dump site region have been generated and used for characterizing the ocean optical and biological properties. Results show that there have been some important changes in the seasonal and interannual variations of phytoplankton biomass and other water optical and biological properties induced by colored dissolved organic matters, as well as suspended sediments.     

MODIS imagery of turbid plumes in San Diego coastal waters during rainstorm events

Data of normalized water-leaving radiance, nLw, obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite at spatial resolution of 250 m (band 1 centered at 645 nm) and 500 m (band 4 at 555 nm) are used to study turbid plumes in coastal waters of southern California during rainstorm events in winter of 2004-2005. Our study area includes San Diego coastal waters, which extend approximately 25 km offshore between Point Loma and 10 km south of the US-Mexican border. These waters are influenced by terrigenous input of particulate and dissolved materials from San Diego and Tijuana watersheds and non-point sources along the shore. Optimum threshold values of satellite-derived normalized water-leaving radiances at both wavebands were established for distinguishing the plume from ambient ocean waters. These threshold values were determined by searching for a maximum correlation between the estimates of satellite-derived plume area calculated using a broad range of nLw values and the environmental variables characterizing rainfall, river discharge, wind, and tides. A correlation analysis involving the amount of precipitated water accumulated during a storm event over the San Diego and Tijuana watersheds was selected as the basis for final determinations of the optimum threshold nLw_thr and subsequent calculations of the plume area. By applying this method to a sequence of MODIS imagery, we demonstrate the spatial extent and evolution of the plume during rainstorm events under various conditions of precipitation, river discharge, wind forcing, and coastal currents.     

The atmospheric correction of water colour and the quantitative retrieval of suspended particulate matter in Case II waters: Application to MERIS

The remote sensing of turbid waters (Case II) using the Medium Resolution Imaging Spectrometer (MERIS) requires new approaches for atmospheric correction of the data. Unlike the open ocean (Case I waters) there are no wavelengths where the water-leaving radiance is zero. A coupled hydrological atmospheric model is described here. The model solves the water-leaving radiance and atmospheric path radiance in the near-infrared (NIR) over Case II turbid waters. The theoretical basis of this model is described, together with its place in the proposed MERIS processing architecture. Flagging procedures are presented that allow seamless correction of both Case I waters, using conventional models, and Case II waters using the proposed model. Preliminary validation of the model over turbid waters in the Humber estuary, UK is presented using Compact Airborne Spectrographic Imager (CASI) imagery to simulate the MERIS satellite sensor. The results presented show that the atmospheric correction scheme has superior performance over the standard single scattering approach, which assumes that water-leaving radiance in the NIR is zero. Despite problems of validating data in such highly dynamic tidal waters, the results show that retrievals of sediments within 50% are possible from algorithms derived from the theoretical models.     

New strategy to improve estimation of diffuse attenuation coefficient for highly turbid inland waters

The diffuse attenuation coefficient, K_d(λ), is an important water optical property. Detection of K_d(λ) by means of remote sensing can provide significant assistance in understanding water environment conditions and many biogeochemical processes. Even when existing algorithms exhibit good performance in clear open ocean and turbid coastal waters, accurate quantification of highly turbid inland water bodies can still be a challenge due to their bio-optical complexity. In this study, we examined the performance of two typical pre-existing K_d(490) models in inland water bodies from Lake Taihu, Lake Chaohu, and the Three Gorges Reservoir in China. On the basis of water optical classification, new K_d(490) models were developed for these waters by means of the support vector machine approach. The obtained results showed that the two pre-existing K_d(490) models presented relatively large errors by comparison with the new models, with mean absolute percentage error (MAPE) values above ~30%. More importantly, among the new models, type-specific models generally outperformed the aggregated model. For water classified as Type 1 + Type 2, the type-specific model produced validation errors with MAPE = 16.8% and RMSE = 0.98 m^?1. For water classified as Type 3, the MAPE and RMSE of the type-specific model were found to be 18.8% and 1.85 m^?1, respectively. The findings in this study demonstrate that water classification (prior to algorithm development) is needed for the development of excellent K_d(490) retrieval algorithms, and the type-specific models thus developed are an important supplement to existing K_d(490) retrieval models for highly turbid inland waters.     

Remote sensing of cyanobacteria-dominant algal blooms and water quality parameters in Zeekoevlei, a small hypertrophic lake, using MERIS

Eutrophication and cyanobacterial algal blooms present an increasing threat to the health of freshwater ecosystems and to humans who use these resources for drinking and recreation. Remote sensing is being used increasingly as a tool for monitoring these phenomena in inland and near-coastal waters. This study uses the Medium Resolution Imaging Spectrometer (MERIS) to view Zeekoevlei, a small hypertrophic freshwater lake situated on the Cape Flats in Cape Town, South Africa, dominated by Microcystis cyanobacteria. The lake's small size, highly turbid water, and covariant water constituents present a challenging case for both algorithm development and atmospheric correction. The objectives of the study are to assess the optical properties of the lake, to evaluate various atmospheric correction procedures, and to compare the performance of empirical and semi-analytical algorithms in hypertrophic water. In situ water quality parameter and radiometric measurements were made simultaneous to MERIS overpasses. Upwelling radiance measurements at depth 0.66 m were corrected for instrument self-shading and processed to water-leaving reflectance using downwelling irradiance measurements and estimates of the vertical attenuation coefficient for upward radiance, K_u, generated from a simple bio-optical model estimating the total absorption, a(λ), and backscattering coefficients, b_b(λ). The normalised water-leaving reflectance was used for assessing the accuracy of image-based Dark Object Subtraction and 6S Radiative Transfer Code atmospheric correction procedures applied to MERIS. Empirical algorithms for estimating chlorophyll a (Chl a), Total Suspended Solids (TSS), Secchi Disk depth (z_SD) and absorption by CDOM (a_CDOM) were derived from simultaneously collected in situ and MERIS measurements. The empirical algorithms gave high correlation coefficient values, although they have a limited ability to separate between signals from covariant water constituents. The MERIS Neural Network algorithms utilised in the standard Level 2 Case 2 waters product and Eutrophic Lakes processor were also used to derive water constituent concentrations. However, these failed to produce reasonable comparisons with in situ measurements owing to the failure of atmospheric correction and divergence between the optical properties and ranges used to train the algorithms and those of Zeekoevlei. Maps produced using the empirical algorithms effectively show the spatial and temporal variability of the water quality parameters during April 2008. On the basis of the results it is argued that MERIS is the current optimal sensor for frequent change detection applications in inland waters. This study also demonstrates the considerable potential value for simple TOA algorithms for hypertrophic systems. It is recommended that regional algorithm development be prioritized in southern Africa and that remote sensing be integrated into future operational water quality monitoring systems.     

Evaluation of shortwave infrared atmospheric correction for ocean color remote sensing of Chesapeake Bay

The NASA Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODIS-Aqua) provides a viable data stream for operational water quality monitoring of Chesapeake Bay. Marine geophysical products from MODIS-Aqua depend on the efficacy of the atmospheric correction process, which can be problematic in coastal environments. The operational atmospheric correction algorithm for MODIS-Aqua requires an assumption of negligible near-infrared water-leaving radiance, nL_w(NIR). This assumption progressively degrades with increasing turbidity and, as such, methods exist to account for non-negligible nL_w(NIR) within the atmospheric correction process or to use alternate radiometric bands where the assumption is satisfied, such as those positioned within shortwave infrared (SWIR) region of the spectrum. We evaluated a decade-long time-series of nL_w(λ) from MODIS-Aqua in Chesapeake Bay derived using NIR and SWIR bands for atmospheric correction. Low signal-to-noise ratios (SNR) for the SWIR bands of MODIS-Aqua added noise errors to the derived radiances, which produced broad, flat frequency distributions of nL_w(λ) relative to those produced using the NIR bands. The SWIR approach produced an increased number of negative nL_w(λ) and decreased sample size relative to the NIR approach. Revised vicarious calibration and regional tuning of the scheme to switch between the NIR and SWIR approaches may improve retrievals in Chesapeake Bay, however, poor SNR values for the MODIS-Aqua SWIR bands remain the primary deficiency of the SWIR-based atmospheric correction approach.     

An assessment of the black ocean pixel assumption for MODIS SWIR bands

Recent studies show that an atmospheric correction algorithm using shortwave infrared (SWIR) bands improves satellite-derived ocean color products in turbid coastal waters. In this paper, the black pixel assumption (i.e., zero water-leaving radiance contribution) over the ocean for the Moderate Resolution Imaging Spectroradiometer (MODIS) SWIR bands at 1240, 1640, and 2130 nm is assessed for various coastal ocean regions. The black pixel assumption is found to be generally valid with the MODIS SWIR bands at 1640 and 2130 nm even for extremely turbid waters. For the MODIS 1240 nm band, however, ocean radiance contribution is generally negligible in mildly turbid waters such as regions along the U.S. east coast, while some slight radiance contributions are observed in extremely turbid waters, e.g., some regions along the China east coast, the estuary of the La Plata River. Particularly, in the Hangzhou Bay, the ocean radiance contribution at the SWIR band 1240 nm results in an overcorrection of atmospheric and surface effects, leading to errors of MODIS-derived normalized water-leaving radiance at the blue reaching ~ 0.5 mW cm^− 2 μm^− 1 sr^− 1. In addition, we found that, for non-extremely turbid waters, i.e., the ocean contribution at the near-infrared (NIR) band < ~ 1.0 mW cm^− 2 μm^− 1 sr^− 1, there exists a good relationship in the regional normalized water-leaving radiances between the red and the NIR bands. Thus, for non-extremely turbid waters, such a red-NIR radiance relationship derived regionally can possibly be used for making corrections for the regional NIR ocean contributions without using the SWIR bands, e.g., for atmospheric correction of ocean color products derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS).     

Validation of MERIS ocean-color products in the Bohai Sea: A case study for turbid coastal waters

An extensive in situ data set in the Bohai Sea of China was collected to assess radiometric properties and concentrations of ocean constituents derived from Medium Resolution Imaging Spectrometer (MERIS). The data collected include spectral normalized water-leaving radiance L_wn(λ) and concentrations of suspended particulate matter (SPM) and chlorophyll a (Chl-a). A strict spatio-temporal match-up method was adopted in view of the complexity and variability of the turbid coastal area, resulting in 13, 48 and 18 match-ups for MERIS L_wn(λ), SPM and Chl-a estimates, respectively. For MERIS L_wn(λ), the match-ups showed mean absolute percentage differences (APD) of 17%-20% in the 412, 443, 620 and 665 nm bands, whereas L_wn(λ) at bands from 490 and 560 nm had better APD of 15-16%. The band ratio of L_wn(490) to L_wn(560) of the satellite data was in good agreement with in situ observations with an APD of 4%. MERIS SPM and Chl-a products overestimated the in situ values, with the APD of approximately 50% and 60%, respectively. When match-up criteria were relaxed, the assessment results degraded systematically. Hence, in turbid coastal areas where temporal variability and spatial heterogeneity of bio-optical properties may be pronounced as the result of terrestrial influences and local dynamics, the strict spatio-temporal match-up is recommended.     

Suspended particulate matter in Lake Erie derived from MODIS aquatic colour imagery

This paper explores the use of Moderate Resolution Imaging Spectroradiometer (MODIS) wavebands in the red/near-infra-red for estimating concentrations of suspended particulate matter (SPM) in the moderately turbid, optically complex waters of Lake Erie. Observations show that at wavelengths shorter than 550 nm, more than 50% of the absorption signal is accounted for by dissolved organic matter and phytoplankton, confirming that algorithms incorporating these wavelengths may not be appropriate for these waters. Single band and band ratios at wavelengths greater than 667 nm are tested for their suitability for monitoring SPM concentrations in these waters. A simplified regional semi-analytical model is utilized which is independent of variations in dissolved organic matter and chlorophyll absorption, enabling estimates of SPM concentrations from MODIS water-leaving radiance at 748 nm with an average root mean square (RMS) error of 40%. Knowledge of the vertical distribution of particles enables estimates of total water column suspended loads which are then related to wind re-suspension events. The method is applied to MODIS water-leaving radiance at 748 nm to produce a time series of surface and total water column suspended loads in Lake Erie for the period 2003–2007.     

Evaluation of spatio-temporal variations in chlorophyll-a in Lake Naivasha,Kenya: remote-sensing approach

Restoration of the ecosystem services and functions of lakes requires an understanding of the turbidity dynamics in order to arrive at informed environmental management decisions. The understanding of the spatio-temporal dynamics of turbidity requires frequent monitoring of the turbidity components such as chlorophyll-a concentration. In this study, we explored the use of Moderate Resolution Imaging Spectroradiometer Aqua (MODIS-Aqua) satellite data in studying the spatio-temporal changes in chlorophyll-a concentration in Lake Naivasha, a turbid tropical system. The temporal trend of chlorophyll-a concentration over the study period in the lake was also evaluated. The temporal trend assessment was achieved through the removal of periodic seasonal interference using Seasonal-Trend decomposition based on the LOESS (Local Regression) procedure. The resultant chlorophyll-a concentration maps derived from MODIS-Aqua satellite data give an indication of the monthly spatial variation in chlorophyll-a concentration from 2002 to 2012. The results of regression analyses between satellite-derived chlorophyll-a and in situ measurements reveal a high level of precision, but with a measureable bias with the satellite underestimating actual in situ measurements (R² = 0.65, P < 0.001). Although the actual values of the chlorophyll-a concentrations are underestimated, the significant relationship between satellite-derived chlorophyll-a and in situ measurements provides reliable information for studying spatial variations and temporal trends. In 2009 and 2010, it was difficult to detect chlorophyll-a from the MODIS-Aqua imagery, and this coincided with a period of the lowest water levels in Lake Naivasha. An inverse relationship between de-seasoned water level and chlorophyll-a concentration was evident. This study shows that MODIS-Aqua satellite data provide useful information on the spatio-temporal variations in Lake Naivasha, which is useful in establishing general trends that are more difficult to determine through routine ground measurements.     

Validation of a synthetic chlorophyll index for remote estimates of chlorophyll-a in a turbid hypereutrophic lake

Remote sensing techniques can offer powerful tools for measuring concentrations of chlorophyll-a (chl-a), which is an important proxy for water quality. However, remote estimates of chl-a can be difficult in water bodies that have high levels of total suspended matter (TSM). In this study, we examined the applicability of the synthetic chlorophyll index (SCI) and a parameter relevant to chlorophyll pigments (H_chl) used in conjunction with remote-sensing data to predict chl-a concentrations (C_chl-a) in Taihu Lake, a highly turbid hypereutrophic lake in eastern China. We sampled water quality and surface spectral properties at 250 field stations throughout the lake over five sampling periods spanning 2 years. Because data acquired at 31 stations could not be used due to equipment failure or blue-green algal blooms, we used data acquired at the remaining 219 stations. We then randomly selected parts of the spectral properties data (N = 164) to calibrate bands used in the SCI algorithm and established cubic polynomial models to estimate C_chl-a with SCI and H_chl as the independent variables. We evaluated the accuracy of these models using data from the remaining 55 stations that were not used for calibration. Our results showed the following trends: (1) the parameter of H_chl performed better than SCI in estimating C_chla in Taihu Lake; (2) H_chl showed optimal performance in winter, average performance in spring, and poor performance in summer and autumn; (3) H_chl was appropriate for the NAP-dominant waters with high C_TSM and low C_chl-a, but was not suitable for organism-dominant waters with low C_TSM; and (4) in short, H_chl had limited usability in turbid and eutrophic waters.     

Detecting the red tide algal blooms from satellite ocean color observations in optically complex Northeast-Asia Coastal waters

Over the last few decades, the coastal regions throughout the world have experienced incidences of algal blooms, which are harmful or otherwise toxic because of their potential threat to humans as well as marine organisms, owing to accelerated eutrophication from human activities and certain oceanic processes. Previous studies have found that correct identification of these blooms remains a great challenge with the standard bio-optical algorithms applied to satellite ocean color data in optically complex coastal waters containing high concentrations of the interfered dissolved organic and particulate inorganic materials. Here a new method called the red tide index (RI) is presented which is capable of identifying potential areas of harmful algal blooms (HABs) from SeaWiFS ocean color measurements representing the typical Case-2 water environments off the Korean and Chinese coasts. The RI method employs the water-leaving radiances (L_w), collected from in-situ radiometric measurements of three SeaWiFS bands centered at 443 nm, 510 nm and 555 nm, to achieve derivation of indices that are then related to absorbing characteristics of harmful algae (i.e., L_w at 443 nm) from which a best fit with a cubic polynomial function with correlation coefficient of R² = 0.91 is obtained providing indices of higher ranges for HABs and lower and slightly reduced ranges for turbid and non-bloom waters. Similar indices derived from the use of remote sensing reflectance (R_rs), normalized water-leaving radiance (nL_w) and combination of both are found rather inadequate to characterize the variability of the encountered bloom. In order to quantify the HABs in terms of chlorophyll (Chl), an empirical relationship is established between the RI and in-situ Chl in surface waters from about 0.4-71 mg m^− 3, which yields a Red tide index Chlorophyll Algorithm (RCA) based on an exponential function with correlation coefficient R² = 0.92. The established methods were extensively tested and compared with the performances of standard Ocean Chlorophyll 4 (OC4) algorithm and Local Chlorophyll Algorithm (LCA) using SeaWiFS images collected from typical red tide waters of Korean South Sea (KSS), East China Sea (ECS), Yellow Sea (YS) and Bohai Sea (BS) during 1999-2002. The standard spectral ratio algorithms, the OC4 and LCA, yielded large errors in Chl retrievals for coastal areas, besides providing false information about the encountered HABs in KSS, ECS, YS and BS waters. On the contrary, the RI coupled with the standard spectral ratios yielded comprehensive information about various ranges of algal blooms, while RCA Chl showing a good agreement with in-situ data led to enhanced understanding of the spatial and temporal variability of the recent HAB occurrences in high scattering and absorbing waters off the Korean and Chinese coasts.     

Atmospheric correction based on inherent optical properties of sea water at NIR wavelengths combined with an automated aerosol spectra determination (ASD) technique

Atmospheric correction is the process whereby atmospheric effects on sensor-recorded radiance are removed and the surface radiance is estimated. Atmospheric effects due to gaseous absorption, molecular scattering – and their seasonal as well as latitudinal variations – can be adequately accounted for by using pre-computed look-up tables. However, scattering by aerosol particles is difficult to correct. At-sensor radiance at near-infrared (NIR) wavelengths, after being corrected for gaseous absorption and molecular scattering, was assumed (in standard atmospheric correction) to have been entirely due to aerosol scattering and was used to calculate the aerosol parameters. This assumption, although valid for open ocean clear waters, is not valid for turbid waters due to scattering by suspended particles in the water, which results in an appreciable amount of water-leaving radiance in the NIR region. A new turbid water atmospheric correction scheme is described here for Oceansat-2 Ocean Colour Monitor (OCM-2) data based on inherent optical properties (IOPs) of sea water at NIR, and obtaining an accurate spectral profile of aerosol radiance.     

Bio‐optical model with optimal parameter suitable for Taihu Lake in water colour remote sensing

Sixty‐seven samplings were collected, almost covering all over the Taihu Lake, in one campaign in October 2004. At each station, the backscattering coefficients and the field spectra were measured in situ, respectively, with a HS‐6 and a FieldSpec 931 spectroradiometer (ASD Inc.). Almost concurrently, water samples were fetched with Niskin water‐fetching equipment and then returned to the laboratory for concentration and absorption measurement. The whole lake was divided into different areas according to some indexes. Three models were used to calculate remote sensing reflectance R _rsc for the waters where the in situ remote sensing reflectance R _rsm was beyond the bottom effect, which was considered as optically deep waters. By comparison of R _rsc and R _rsm, the best model suitable for optically deep waters in Taihu Lake, together with its optimal experiential parameter, were selected and developed, which was very important and helpful to develop a universal model to estimate accurately remote sensing reflectance for the whole lake in the next step.     

Comparison of three SeaWiFS atmospheric correction algorithms for turbid waters using AERONET-OC measurements

The use of satellites to monitor the color of the ocean requires effective removal of the atmospheric signal. This can be performed by extrapolating the aerosol optical properties in the visible from the near-infrared (NIR) spectral region assuming that the seawater is totally absorbant in this latter part of the spectrum. However, the non-negligible water-leaving radiance in the NIR which is characteristic of turbid waters may lead to an overestimate of the atmospheric radiance in the whole visible spectrum with increasing severity at shorter wavelengths. This may result in significant errors, if not complete failure, of various algorithms for the retrieval of chlorophyll-a concentration, inherent optical properties and biogeochemical parameters of surface waters.This paper presents results of an inter-comparison study of three methods that compensate for NIR water-leaving radiances and that are based on very different hypothesis: 1) the standard SeaWiFS algorithm (Stumpf et al., 2003; Bailey et al., 2010) based on a bio-optical model and an iterative process; 2) the algorithm developed by Ruddick et al. (2000) based on the spatial homogeneity of the NIR ratios of the aerosol and water-leaving radiances; and 3) the algorithm of Kuchinke et al. (2009) based on a fully coupled atmosphere-ocean spectral optimization inversion. They are compared using normalized water-leaving radiance nL_w in the visible. The reference source for comparison is ground-based measurements from three AERONET-Ocean Color sites, one in the Adriatic Sea and two in the East Coast of USA.Based on the matchup exercise, the best overall estimates of the nL_w are obtained with the latest SeaWiFS standard algorithm version with relative error varying from 14.97% to 35.27% for λ = 490 nm and λ = 670 nm respectively. The least accurate estimates are given by the algorithm of Ruddick, the relative errors being between 16.36% and 42.92% for λ = 490 nm and λ = 412 nm, respectively. The algorithm of Kuchinke appears to be the most accurate algorithm at 412 nm (30.02%), 510 (15.54%) and 670 nm (32.32%) using its default optimization and bio-optical model coefficient settings.Similar conclusions are obtained for the aerosol optical properties (aerosol optical thickness τ(865) and the Ångström exponent, α(510, 865)). Those parameters are retrieved more accurately with the SeaWiFS standard algorithm (relative error of 33% and 54.15% for τ(865) and α(510, 865)).A detailed analysis of the hypotheses of the methods is given for explaining the differences between the algorithms. The determination of the aerosol parameters is critical for the algorithm of Ruddick et al. (2000) while the bio-optical model is critical for the algorithm of Stumpf et al. (2003) utilized in the standard SeaWiFS atmospheric correction and both aerosol and bio-optical model for the coupled atmospheric-ocean algorithm of Kuchinke. The Kuchinke algorithm presents model aerosol-size distributions that differ from real aerosol-size distribution pertaining to the measurements. In conclusion, the results show that for the given atmospheric and oceanic conditions of this study, the SeaWiFS atmospheric correction algorithm is most appropriate for estimating the marine and aerosol parameters in the given turbid waters regions.     

SeaWiFS data interpretation in a coastal area in the Bay of Biscay

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) instrument, launched onboard the Orbimage 2 satellite, is composed of an optical scanner with eight channels that are used to interpret the ocean colour, and has been operational since September 1997. SeaWiFS data were received by the Dundee Satellite Receiving Station and processed by the Plymouth Marine Laboratory with a slight time-lag. In situ measurements of reflectance, salinity, seston and chlorophyll a were analysed during the Biomet surveys to gain a better knowledge of the dynamics of the Gironde turbid plume during this period. The results showed logarithmic relationships between the SeaWiFS normalized water-leaving radiances (n L w ) at 490 and 555 nm (n L w (490) and n L w (555)), and the suspended particle matter concentrations. The relationship between the n L w (555) radiances and these concentrations is used to map the coastal terrigenous turbidities. But the chlorophyll a concentrations calculated from SeaWiFS are overestimated in the turbid waters. The n L w (490)/n L w (555) ratio decreases with increasing turbidity and with increasing chlorophyll a concentration. To distinguish the chlorophyll a in turbid waters, the n L w (490) radiances are calculated from n L w (555) considering only the effect of terrigenous turbidity. Then, the n L w (490) SeaWiFS image is compared to the calculated n L w (490), to reveal the 'negative' areas caused by the chlorophyll a and yellow substance absorption.     

Atmospheric correction of ENVISAT/MERIS data over case II waters: the use of black pixel assumption in oxygen and water vapour absorption bands

The Medium Resolution Imaging Spectrometer (MERIS) sensor, with its good physical design, can provide excellent data for water colour monitoring. However, owing to the shortage of shortwave-infrared (SWIR) bands, the traditional near-infrared (NIR)–SWIR algorithm for atmospheric correction in inland turbid case II waters cannot be extended to the MERIS data directly, which limits its applications. In this study, we developed a modified NIR black pixel method for atmospheric correction of MERIS data in inland turbid case II waters. In the new method, two special NIR bands provided by MERIS data, an oxygen absorption band (O₂ A-band, 761 nm) and a water vapour absorption band (vapour A-band, 900 nm), were introduced to keep the assumption of zero water-leaving reflectance valid according to the fact that both atmospheric transmittance and water-leaving reflectance are very small at these two bands. After addressing the aerosol wavelength dependence for the cases of single- and multiple-scattering conditions, we further validated the new method in two case lakes (Lake Dianchi in China and Lake Kasumigaura in Japan) by comparing the results with in situ measurements and other atmospheric correction algorithms, including Self-Contained Atmospheric Parameters Estimation for MERIS data (SCAPE-M) and the Basic ERS (European Remote Sensing Satellite) & ENVISAT (Environmental Satellite) (A)ATSR ((Advanced) Along-Track Scanning Radiometer) and MERIS (BEAM) processor. We found that the proposed method had acceptable accuracy in the bands within 560–754 nm (MERIS bands 5–10) (average absolute deviation (AAD) = 0.0081, average deviation (AD) = 0.0074), which are commonly used in the estimation models of chlorophyll-a (chl-a) concentrations. In addition, the performance of the new method was superior to that of the BEAM processor and only slightly worse than that of SCAPE-M in these bands. Considering its acceptable accuracy and simplicity both in principle and at implementation compared with the SCAPE-M method, the new method provides an option for atmospheric correction of MERIS data in inland turbid case II waters with applications aiming for chl-a estimation.     

Surface chlorophyll a estimation in the Arabian Sea using IRS-P4 Ocean Colour Monitor (OCM) satellite data

The IRS-P4 satellite launched on 26 May 1999 by Indian Space Research Organisation (ISRO) carried an Ocean Colour Monitor (OCM) payload, primarily designed to measure ocean colour, the spectral variations of waterleaving radiance that can be related to the concentration of phytoplankton pigments, coloured dissolved organic matter and suspended particulate matter. Remote sensing data obtained from IRS-P4 OCM sensor is processed for the removal of atmospheric effects of Rayleigh and aerosol scattering to derive normalized water-leaving radiance in visible channels of 412, 443, 490, 512 and 555 nm. Ocean chlorophyll-2 (OC2) global bio-optical algorithm was used to convert normalized water-leaving radiance data to chlorophyll a concentration. For quantitative accuracy assessment, OCM-derived chlorophyll a concentration values were compared to the in situ measurements of chlorophyll a, conducted during ORV Sagar Kanya SK-149c ship cruise during 15-27 November 1999 in Arabian Sea. In general OCM-derived chlorophyll a showed a good correlation ( r 2 =0.90, N = 8, RMS=0.125 mgm -3 ) with measured chlorophyll values.     

Towards a better assessment of the ecological status of coastal waters using satellite-derived chlorophyll-a concentrations

The application of the new Water Framework Directive (WFD) of the European Union will require a dense and frequent monitoring of chlorophyll-a near the coast. Not counting the transitional water bodies located in the vicinity of estuaries, not less than seventy four coastal water bodies have to be monitored along the coast of the French Atlantic continental shelf and the English Channel. All the available data have to be gathered to implement a comprehensive monitoring scheme. To this purpose, we evaluate the capacity of ocean colour imagery to complete the conventional in situ data set collected in coastal networks. Satellite-derived chlorophyll-a concentration is obtained by the application of a coastal Look-Up-Table to water-leaving radiance of the Sea-viewing Wide Field Instrument Sensor (SeaWiFS) for the 1998–2004 period. Seven years of satellite-derived and in situ chlorophyll-a concentrations are compared at seven representative stations of different water bodies. These comparisons show that the satellite products are reliable in most of the situations studied and throughout the seasons. Then the satellite imagery is used to classify the coastal waters following the eutrophication risk criterion of the WFD. This classification is made according to the percentile-90 of chlorophyll-a calculated during the productive season, from March to October. Despite a lack of sensor coverage over a small fraction of the near shore waters, this work shows that the satellite monitoring can considerably ease the application of the WFD.