Author
David Doxaran
Other affiliations: Pierre-and-Marie-Curie University, University of Paris
Bio: David Doxaran is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Ocean color & Colored dissolved organic matter. The author has an hindex of 27, co-authored 66 publications receiving 2431 citations. Previous affiliations of David Doxaran include Pierre-and-Marie-Curie University & University of Paris.
Papers published on a yearly basis
Papers
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University of Perpignan1, Pierre-and-Marie-Curie University2, Centre national de la recherche scientifique3, IFREMER4, University of Toulouse5, Université Paul Cézanne Aix-Marseille III6, University of Montpellier7, Stazione Zoologica Anton Dohrn8, Spanish National Research Council9, Institut de radioprotection et de sûreté nucléaire10, University of Nice Sophia Antipolis11, University College West12, École Normale Supérieure13, University of Georgia14, Plymouth Marine Laboratory15, university of lille16
TL;DR: In this article, a review of current functioning and responses of Mediterranean marine biogeochemical cycles and ecosystems with respect to key natural and anthropogenic drivers and to consider the ecosystems' responses to likely changes in physical, chemical and socio-economical forcings induced by global change and by growing anthropogenic pressure at the regional scale.
391 citations
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TL;DR: In this paper, a semi-empirical single-band turbidity retrieval algorithm using the near infrared (NIR) band at 859 nm in highly turbid waters is assessed.
290 citations
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TL;DR: In this article, field and satellite measurements of surface water turbidity were combined in order to study the dynamics of the turbidity maximum zone (TM) in a macrotidal estuary (the Gironde, France).
Abstract: Over a 1-year period, field and satellite measurements of surface water turbidity were combined in order to study the dynamics of the turbidity maximum zone (TM) in a macrotidal estuary (the Gironde, France). Four fixed platforms equipped with turbidity sensors calibrated to give the suspended particulate matter (SPM) concentration provided continuous information in the upper estuary. Full resolution data recorded by the moderate resolution imaging spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellite platforms provided information in the central and lower estuary twice a day (depending on cloud cover). Field data were used to validate a recently developed SPM quantification algorithm applied to the MODIS ‘surface reflectance’ product. The algorithm is based on a relationship between the SPM concentration and a reflectance ratio of MODIS bands 2 (near-infrared) and 1 (red). Based on 62 and 75 match-ups identified in 2005 with MODIS Terra and Aqua data, the relative uncertainty of the algorithm applied to these sensors was found to be 22 and 18%, respectively. Field measurements showed the tidal variations of turbidity in the upper estuary, while monthly-averaged MODIS satellite data complemented by field data allowed observing the monthly movements of the TM in the whole estuary. The trapping of fine sediments occurred in the upper estuary during the period of low river flow. This resulted in the formation of a highly concentrated TM during a 4-month period. With increasing river flow, the TM moved rapidly to the central estuary. A part of the TM detached, moved progressively in the lower estuary and was finally either massively exported to the ocean during peak floods or temporary trapped (settled) on intertidal mudflats. The massive export to the ocean was apparently the result of combined favorable environmental conditions: presence of fluid mud near the mouth, high river flow, high tides and limited wind speeds. The mean SPM concentration within surface waters of the whole estuary showed strong seasonal variations but remained almost unchanged on a 1-year-basis. These observations suggest that the masses of suspended sediments exported toward the ocean and supplied by the rivers were almost equivalent during the year investigated (2005). Results show the usefulness of information extracted from combined field and current ocean color satellite data in order to monitor the transport of suspended particles in coastal and estuarine waters.
280 citations
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30 Mar 2010TL;DR: In this paper, regional empirical algorithms based on in-situ data were tested to retrieve the concentration of total suspended matter and turbidity from the remote sensing reflectance, and the respective sensitivity of MODIS surface reflectance bands 1 and 2 for water quality application was investigated as well as the quality of atmospheric corrections.
Abstract: The Basque coastal waters (South Bay of Biscay) are directly influenced by the Adour River freshwater plume. The Adour outflow leads to important variations of suspended matter concentrations and turbidity, which in turn may affect biological productivity and water quality. This study aims at both developing specific algorithms and testing the efficiency of atmospherically corrected MODIS-Aqua 250-m surface reflectance product (MYD09) to map total suspended matter concentrations and turbidity within the Adour coastal region. First, regional empirical algorithms based on in-situ data were tested to retrieve the concentration of total suspended matter and turbidity from the remote sensing reflectance. Then, the respective sensitivity of MODIS surface reflectance bands 1 and 2 for water quality application was investigated as well as the quality of atmospheric corrections. Finally, selected algorithms were applied to the MYD09 product. The resulting 250-m resolution maps were then compared to 1000-m maps produced by IFREMER and comparisons between satellite measurements and in-situ sampling points were performed. Results show that MODIS-Aqua band 1 (620–670 nm) is appropriate for predicting turbidity and total suspended matter concentrations using polynomial regression models, whilst band 2 is unadapted. Comparison between total suspended matter concentration 250-m resolution maps and mineral suspended matter 1000-m maps (generated by IFREMER) produced consistent results. A high correlation was obtained between turbidity measured in-situ and turbidity retrieved from MODIS-Aqua satellite data.
224 citations
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TL;DR: The multi-sensor approach together with the multi-conditional algorithm presented here can be applied to the latest generation of ocean color sensors to study SPM dynamics in the coastal ocean at higher spatial and temporal resolutions.
Abstract: The accurate measurement of suspended particulate matter (SPM) concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM spatio-temporal variability in coastal waters. However, near-shore satellite images are complex to correct for atmospheric effects due to the proximity of land and to the high level of reflectance caused by high SPM concentrations in the visible and near-infrared spectral regions. The water reflectance signal (ρw) tends to saturate at short visible wavelengths when the SPM concentration increases. Using a comprehensive dataset of high-resolution satellite imagery and in situ SPM and water reflectance data, this study presents (i) an assessment of existing atmospheric correction (AC) algorithms developed for turbid coastal waters; and (ii) a switching method that automatically selects the most sensitive SPM vs. ρw relationship, to avoid saturation effects when computing the SPM concentration. The approach is applied to satellite data acquired by three medium-high spatial resolution sensors (Landsat-8/Operational Land Imager, National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite and Aqua/Moderate Resolution Imaging Spectrometer) to map the SPM concentration in some of the most turbid areas of the European coastal ocean, namely the Gironde and Loire estuaries as well as Bourgneuf Bay on the French Atlantic coast. For all three sensors, AC methods based on the use of short-wave infrared (SWIR) spectral bands were tested, and the consistency of the retrieved water reflectance was examined along transects from low- to high-turbidity waters. For OLI data, we also compared a SWIR-based AC (ACOLITE) with a method based on multi-temporal analyses of atmospheric constituents (MACCS). For the selected scenes, the ACOLITE-MACCS difference was lower than 7%. Despite some inaccuracies in ρw retrieval, we demonstrate that the SPM concentration can be reliably estimated using OLI, MODIS and VIIRS, regardless of their differences in spatial and spectral resolutions. Match-ups between the OLI-derived SPM concentration and autonomous field measurements from the Loire and Gironde estuaries’ monitoring networks provided satisfactory results. The multi-sensor approach together with the multi-conditional algorithm presented here can be applied to the latest generation of ocean color sensors (namely Sentinel2/MSI and Sentinel3/OLCI) to study SPM dynamics in the coastal ocean at higher spatial and temporal resolutions.
112 citations
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2,261 citations
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1,327 citations
01 Apr 1994
TL;DR: In this paper, seven models for computing underwater radiances and irradiances by numerical solution of the radiative transfer equation are compared and applied to the solution of several problems drawn from optical oceanography.
Abstract: Seven models for computing underwater radiances and irradiances by numerical solution of the radiative transfer equation are compared. The models are applied to the solution of several problems drawn from optical oceanography. The problems include highly absorbing and highly scattering waters, scattering by molecules and by particulates, stratified water, atmospheric effects, surface-wave effects, bottom effects, and Raman scattering. The models provide consistent output, with errors (resulting from Monte Carlo statistical fluctuations) in computed irradiances that are seldom larger, and are usually smaller, than the experimental errors made in measuring irradiances when using current oceanographic instrumentation. Computed radiances display somewhat larger errors.
418 citations
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TL;DR: In this article, a thorough review of empirical algorithms for quantitatively estimating a variety of parameters from space-borne, airborne and in situ remote sensors in inland and transitional waters, including chlorophyll-a, total suspended solids, Secchi disk depth (z SD), turbidity, absorption by coloured dissolved organic matter (a CDOM) and other parameters, for example, phycocyanin, is given.
Abstract: The empirical approach of remote sensing has a proven capability to provide timely and accurate information on inland and near-coastal transitional waters. This article gives a thorough review of empirical algorithms for quantitatively estimating a variety of parameters from space-borne, airborne and in situ remote sensors in inland and transitional waters, including chlorophyll-a, total suspended solids, Secchi disk depth (z SD), turbidity, absorption by coloured dissolved organic matter (a CDOM) and other parameters, for example, phycocyanin. Current remote-sensing instruments are also reviewed. The theoretical basis of the empirical algorithms is given using fundamental bio-optical theory of the inherent optical properties (IOPs). Bands, band ratios and band arithmetic algorithms that could be used to produce common biogeophysical products for inland/transitional waters are identified. The article discusses the potential role that empirical algorithms could play alongside more advanced model-based algo...
391 citations