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.     

Evaluation of four MERIS atmospheric correction algorithms in Lake Kasumigaura,Japan

Accurate atmospheric correction for turbid inland waters remains a significant challenge. Several atmospheric correction algorithms have been proposed to address this issue, but their performance is unclear in regard to Asian lakes, some of which have extremely high turbidity and different inherent optical properties from lakes in other continents. Here, four existing atmospheric correction algorithms were tested in Lake Kasumigaura, Japan (an extremely turbid inland lake), using in situ water-leaving reflectance and concurrently acquired medium resolution imaging spectrometer (MERIS) images. The four algorithms are (1) GWI (the standard Gordon and Wang algorithm with an iterative process and a bio-optical model) (2) MUMM (Management Unit of the North Sea Mathematical Models); (3) SCAPE-M (Self-Contained Atmospheric Parameters Estimation for MERIS Data) and (4) C2WP (Case-2 Water Processor). The results show that all four atmospheric correction algorithms have limitations in Lake Kasumigaura, even though SCAPE-M and MUMM gave acceptable accuracy for atmospheric correction in several cases (relative errors less than 30% for the 2006 and 2008 images). The poor performance occurred because the conditions in Lake Kasumigaura (i.e. the atmospheric state and/or turbidity) did not always meet the assumptions in each atmospheric correction algorithm (e.g. in 2010, the relative errors ranged from 42% to 83%). These results indicate that further improvements are necessary to address the issue of atmospheric correction for turbid inland waters such as Lake Kasumigaura, Japan.     

Coupled retrieval of aerosol optical thickness, columnar water vapor and surface reflectance maps from ENVISAT/MERIS data over land

An algorithm for the derivation of atmospheric parameters and surface reflectance data from MEdium Resolution Imaging Specrometer Instrument (MERIS) on board ENVIronmental SATellite (ENVISAT) images has been developed. Geo-rectified aerosol optical thickness (AOT), columnar water vapor (CWV) and spectral surface reflectance maps are generated from MERIS Level-1b data over land. The algorithm has been implemented so that AOT, CWV and reflectance products are provided on an operational manner, making no use of ancillary parameters apart from those attached to MERIS products. For this reason, it has been named Self-Contained Atmospheric Parameters Estimation from MERIS data (SCAPE-M). The fundamental basis of the algorithm and applicable error figures are presented in the first part of this paper. In particular, errors of ± 0.03, ± 4% and ± 8% have been estimated for AOT, CWV and surface reflectance retrievals, respectively, by means of a sensitivity analysis based on a synthetic data set simulated under a usual MERIS scene configuration over land targets. The assumption of a fixed aerosol model, the coarse spatial resolution of the AOT product and the neglection of surface reflectance directional effects were also identified as limitations of SCAPE-M. Validation results are detailed in the second part of the paper. Comparison of SCAPE-M AOT retrievals with data from AErosol RObotic NETwork (AERONET) stations showed an average Root Mean Square Error (RMSE) of 0.05, and an average correlation coefficient R² of about 0.7-0.8. R² values grew up to more than 0.9 in the case of CWV after comparison with the same stations. A good correlation is also found with the MERIS Level-2 ESA CWV product. Retrieved surface reflectance maps have been successfully compared with reflectance data derived from the Compact High Resolution Imaging Spectrometer (CHRIS) on board the PRoject for On-Board Autonomy (PROBA) in the first place. Reflectance retrievals have also been compared with reflectance data derived from MERIS images by the Bremen AErosol Retrieval (BAER) method. A good correlation in the red and near-infrared bands was found, although a considerably higher proportion of pixels was successfully processed by SCAPE-M.     

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.     

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.     

OCEANcode: The complete set of algorithms and models for the level_2 processing of European CZCS historical data

A complete set of algorithms and models for the level_2 processing of the European CZCS historical data was integrated in the OCEANcode software package. The OCEANcode allows the calibration of the sensor-recorded signal taking into account the instrument sensitivity loss; the correction of the calibrated signal for atmospheric contamination and derive sub-surface reflectances; and then the estimation of the concentration of water constituents. The atmospheric correction is performed on the basis of a reflectance-model-based algorithm. The Rayleigh correction is applied consistently for all water pixels, using a multiple scattering approach, and introducing atmospheric pressure and Ozone concentration data in the computation. The marine aerosol correction uses a pixel-by-pixel iterative procedure, allowing successive estimates of both the marine reflectance in the red spectral region (670nm) and the Angstrom exponent, which links simple wavelengths ratios to reflectance ratios. For case 1 waters, the optical properties of which are essentially dominated by planktonic pigments, the interrelations between marine reflectances and reflectance ratios at various wavelengths are derived from modelled calculations. For identified case 2 waters, where water constituents other than planktonic pigments (i.e. dissolved organics and suspended sediments) dominate the water optical properties, the evaluation of marine reflectances is approximated by means of interpolated Angstrom exponent values computed over case 1 water pixels and of empirical relationships derived from in situ measurements. The computation of chlorophyll-like pigments is performed with algorithms based on blue/green (443-550nm) reflectance ratios, for lower pigment concentration, or on green/green (520-550nm) reflectance ratios, for higher pigment concentration. As for the case of atmospheric corrections, the inter-relations between pigment concentration and reflectance ratios are model-derived for case 1 waters, and empirically determined for case 2 waters.     

Spectral optimization for constituent retrieval in Case 2 waters II: Validation study in the Chesapeake Bay

Coastal waters (Case 2) are generally more optically complex than oceanic waters and contain much higher quantities of colored detrital matter (CDM, a combination of dissolved organic matter and detrital particulates) as well as suspended sediment. Exclusion of CDM in the retrieval can lead to an overestimation of chlorophyll a concentration (C). We present a validation of a Case 2 version of the coupled spectral optimization algorithm (SOA) for simultaneous atmospheric correction and water parameter retrieval using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite ocean color data. Modeling of water constituents uses the Garver, Siegel and Maritorena (GSM) semi-analytic bio-optical model locally tuned for Chesapeake Bay. This includes a parameterization for CDM through its absorption spectrum.SOA-retrieved C and CDM are compared with in situ measurements in Chesapeake Bay. Results are also compared with output from two alternate models 1) the standard algorithm (Std) and 2) the standard atmospheric correction combined with the locally tuned GSM model (StdGSM). The comparisons indicate that the SOA is a viable alternative to both given models in Chesapeake Bay. In contrast, StdGSM appears to require improvement before it can be considered for operational use in these waters. Perhaps the most important result is the high-quality of CDM retrievals with the SOA. They suggest that there is value added using the SOA method in Chesapeake waters, as the Std method does not retrieve CDM. In a companion paper we describe in detail the model implementation, and its accuracy and limitations when applied to the Chesapeake Bay.     

A simple correction method for the MODIS surface reflectance product over typical inland waters in China

The Moderate Resolution Imaging Spectroradiometer (MODIS) has the advantage of providing continuous, global, near-daily spatial measurements, and has greatly aided in understanding physical, optical, and biological processes in the global ocean biosphere. However, little research has been implemented for the remote-sensing monitoring of global inland waters. One important factor is that there is no operational atmospheric correction method designed for global inland waters. The MODIS surface reflectance product (MOD09) provides surface reflectance data for land at the global scale, but it does not offer accurate atmospheric correction over inland waters because of the constraints of its primary correction algorithm. The purpose of this article is to provide a simple and operational correction method for the MOD09 product to retrieve the water-leaving reflectance for large inland waters larger than 25 km². The correction method is based on an analysis of additive noises in MOD09 data over inland waters and on the adoption of two assumptions. Field-measured data collected in three typical inland waters in China were used to assess the performance of the correction method to ensure its applicability for waters in different conditions. The results show acceptable agreement with field data over the three inland waterbodies, with a mean relative error of 17.1% in visible bands. Our study demonstrates that the MOD09 correction method is moderately accurate when compared with the optimal method for specific waterbodies, but it has the potential for use in operational data-processing systems to derive water-leaving reflectance data from MOD09 data over inland waters in a variety of conditions and large regions.     

Spectral optimization for constituent retrieval in Case 2 waters I: Implementation and performance

We describe in detail the implementation of the spectral optimization algorithm (SOA) for Case 2 waters for processing of ocean color data. This algorithm uses aerosol models and a bio-optical reflectance model to provide the top-of atmosphere (TOA) reflectance. The parameters of both models are then determined by fitting the modeled TOA reflectance to that observed from space, using non-linear optimization. The algorithm will be incorporated into the SeaDAS software package as an optional processing switch of the Multi-Sensor Level-1 to Level-2 code. To provide potential users with an understanding of the accuracy and limitations of the algorithm, we generated a synthetic data set and tested the performance of the SOA with both correct and incorrect bio-optical model parameters. Application of the SOA to actual SeaWiFS data in the Lower Chesapeake Bay (for which surface measurements were available) showed that 20% errors in the bio-optical model parameters still enabled retrieval of chlorophyll a and the total absorption coefficient of dissolved plus particulate detrital material at 443 nm with an error of less than 30% and 20%, respectively. In a companion paper we present a validation study of the application of the algorithm in the Chesapeake Bay.     

Comparison of atmospheric correction algorithms for TM image in inland waters

In order to extract quantitative water‐leaving information from the Thematic Mapper (TM) image accurately in inland waters, atmospheric correction is a necessary step. Based on former researchers' results, the paper presents two atmospheric correction algorithms based on meteorological data (MD) and on Moderate Resolution Imaging Spectroradiometer (MODIS) Vicarious Calibration (MVC) for TM image in inland waters according to the theory of radiative transfer. Studying Taihu lake, China, in this paper we derived water remote sensing reflectance from a TM image of 26 July 2004 by these two atmospheric correction algorithms and we compare the results with that of dark object subtraction (DOS) and 6S code. The results show that the effect of atmospheric correction based on meteorological data and MODIS Vicarious Calibration is much better than that of DOS and 6S code. Although the MD is more accurate, MVC may be an ideal choice for TM images in inland water because TERRA MODIS images can be acquired easily than collecting meteorological data at the time of satellites passing over.     

Atmospheric correction algorithm for MERIS above case‐2 waters

The development and validation of an atmospheric correction algorithm designed for the Medium Resolution Imaging Spectrometer (MERIS) with special emphasis on case‐2 waters is described. The algorithm is based on inverse modelling of radiative transfer (RT) calculations using artificial neural network (ANN) techniques. The presented correction scheme is implemented as a direct inversion of spectral top‐of‐atmosphere (TOA) radiances into spectral remote sensing reflectances at the bottom‐of‐atmosphere (BOA), with additional output of the aerosol optical thickness (AOT) at four wavelengths for validation purposes. The inversion algorithm was applied to 13 MERIS Level1b data tracks of 2002–2003, covering the optically complex waters of the North and Baltic Sea region. A validation of the retrieved AOTs was performed with coincident in situ automatic sun–sky scanning radiometer measurements of the Aerosol Robotic Network (AERONET) from Helgoland Island located in the German Bight. The accuracy of the derived reflectances was validated with concurrent ship‐borne reflectance measurements of the SIMBADA hand‐held field radiometer. Compared to the MERIS Level2 standard reflectance product generated by the processor versions 3.55, 4.06 and 6.3, the results of the proposed algorithm show a significant improvement in accuracy, especially in the blue part of the spectrum, where the MERIS Level2 reflectances result in errors up to 122% compared to only 19% with the proposed algorithm. The overall mean errors within the spectral range of 412.5–708.75 nm are calculated to be 46.2% and 18.9% for the MERIS Level2 product and the presented algorithm, respectively.     

Assessment of water quality in Lake Garda (Italy) using Hyperion

For testing the integration of the remote sensing related technologies into the water quality monitoring programs of Lake Garda (the largest Italian lake), the spatial and spectral resolutions of Hyperion and the capability of physics-based approaches were considered highly suitable. Hyperion data were acquired on 22nd July 2003 and water quality was assessed (i) defining a bio-optical model, (ii) converting the Hyperion at-sensor radiances into subsurface irradiance reflectances, and (iii) adopting a bio-optical model inversion technique. The bio-optical model was parameterised using specific inherent optical properties of the lake and light field variables derived from a radiative transfer numerical model. A MODTRAN-based atmospheric correction code, complemented with an air/water interface correction was used to convert Hyperion at-sensor radiances into subsurface irradiance reflectance values. These reflectance values were comparable to in situ reflectance spectra measured during the Hyperion overpass, except at longer wavelengths (beyond 700 nm), where reflectance values were contaminated by severe atmospheric adjacency effects. Chlorophyll-a and tripton concentrations were retrieved by inverting two Hyperion bands selected using a sensitivity analysis applied to the bio-optical model. The sensitivity analysis indicated that the assessment of coloured dissolved organic matter was not achievable in this study due to the limited coloured dissolved organic matter concentration range of the lake, resulting in reflectance differences below the environmental measurement noise of Hyperion. The chlorophyll-a and tripton image-products were compared to in situ data collected during the Hyperion overpass, both by traditional sampling techniques (8 points) and by continuous flow-through systems (32 km). For chlorophyll-a the correlation coefficient between in situ point stations and Hyperion-inferred concentrations was 0.77 (data range from 1.30 to 2.16 mg m^− 3). The Hyperion-derived chlorophyll-a concentrations also match most of the flow-through transect data. For tripton, the validation was constrained by variable re-suspension phenomena. The correlation coefficient between in situ point stations and Hyperion-derived concentrations increased from 0.48 to 0.75 (data range from 0.95 to 2.13 g m^− 3) if the sampling data from the re-suspension zone was avoided. The comparison of Hyperion-derived tripton concentrations and flow-through transect data exhibited a similar mismatch. The results of this research suggest further studies to address compatibilities of validation methods for water body features with a high rate of change, and to reduce the contamination by atmospheric adjacency effects on Hyperion data at longer wavelengths in Alpine environment. The transferability of the presented method to other sensors and the ability to assess water quality independent from in situ water quality data, suggest that management relevant applications for Lake Garda (and other subalpine lakes) could be supported by remote sensing.     

MERIS atmospheric correction over coastal waters: validation of the MERIS aerosol models using AERONET

Standard aerosol models (SAMs) are used for the Medium-Resolution Imaging Spectrometer (MERIS) level-2 processing over water, first to remotely sense the aerosols in the near-infrared and secondly to perform the atmospheric correction for ocean colour analysis. However, are these SAMs still suitable over coastal areas? The present work was intended to answer that question through the use of the Aerosol Robotic Network (AERONET) by selecting CIMEL radiometers operating over the sea surface or near the coastline. The current official MERIS algorithm overestimates aerosol optical thickness (AOT) over coastal waters at 865 nm. This can be related either to incorrect assumptions of the underlying surface assumption or to the assumptions of the aerosol properties (e.g. phase function). This study looks at the importance of aerosol modelling and confirms that the improved aerosol models must be used in the retrieval chain. Extinction measurements were first used to derive the aerosol optical thicknesses (AOTs). The spectral dependency of the AOTs between 670 nm and 865 nm allowed the selection of a standard aerosol model. The ability of the standard aerosol models to retrieve the AOTs at 440 nm was then analysed as a key element in the extrapolation of the aerosol path radiance from the near-infrared to the blue spectral range. The two outputs of this analysis are systematic biases in this retrieval process and accordingly they are an estimation of the dispersion. The first output can be defined as a corrective factor in the aerosol path radiance at 440 nm and the second output can be used for error analysis. A radiative transfer code was used to simulate the sky radiance in the principal plane of acquisition. Comparisons at 870 nm illustrated the ability of the standard aerosol models to retrieve the aerosol path radiances with a direct impact on the AOT retrieval from satellite observations at 865 nm.     

The sensitivity of MERIS atmospheric correction over water to aerosol climatology

Performing a classical atmospheric correction over water requires a well-defined climatology representative of the aerosols encountered in the remote areas of oceans. Different climatologies built up at the global scale are candidates to be implemented, as an auxiliary data file (ADF) including look-up tables (LUTs) with radiative properties of the aerosols, in a traditional atmospheric correction algorithm. In addition to these, two regional climatologies were developed in the 2-Seas region, comprising both the Eastern English Channel and the North Sea, and at the Acqua Alta Oceanographic Tower (AAOT) in the Adriatic Sea. By using the optical data processor of the European Space Agency (ODESA), Medium Resolution Imaging Spectrometer (MERIS) level-1 (L1) data extracted from the MERis MAtchup In-situ Database (MERMAID) were processed to obtain the level-2 (L2) products over water. For a given climatology, a full processing chain was developed to generate the MERIS aerosol LUTs suitable to ODESA. The final step consisted of an analysis of the L2 products, for both the aerosols and marine reflectance, in the framework of the evaluation of the performance of each climatology in atmospheric correction over oceans. Finally, we recommend using the regional aerosol climatologies available from the AErosol RObotic NETwork (AERONET) database, at least for the retrieval of the L2 aerosol product. In regard to marine reflectance, this remains more challenging and needs a more extensive analysis.     

Detection and correction of adjacency effects in hyperspectral airborne data of coastal and inland waters: the use of the near infrared similarity spectrum

A method for the detection and correction of water pixels affected by adjacency effects is presented. The approach is based on the comparison of spectra with the near infrared (NIR) similarity spectrum. Pixels affected by adjacency effects have a water-leaving reflectance spectrum with a different shape to the reference spectrum. This deviation from the similarity spectrum is used as a measure for the adjacency effect. Secondly, the correspondence with the NIR similarity spectrum is used to quantify and to correct for the contribution of the background radiance during atmospheric correction. The advantage of the approach is that it requires no a priori assumptions on the sediment load or related reflectance values in the NIR and can therefore be applied to turbid waters. The approach is tested on hyperspectral airborne data (Compact Airborne Spectrographic Imager (CASI), Airborne Hyperspectral Scanner (AHS)) acquired above coastal and inland waters at different flight altitudes and under varying atmospheric conditions. As the NIR similarity spectrum forms the basis of the approach, the method will fail for water bodies for which this similarity spectrum is no longer valid.     

Measurements and analysis of in situ multi-angle reflectance of turbid inland water: a case study in Meiliang Bay,Taihu Lake,China

The bidirectional reflectance properties of the anisotropic light field above the water surface are important for a range of applications. The bidirectional reflectance distribution function of oceanic waters has been well characterized but there is a lack of information for turbid inland waters. In addition, there is a lack of bidirectional reflectance data measured in turbid inland waters partially due to the difficulty in collecting in situ water-surface multi-angle remote-sensing reflectance data. To facilitate bidirectional reflectance studies of turbid inland waters using in situ multi-angular reflectance data, we have designed and developed a simple hand-held 3D positioning pole to position the spectrometer optical fibre probe and a specific method to collect the multi-angular reflectance data above the water surface with this pole. Using this device, we collected multi-angular reflectance data in Meiliang Bay, Taihu Lake, China, and analysed the uncertainties in this method. We analysed the bidirectional distribution characteristics of the data, and compared the findings to those in the literature. Both uncertainty analysis and bidirectional distribution characteristics analysis showed that our method is effective in collecting multi-angular reflectance above the water surface and can be applied to validate bidirectional correction models in the future.     

Modeling spectral reflectance of optically complex waters using bio-optical measurements from Tokyo Bay

This study presents an approach for optimally parameterizing a reflectance model. A parameterization scheme is realized based on a comprehensive bio-optical data set, including subsurface downwelling and upwelling irradiance spectra, absorption spectra of particle and dissolved substances, as well as chlorophyll and total suspended matter concentrations at 45 stations near Tokyo Bay between 1982 and 1984. The irradiance reflectance model is implemented with three-component inherent optical property submodels.In this parameterization scheme, an unsupervised classification was applied in the hyper-spectral space of reflectance, leading to three spectrally distinct optical water types. The reflectance model was parameterized for the entire data set, and then parameterized for each of the water types. The three sets of type-specific model parameters, which define corresponding IOP submodels, are believed to accommodate differences in the optical properties of the in-water constituents. The parameterized reflectance model was evaluated by both reconstructing measured reflectance spectra and solving for the nonlinear inverse problem to retrieve in-water constituent concentrations. The model accuracy was significantly improved in the forward direction for classified waters over that of non-classified waters, but no significant improvement was achieved in the retrieval accuracy (inverse direction). A larger data set with greater resolution of constituent inherent optical properties would likely improve the modeling results.     

MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes

Chlorophyll-a (Chla) concentrations and ‘water-leaving’ reflectance were assessed along transects in Keweenaw Bay (Lake Superior) and in Green Bay (Lake Michigan) (two of the Laurentian Great Lakes, USA), featuring oligotrophic (0.4–0.8 mg Chla m^? 3) and eutrophic to hyper-eutrophic waters (11–131 mg Chla m^? 3), respectively. A red-to-NIR band Chla retrieval algorithm proved to be applicable to Green Bay, but gave mostly negative values for Keweenaw Bay. An alternative algorithm could be based on Chla fluorescence, which in Keweenaw Bay was indicated by enhanced reflectance near 680 nm. Bands 7, 8 and 9 of the Medium Resolution Imaging Spectrometer (MERIS) have been specifically designed to detect phytoplankton fluorescence in coastal waters. A quite strong linear relationship was found between Chla concentration and fluorescence line height (FLH) computed with these MERIS bands. The same relationship held for observations on oligotrophic waters elsewhere, but not for Green Bay, where the FLH diminished to become negative as Chla increased. The remote sensing application of the algorithms could be tested because a MERIS scene was acquired coinciding with the day of the field observations in Keweenaw Bay and one day after those in Green Bay. For Green Bay the pixel values from the red-to-NIR band algorithm compared well to the steep Chla gradient in situ. This result is very positive from the perspective of satellite use in monitoring eutrophic inland and coastal waters in many parts of the world. Implementation of the FLH relationship in the scene of Keweenaw Bay produced highly variable pixel values. The FLH in oligotrophic inland waters like Lake Superior appears to be very close to or below the MERIS detection limit. An empirical algorithm incorporating three MERIS bands in the blue-to-green spectral region might be used as an alternative, but its applicability to other regions and seasons remains to be verified. Moreover, none of the algorithms will be suitable for mesotrophic water bodies. The results indicate that Chla mapping in oligotrophic and mesotrophic areas of the Great Lakes remains problematic for the current generation of satellite sensors.     

Validation of chlorophyll-α concentration maps from Aqua MODIS over the Gulf of Gabes (Tunisia): comparison between MedOC3 and OC3M bio-optical algorithms

Few studies have focused on the use of ocean colour remote sensors in the Gulf of Gabes (southeastern Tunisia). This work is the first study to evaluate the ocean colour chlorophyll-a product in this area. Chlorophyll-a concentrations were measured during oceanographic cruises performed off the Gulf of Gabes. These measurements were used to validate satellite data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite. First, two atmospheric correction procedures (standard and shortwave infrared) were tested to derive the remote-sensing reflectance, and then a comparison between two bio-optical (OC3M and MedOC3) algorithms were realized using the in situ measurements. Both atmospheric correction procedures gave similar results when applied to our study area indicating that most pixels were non-turbid. The comparison between bio-optical algorithms shows that using the regional bio-optical algorithm MedOC3 improves chlorophyll-a estimation in the Gulf of Gabes for the low values of this parameter.