Search publications of the members of the Royal Belgian institute of natural Sciences
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Generalized satellite image processing: eight years of ocean colour data for any region on earth
- During the past decade, the world's oceans have been systematically observed by orbiting spectroradiometers such as MODIS and MERIS. These sensors have generated a huge amount of data with unprecedented temporal and spatial coverage. The data is freely available, but not always accessible for marine researchers with no image processing experience. In order to provide historical and current oceanographic parameters for the jellyfish forecasting in the JELLYFOR project, a tool for the generalized processing and archiving of satellite data was created (GRIMAS). Using this generalized software, the large amount of remote sensing data can be accessed, and parameters such as chlorophyll a concentration (CHL), sea surface temperature (SST) and total suspended matter concentration (TSM) can be extracted and gridded for any region on earth. Time-series and climatologies can be easily extracted from this data archive. The products generated can be based on the standard products, as supplied by space agencies, or can be new or regionally calibrated products. All available MODIS and MERIS L2 images from an eight year period (2003-2010) were processed in order to create a gridded dataset of CHL, SST (MODIS only) and of TSM for the three JELLYFOR regions. For two of the regions, data for an extended region was also processed. Multi-year composites (climatologies) of satellite data and time-series can provide a wealth of information for different projects in any region. Climatologies from the two sensors are in good agreement, while significant differences can occur on a scene per scene basis. Total suspended matter concentrations match favourably with in situ data derived from sensors on autonomous buoys. MODIS sea surface temperature corresponds closely to temperature continuously measured underway on research vessels.
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In situ determination of the remote sensing reflectance: an inter-comparison
- 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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Variability of the inherent and apparent optical properties in a highly turbid coastal area: impact for the calibration of remote sensing algorithms
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Estimating PCO2 from remote sensing in the Belgian Coastal Zone.
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Net ecosystem production and carbon dioxide fluxes in the Scheldt estuarine plume
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Optical remote sensing in support of eutrophication monitoring in the Southern North Sea
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A generalised vertical coordinate for 3D marine models
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Calibration and validation of an algorithm for remote sensing of turbidity over La Plata River estuary, Argentina
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Improving water reflectance retrieval from MODIS imagery in the highly turbid waters of La Plata River
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Visible and near infrared spectral variations of light backscattering by hydrosols
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SIMEC, an environmental correction for MERIS based on the NIR similarity spectrum
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Modelling the relative impact of the rivers Scheldt, Rhine, Meuse and Seine on the availability of nutrients in Belgian waters (Southern North Sea) using the 3D coupled physical-biological model MIRO&CO-3D.
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Spatial and interannual variability of the spring phytoplankton bloom in the North Sea investigated by modelling and remote sensing
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ERS-1 Synthetic Aperture Radar imagery of the Rhine-Muese plume discharge front - preliminary results
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Suspended Particulate Matter (SPM) mapping from MERIS imagery. Calibration of a regional algorithm for the Belgian coastal waters
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Remote sensing of the diffuse attenuation coefficient and related parameters in turbid waters: state of the art and future perspectives
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Calibration and validation of a generic multisensor algorithm for mapping of turbidity in coastal waters
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Optical remote sensing of coastal waters from geostationary platforms: a feasibility study
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Diurnal variability of suspended matter from the SEVIRI geostationary sensor and validation with high frequency in situ data
