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Comparison of three SeaWiFS atmospheric correction algorithms for turbid waters using AERONET-OC measurements
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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 Sea WiFS algorithm (Stumpfet 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 lambda = 490 nm and lambda = 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 lambda = 490 nm and lambda = 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 tau(865) and the Angstrom exponent, alpha(510, 865)). Those parameters are retrieved more accurately with the SeaWiFS standard algorithm (relative error of 33\% and 54.15\% for tau(865) and alpha(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. (C) 2011 Elsevier Inc. All rights reserved.
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Optical remote sensing of turbidity and total suspended matter in the Gulf of Gabes
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Optical remote sensing was used to provide scientific information to support environmental management in the Gulf of Gabes that is located in the southeastern coast of Tunisia. This region is characterized by shallow continental shelf subjected to semi-diurnal tides. Industrial activities in this area since the early 1970s may have contributed to the degradation of the biodiversity of the ecosystem with eutrophication problems and disappearance of benthic and planktonic species. To assess the long-term effect of anthropogenic and natural discharges on the Gulf of Gabes, the optical environment of the coastal waters is assessed from in situ measurements of total suspended matter concentration (TSM), Secchi depth and turbidity (TU). This monitoring requires regular seaborne measurements (monthly), which is very expensive and difficult to obtain. The objective of the present study is the evaluation of the Moderate Resolution Imaging Spectrometer (MODIS) AQUA data compared with two sampling campaigns realized at the study area. To map turbidity data from MODIS images, a semi-empirical algorithm was applied at band 667 nm. This bio-optical algorithm has already been calibrated and validated on the Belgian coast. The validation of this algorithm on the Gulf of Gabes using in situ measurements of turbidity and remotely sensed turbidity obtained from MODIS imagery shows a correlation coefficient of 68.9\%. Seasonal and annual average maps for TSM and TU were then computed over the Gulf of Gabes using MODIS imagery. The obtained results of TSM and TU from remotely sensed data are conformable with those obtained through the analysis of in situ measurements. Therefore, remote sensing techniques offer a better and efficient tool for mapping and monitoring turbidity over the whole region.
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Reconstruction of MODIS total suspended matter time series maps by DINEOF and validation with autonomous platform data
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In situ measurements of total suspended matter (TSM) over the period 2003-2006, collected with two autonomous platforms from the Centre for Environment, Fisheries and Aquatic Sciences (Cefas) measuring the optical backscatter (OBS) in the southern North Sea, are used to assess the accuracy of TSM time series extracted from satellite data. Since there are gaps in the remote sensing (RS) data, due mainly to cloud cover, the Data Interpolating Empirical Orthogonal Functions (DINEOF) is used to fill in the TSM time series and build a continuous daily “recoloured” dataset. The RS datasets consist of TSM maps derived from MODIS imagery using the bio-optical model of Nechad et al. (Rem Sens Environ 114: 854-866, 2010). In this study, the DINEOF time series are compared to the in situ OBS measured in moderately to very turbid waters respectively in West Gabbard and Warp Anchorage, in the southern North Sea. The discrepancies between instantaneous RS, DINEOF-filled RS data and Cefas data are analysed in terms of TSM algorithm uncertainties, space-time variability and DINEOF reconstruction uncertainty.
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Mapping total suspended matter from geostationary satellites: a feasibility study with SEVIRI in the Southern North Sea
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Geostationary ocean colour sensors have not yet been launched into space, but are under consideration by a number of space agencies. This study provides a proof of concept for mapping of Total Suspended Matter (TSM) in turbid coastal waters from geostationary platforms with the existing SEVIRI (Spinning Enhanced Visible and InfraRed Imager) meteorological sensor on the METEOSAT Second Generation platform. Data are available in near real time every 15 minutes. SEVIRI lacks sufficient bands for chlorophyll remote sensing but its spectral resolution is sufficient for quantification of Total Suspended Matter (TSM) in turbid waters, using a single broad red band, combined with a suitable near infrared band. A test data set for mapping of TSM in the Southern North Sea was obtained covering 35 consecutive days from June 28 until July 31 2006. Atmospheric correction of SEVIRI images includes corrections for Rayleigh and aerosol scattering, absorption by atmospheric gases and atmospheric transmittances. The aerosol correction uses assumptions on the ratio of marine reflectances and aerosol reflectances in the red and near-infrared bands. A single band TSM retrieval algorithm, calibrated by non-linear regression of seaborne measurements of TSM and marine reflectance was applied. The effect of the above assumptions on the uncertainty of the marine reflectance and TSM products was analysed. Results show that (1) mapping of TSM in the Southern North Sea is feasible with SEVIRI for turbid waters, though with considerable uncertainties in clearer waters, (2) TSM maps are well correlated with TSM maps obtained from MODIS AQUA and (3) during cloud-free days, high frequency dynamics of TSM are detected. (C) 2009 Optical Society of America
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Optimization and quality control of suspended particulate matter concentration measurement using turbidity measurements
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The dry weight concentration of suspended particulate material, [SPM] (units: mg L-1), is measured by passing a known volume of seawater through a preweighed filter and reweighing the filter after drying. This is apparently a simple procedure, but accuracy and precision of [SPM] measurements vary widely depending on the measurement protocol and experience and skills of the person filtering. We show that measurements of turbidity, T (units: FNU), which are low cost, simple, and fast, can be used to optimally set the filtration volume, to detect problems with the mixing of the sample during subsampling, and to quality control [SPM]. A relationship between T and `optimal filtration volume', V opt, is established where V opt is the volume at which enough matter is retained by the filter for precise measurement, but not so much that the filter clogs. This relationship is based on an assessment of procedural uncertainties in the [SPM] measurement protocol, including salt retention, filter preparation, weighing, and handling, and on a value for minimum relative precision for replicates. The effect of filtration volume on the precision of [SPM] measurement is investigated by filtering volumes of seawater ranging between one fifth and twice V opt. It is shown that filtrations at V opt maximize precision and cost effectiveness of [SPM]. Finally, the 90\% prediction bounds of the T versus [SPM] regression allow the quality control of [SPM] determinations. In conclusion it is recommended that existing [SPM] gravimetric measurements be refined to include measurement of turbidity to improve their precision and quality control.
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Variability of Suspended Particulate Matter in the Bohai Sea from the Geostationary Ocean Color Imager (GOCI)
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This study assesses the performance of the Geostationary Ocean Imager (GOCI) for mapping of suspended particulate matter in the Bohai Sea, a turbid water region. GOCI imagery for remote sensing reflectance and Total Suspended Solids (TSS) is analysed in detail for two days in June 2011 (8 images per day). Both instantaneous and daily composite maps are considered and a comparison is made with corresponding reflectance and TSS products from MODIS-AQUA. Results show TSS distributions corresponding to previous studies of the region. The advantage of the higher acquisition frequency (8 images/day instead of 1) offered by GOCI is clearly demonstrated in the daily composite which is more complete during this period of scattered but moving clouds. Consideration of temporal variation over the day indicates low natural variability but some artificial variability from processing errors - this analysis provides a first indication of how the higher frequency of data from geostationary ocean colour could lead to improved data quality control via temporal coherency outlier detection. While there is room for improvement on the GOCI calibration, atmospheric correction and retrieval algorithms, the current study suggests that the GOCI data can already be used now to study qualitatively sediment dynamics except in the extremely turbid waters which are masked out of the current dataset. In a wider context, it is considered that the technical challenges of geostationary ocean colour have been met by the GOCI concept, and, notwithstanding potential improvements on the concept and data processing methods, it is recommended that this mission serve as a model for future geostationary ocean colour sensors over Europe/Africa and the Americas.
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Detection and correction of adjacency effects in hyperspectral airborne data of coastal and inland waters: the use of the near infrared similarity spectrum
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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.
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Synergy between polar-orbiting and geostationary sensors: Remote sensing of the ocean at high spatial and high temporal resolution
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Ocean colour sensors have been capturing the state of the world's oceans for over a decade. They are typically installed on polar-orbiting satellites and cover the entire earth every 1 to 2 days. This temporal resolution is insufficient to observe oceanic processes occurring at a higher frequency, especially when taking cloud cover into account. Data from geostationary platforms can be obtained with a much better temporal resolution (images every 15 or 60 min), and thus are useful to study those processes. We show that by synergistically combining marine reflectance data from SEVIRI, a geostationary sensor, and MODIS Aqua, a polar orbiter, the resulting product is an improvement over both data sources. The synergy approach takes the reflectance from MODIS, with high quality and high spatial resolution, and modulates this over the day by the temporal variability of the SEVIRI reflectance, normalized to the SEVIRI reflectance at the time of MODIS overpass. The temporal frequency of the synergy product is much better than that of MODIS, and by using the latter's high quality data, the limited spatial and radiometric resolution of SEVIRI is enhanced. As the SEVIRI data is limited to a single broad red band (560-710 nm), the applications of the synergy product are limited to parameters that can be derived from this band, such as suspended particulate matter (SPM), turbidity (T) and the diffuse attenuation of photosynthetically available radiation (Kpar) in turbid waters. A geostationary ocean colour sensor over Europe will provide invaluable data concerning our marine environment. The cost of increasing the spatial resolution of a geostationary sensor is very high, and this study illustrates that a lower resolution geostationary ocean colour sensor combined with a high resolution polar orbiting sensor, can provide a high frequency synergetic product with high spatial resolution. (C) 2013 The Authors. Published by Elsevier Inc All rights reserved.
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In situ determination of the remote sensing reflectance: an inter-comparison
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Inter-comparison of data products from simultaneous measurements performed with independent systems and methods is a viable approach to assess the consistency of data and additionally to investigate uncertainties. Within such a context the inter-comparison called Assessment of In Situ Radiometric Capabilities for Coastal Water Remote Sensing Applications (ARC) was carried out at the Acqua Alta Oceanographic Tower in the northern Adriatic Sea to explore the accuracy of in situ data products from various in- and above-water optical systems and methods. Measurements were performed under almost ideal conditions, including a stable deployment platform, clear sky, relatively low sun zenith angles and moderately low sea state. Additionally, all optical sensors involved in the experiment were inter-calibrated through absolute radiometric calibration performed with the same standards and methods. Inter-compared data products include spectral waterleaving radiance L-w(lambda), above-water downward irradiance E-d(0(+),lambda) and remote sensing reflectance R-rs(lambda). Data products from the various measurement systems/methods were directly compared to those from a single reference system/method. Results for R-rs(lambda) indicate spectrally averaged values of relative differences comprised between - 1 and +6 \%, while spectrally averaged values of absolute differences vary from approximately 6\% for the above-water systems/methods to 9 \% for buoy-based systems/methods. The agreement between R-rs(lambda) spectral relative differences and estimates of combined uncertainties of the inter-compared systems/methods is noteworthy.
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A model study of the Rhine discharge front and downwelling circulation
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