0000000001285648

AUTHOR

Audrey Minghelli-roman

showing 14 related works from this author

Image simulation of geostationary sensor dedicated to ocean color

2010

A method of image simulation of geostationary sensor dedicated to ocean color for open water (case1) and coastal water (case2) is presented in this paper. This method uses HYDROLIGHT to model the radiative transfer in order to obtain the water surface radiance. MeRIS level 3 products have been used for input water components to provide a realistic spatial distribution. The atmospheric radiative transfer model and the sensor model finely lead to satellite remote sensing images. This system allows to evaluate the dynamic range of BOA and TOA radiances depending on solar and viewing angles in operational situation and latter their influence on water composition retrieval.

Atmospheric radiative transfer codesMeteorologyOcean colorRadianceGeostationary orbitRadiative transferHyperspectral imagingEnvironmental scienceAtmospheric modelViewing angleRemote sensing2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
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Optimization of image parameters using a hyperspectral library application to soil identification and moisture estimation

2009

The growing number of sensors raises questions about the image parameters required for the application, soil identification and moisture estimation. Hyperspectral images are also known to contain highly redundant information. Hence not all the spectral bands are needed for the satisfactory classification of the soil types. Hence, the work was aimed at obtaining these optimal spectral bands for identifying the soil types and to use these spectral bands to estimate the moisture content of the soils using the method proposed by Whiting et.al.

Identification (information)MoistureSoil waterEnvironmental scienceHyperspectral imagingFeature selectionSoil classificationSpectral bandsWater contentPhysics::GeophysicsRemote sensing2009 IEEE International Geoscience and Remote Sensing Symposium
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Bathymetric estimation using MERIS images in coastal sea waters.

2007

Bathymetric estimation using remote sensing images has previously been applied to high spatial resolution imagery such as CASI, Ikonos, or SPOT but not on medium spatial resolution images (i.e., MERIS). This choice can be justified when there is a need to map the bathymetry on large areas. In this letter, we present the results of the bathymetry estimation over a large known area, the Gulf of Lion (France), expanding over 270times180 km

010504 meteorology & atmospheric sciences0211 other engineering and technologies02 engineering and technologyCoastal zone01 natural sciences[SPI]Engineering Sciences [physics]Coastal zoneHigh spatial resolutionBathymetry14. Life underwaterElectrical and Electronic EngineeringImage resolutionComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesCoastal seaRemote sensingEstimationGeotechnical Engineering and Engineering GeologyMERISOceanographyRemote sensing (archaeology)Bathymetry[SDE]Environmental Sciences[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingGeology
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Influence of solar and sensor angles on chlorophyll estimation for geostationary ocean color imager

2012

The impact of the solar and sensor angles on band-ratio chlorophyll concentration (Chl) estimation in Case 1 waters (open ocean) is analyzed in this work. The error range of Chl estimation due to angular variation is evaluated. The radiative transfer code Hydrolight is used for remote sensing reflectance simulation for 20 spectral bands. OC4v4 algorithm is used for Chl estimation. The results indicate that the error range of Chl estimation is between -41.91% and +46.15% when Chl range is from 0.0425 mg/m 3 to 10.6685 mg/m 3 and the solar and sensor zenith angles vary between 0 and 80°. This study provides a reference to determine the effective observation area of a future multispectral or h…

Ocean colorMultispectral imageGeostationary orbitRadiative transferHyperspectral imagingEnvironmental scienceSpectral bands[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingGeostationary Ocean Color ImagerZenithComputingMilieux_MISCELLANEOUS[SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/OceanographyRemote sensing
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Assessment of the Potential future high and medium resolution sensors on geosynchronous orbit for coastal zone monitoring

2009

Geosynchronous satellite can measure any area with high temporal repetitivity within its coverage region because of its relative static location compared to Earth. Considering the temporal repetitivity, it can satisfy requirements for coastal zone monitoring but also has to face the influence of the varying solar angle and sensor angle (zenith and azimuth). Up to now, there is no geosynchronous sensor dedicated to ocean color monitoring (a geosynchronous sensor "Korea Geostationary Ocean Color Imager" (KGOCI) is supposed to be launched in 2009 [1]). To obtain radiances from the ocean at 36000km of altitude, we have to use a simulation model. In this conference, we present generic model of s…

AzimuthMeteorologyOcean colorOcean chemistryPhysics::Space PhysicsGeosynchronous orbitEnvironmental scienceAtmospheric modelImage sensorPhysics::Atmospheric and Oceanic PhysicsZenithGeostationary Ocean Color ImagerRemote sensing2009 IEEE International Geoscience and Remote Sensing Symposium
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Satellite survey of seasonal trophic status and occasional anoxic 'malaigue' crises in the Thau lagoon using MERIS images

2011

International audience; The Thau lagoon, located in southern France, suffers episodically from anoxic crises locally known as 'malaigue'. Such crises mostly occur under warm conditions, low winds leading to a strong eutrophication of the lagoon. The development of a sulphur bacterium sometimes gives locally to the waters a 'milky turquoise' appearance and leads to shellfish mortality. One of the indicators of the eutrophication status of the lagoon can be surveyed by the chlorophyll product provided by remote sensing images such as Medium Resolution Imaging Spectrometer (MERIS). In this paper we compare chl2 (or algal2) estimations provided by MERIS level 2 products and the ground measureme…

0106 biological sciences[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciencesEcology[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing010604 marine biology & hydrobiology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesAnoxic waters6. Clean waterMedium resolutionOceanography[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing13. Climate actionGeneral Earth and Planetary SciencesEnvironmental scienceSatellite14. Life underwaterEutrophication[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing0105 earth and related environmental sciencesTrophic level[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Simulation of Future Geostationary Ocean Color Images

2012

The objective of this work is to simulate global images that would be provided by a theoretical ocean color sensor on a geostationary orbit at longitude 0, in order to assess the range of radiance value data reaching the sensor throughout the day for 20 spectral bands similar to those of the Ocean and Land Color Imager (OLCI). The secondary objective is to assess the illumination and viewing geometries that result in sunglint. For this purpose, we combined a radiative transfer model for ocean waters (Hydrolight) and a radiative transfer model for atmosphere (MODTRAN) to construct the simulated radiance images at the sea surface and at the Top-Of-Atmosphere (TOA). Bio-optical data from GlobC…

Atmospheric Science010504 meteorology & atmospheric sciencesMeteorologyMODTRANSolar zenith angleSunglint01 natural sciences010309 opticsAtmospheric radiative transfer codes13. Climate actionOcean color0103 physical sciencesGeostationary orbitRadianceEnvironmental scienceComputers in Earth Sciences[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUSZenith0105 earth and related environmental sciencesRemote sensingIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Discrimination of coral reflectance spectra in the Red Sea

2002

Benthic populations can potentially be mapped from remotely acquired spectral imagery, provided that they have distinctive reflectance signatures. We examined the spectral reflectance characteristics of 14 genera of Red Sea coral using a submersible spectroradiometer. Coral spectra varied quantitatively and qualitatively over the depth interval 5–20 m. Tissue pigment content had a larger effect on reflectance than colony morphology. Ten coral genera could be discriminated with a statistical probability of 52% on the basis of their absolute reflectance. Six groups of two to three coral genera could be discriminated with a probability of 60% on the basis of their rates of change in reflectanc…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciences[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCoral0211 other engineering and technologies02 engineering and technologyAquatic Science01 natural sciencesSpectral line[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing14. Life underwaterComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinggeographygeography.geographical_feature_categoryfungiPigment compositionCoral reefReflectivityWavelengthSpectroradiometerBenthic zone[SDE]Environmental SciencesEnvironmental science[SDE.BE]Environmental Sciences/Biodiversity and Ecology
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Comparison of Bathymetric estimation using different satellite images in coastal sea waters

2009

Bathymetric estimation can be obtained from multispectral satellite images for shallow waters. The method is based on the rotation of a pair of spectral bands. One of the resulting images is depth-dependent. Therefore several pixels corresponding to different depths are required to numerically evaluate the linear relation between the pixel values and the real depth for a training area. The aim of this study is to compare, for one bathymetric estimation method and one mesotrophic site, the results of depth estimation with a large panel of satellite and aerial images: CASI, QUICKBIRD, CHRIS PROBA, ETM, HYPERION and MeRIS. For each image the pair of spectral bands chosen to compute the bathyme…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciencesPixelAerial survey[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingMultispectral image0211 other engineering and technologies02 engineering and technologySpectral bands01 natural sciencesMultispectral pattern recognition[SPI]Engineering Sciences [physics][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer Science::Computer Vision and Pattern RecognitionGeneral Earth and Planetary SciencesBathymetry14. Life underwaterQuantization (image processing)Image resolution[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingGeologyComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Optimal band selection for future satellite sensor dedicated to soil science

2009

Hyperspectral imaging systems could be used for identifying the different soil types from the satellites. However, detecting the reflectance of the soils in all the wavelengths involves the use of a large number of sensors with high accuracy and also creates a problem in transmitting the data to earth stations for processing. The current sensors can reach a bandwidth of 20 nm and hence, the reflectance obtained using the sensors are the integration of reflectance obtained in each of the wavelength present in the spectral band. Moreover, not all spectral bands contribute equally to classification and hence, identifying the bands necessary to have a good classification is necessary to reduce …

Statistical classificationContextual image classificationComputer scienceBandwidth (signal processing)Hyperspectral imagingSatelliteFeature selectionSpectral bandsData transmissionRemote sensing2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
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Re-evaluation of the extent of Caulerpa taxifolia development in the northern Mediterranean using airborne spectrographic sensing

2003

International audience; no abstract

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMilieux_MISCELLANEOUS
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Conception of Products and Services for coastal applications

2005

International audience

[ SPI.NRJ ] Engineering Sciences [physics]/Electric power[SPI.NRJ]Engineering Sciences [physics]/Electric powerComputingMilieux_MISCELLANEOUS[SPI.NRJ] Engineering Sciences [physics]/Electric power
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A century of warfare shoots holes in anti-Caulerpa campaign

2007

doi:10.1038 /npre.2007.1240.1; International audience; no abstract

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing
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Comparison of metrics for the classification of soils under variable geometrical conditions using hyperspectral data

2008

International audience; no abstract

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMilieux_MISCELLANEOUS
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