0000000000942996

AUTHOR

Marie Weiss

showing 9 related works from this author

EVASPA (EVapotranspiration Assessment from SPAce) tool: an overview

2013

International audience; Evapotranspiration (ET) is a fundamental variable of the hydrological cycle and its estimation is required for irrigation management, water resources planning and environmental studies. Remote sensing provides spatially distributed cost-effective information for ET maps production at regional scale. We have developed EVASPA too for mapping ET from remote sensing data at spatial and temporal scales relevant to hydrological or agronomica studies. EVASPA includes several algorithms for estimating evapotranspiration and various equations for estimating the required input information (net radiation, ground heat flux, evaporative fraction…), which provides a way to assess …

Crau-Camargue.010504 meteorology & atmospheric sciencesBiodiversité et Ecologietélédétectionévapotranspirationcartographie - évapotranspiration;télédétection;landsat;MODIS02 engineering and technologysatellite landsat01 natural sciencesirrigationremote sensingEvapotranspirationtélédétection spatialeWater cycle020701 environmental engineeringTemporal scalesGeneral Environmental Science6. Clean waterVariable (computer science)Remote sensing (archaeology)francealgorithmebase de données spatio temporellelandsat0207 environmental engineering[SCCO.COMP]Cognitive science/Computer sciencecartographie - évapotranspirationcycle hydrologiquecamargueBiodiversity and Ecologyressource en eauIrrigation management0105 earth and related environmental sciencesRemote sensingEnvironmental and Societyrayonnement netEvapotranspiration mappingflux conductif de chaleur dans le solcrauComputer science[SDE.ES]Environmental Sciences/Environmental and SocietyWater resourcesMODIS13. Climate actionInformatique (Sciences cognitives)cartographieGeneral Earth and Planetary SciencesEnvironmental scienceéchelle spatio temporelleEnvironnement et Société[SDE.BE]Environmental Sciences/Biodiversity and EcologyScale (map)
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A multisensor fusion approach to improve LAI time series

2011

International audience; High-quality and gap-free satellite time series are required for reliable terrestrial monitoring. Moderate resolution sensors provide continuous observations at global scale for monitoring spatial and temporal variations of land surface characteristics. However, the full potential of remote sensing systems is often hampered by poor quality or missing data caused by clouds, aerosols, snow cover, algorithms and instrumentation problems. A multisensor fusion approach is here proposed to improve the spatio-temporal continuity, consistency and accuracy of current satellite products. It is based on the use of neural networks, gap filling and temporal smoothing techniques. …

010504 meteorology & atmospheric sciencesMeteorologytélédétectionsatellite0211 other engineering and technologiesSoil Scienceréseau neuronal02 engineering and technology01 natural sciencessuivi de culturesInstrumentation (computer programming)Computers in Earth SciencesLeaf area index021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingVegetationGeologyVegetationData fusionLAI time seriesSensor fusionMissing dataLAI time series;Vegetation;Modis;Temporal smoothing;Gap filling;Data fusionqualité des données13. Climate actionAutre (Sciences de l'ingénieur)Gap filling[SDE]Environmental SciencesEnvironmental scienceSatelliteModisTemporal smoothingScale (map)Smoothing
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GEOV1: LAI, FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part 2: Validation and intercomparis…

2013

International audience; This paper describes the scientific validation of the first version of global biophysical products (i.e., leaf area index, fraction of absorbed photosynthetically active radiation and fraction of vegetation cover), namely GEOV1, developed in the framework of the geoland-2/BioPar core mapping service at 1 km spatial resolution and 10-days temporal frequency. The strategy follows the recommendations of the CEOS/WGCV Land Product Validation for LAI global products validation. Several criteria of performance were evaluated, including continuity, spatial and temporal consistency, dynamic range of retrievals, statistical analysis per biome type, precision and accuracy. The…

Accuracy and precision010504 meteorology & atmospheric sciencescouvert végétalcomparaison de modèlesBiomecritère de performanceSoil ScienceMagnitude (mathematics)Context (language use)01 natural sciencesGEOV1;Vegetation variables;Validation;GMES;Land monitoring core servicevalidation scientifiquefraction of absorbed photosynthetically active radiation (fAPAR)GEOV1ValidationfcoverFraction (mathematics)Computers in Earth SciencesLeaf area indexvariable climatiqueMilieux et Changements globauxfraction de couvert0105 earth and related environmental sciencesRemote sensinggmescarte de référenceanalyse statistiquefaparLand monitoring core serviceGeology04 agricultural and veterinary sciencesresolution spatiale15. Life on landComputer scienceLAIindice de surface foliaireSeaWiFSbiome13. Climate actionPhotosynthetically active radiationInformatique (Sciences cognitives)surveillance de l'environnement[SDE]Environmental Sciences040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental scienceVegetation variables
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Performances of neural networks for deriving LAI estimates from existing CYCLOPES and MODIS products

2008

International audience; This paper evaluates the performances of a neural network approach to estimate LAI from CYCLOPES and MODIS nadir normalized reflectance and LAI products. A data base was generated from these products over the BELMANIP sites during the 2001-2003 period. Data were aggregated at 3 km x 3 km, resampled at 1/16 days temporal frequency and filtered to reject outliers. VEGETATION and MODIS reflectances show very consistent values in the red, near infrared and short wave infrared bands. Neural networks were trained over part of this data base for each of the 6 MODIS biome classes to retrieve both MODIS and CYCLOPES LAI products. Results show very good performances of neural …

[SPI.OTHER]Engineering Sciences [physics]/OtherMean squared errorBiome0211 other engineering and technologiesSoil Science02 engineering and technologyNEURAL NETWORKSStandard deviationALBEDONadirComputers in Earth SciencesLeaf area indexLEA021101 geological & geomatics engineeringRemote sensingMathematicsCYCLOPESGeology04 agricultural and veterinary sciencesVegetation15. Life on landCONSISTENCY OF PRODUCTSRESEAU DE NEURONESMODISTemporal resolutionOutlier040103 agronomy & agriculture0401 agriculture forestry and fisheriesVEGETATIONLEAF AREA INDEX
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Crop specific algorithms trained over ground measurements provide the best performance for GAI and fAPAR estimates from Landsat-8 observations

2021

Abstract Estimation of Green Area Index (GAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) from decametric satellites was investigated in this study using a large database of ground measurements over croplands. It covers six main crop types including rice, corn, wheat and barley, sunflower, soybean and other types of crops. Ground measurements were completed using either digital hemispherical cameras, LAI-2000 or AccuPAR devices over sites representative of a decametric pixel. Sites were spread over the globe and the data collected at several growth stages concurrently to the acquisition of Landsat-8 images. Several machine learning techniques were investigated to re…

010504 meteorology & atmospheric sciencesMean squared errorArtificial neural networkCalibration (statistics)0208 environmental biotechnologyEmpirical modellingSoil ScienceGeology02 engineering and technology01 natural sciencesNormalized Difference Vegetation Index020801 environmental engineeringSupport vector machineData pointKrigingComputers in Earth SciencesAlgorithm0105 earth and related environmental sciencesRemote sensingMathematicsRemote Sensing of Environment
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Data service platform for sentinel-2 surface reflectance and value-added products: System use and examples

2016

This technical note presents the first Sentinel-2 data service platform for obtaining atmospherically-corrected images and generating the corresponding value-added products for any land surface on Earth (http://s2.boku.eodc.eu/). Using the European Space Agency’s (ESA) Sen2Cor algorithm, the platform processes ESA’s Level-1C top-of-atmosphere reflectance to atmospherically-corrected bottom-of-atmosphere (BoA) reflectance (Level-2A). The processing runs on-demand, with a global coverage, on the Earth Observation Data Centre (EODC), which is a public-private collaborative IT infrastructure in Vienna (Austria) for archiving, processing, and distributing Earth observation (EO) data (http://www.…

Earth observation010504 meteorology & atmospheric sciencesreflectanceComputer sciencetélédétection0211 other engineering and technologies02 engineering and technology01 natural sciences7. Clean energyConsistency (database systems)remote sensingTraitement du signal et de l'imageatmospheric correctionremote sensing;sentinel-2;atmospheric correction;Sen2Cor;LAI;broadband HDRFlcsh:Science021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingSentinel-2; atmospheric correction; Sen2Cor; LAI; broadband HDRFbusiness.industrysentinel-2Settore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaSignal and Image processingVegetationReflectivitybroadband HDRFLAIatmosphèreSen2Cor13. Climate actionGeneral Earth and Planetary Scienceslcsh:QData centerData as a servicebusinessdonnée satellitaire[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Combining hectometric and decametric satellite observations to provide near real time decametric FAPAR product

2017

Abstract A wide range of ecological, agricultural, hydrological and meteorological applications at local to regional scales requires decametric biophysical data. However, before the launch of SENTINEL-2A, only few decametric products are produced and most of them remain limited by the small number of available observations, mostly due to a moderate revisit frequency combined with cloud occurrence. Conversely, kilometric and hectometric biophysical products are now widely available with almost complete and continuous coverage, but the associated spatial resolution limits the application over heterogeneous landscapes. The objective of this study is to combine unfrequent decametric spatial res…

Point spread functionanalyse de données010504 meteorology & atmospheric sciencesMeteorology[SDV]Life Sciences [q-bio]Real-time computingdata analysis0211 other engineering and technologiesSoil Science02 engineering and technology01 natural sciencesGEOV3Range (statistics)Landsat-8FAPARComputers in Earth Sciencestemps réelImage resolutionphotosynthetically active radiation021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinganalyse temporellereal timePixelrayonnement photosynthétiquement actifGeologyFunction (mathematics)15. Life on landData fusionSensor fusionDecametricHectometric13. Climate actionPhotosynthetically active radiationtime analysisEnvironmental scienceSatelliteNear real timeobservation satellite
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On Line Validation Exercise (OLIVE): A Web Based Service for the Validation of Medium Resolution Land Products. Application to FAPAR Products

2014

International audience; The OLIVE (On Line Interactive Validation Exercise) platform is dedicated to the validation of global biophysical products such as LAI (Leaf Area Index) and FAPAR (Fraction of Absorbed Photosynthetically Active Radiation). It was developed under the framework of the CEOS (Committee on Earth Observation Satellites) Land Product Validation (LPV) sub-group. OLIVE has three main objectives: (i) to provide a consistent and centralized information on the definition of the biophysical variables, as well as a description of the main available products and their performances (ii) to provide transparency and traceability by an online validation procedure compliant with the CEO…

validation;LAI;FAPAR;intercomparison;product;CEOSService (systems architecture)Earth observationTraceabilityComputer scienceScienceintercomparison10127 Institute of Evolutionary Biology and Environmental StudiesDocumentationBenchmark (surveying)Web applicationproductFAPARComputingMilieux_MISCELLANEOUSRemote sensingvalidationbusiness.industryQ1900 General Earth and Planetary SciencesLAI13. Climate action[SDE]Environmental Sciences570 Life sciences; biology590 Animals (Zoology)General Earth and Planetary SciencesbusinessHost (network)Quality assuranceCEOSRemote Sensing
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Quantification of LAI interannual anomalies by adjusting climatological patterns

2011

International audience; Scaling variations and shifts in the timing of seasonal phenology are central features of global change research. In this study, we propose a novel climatology fitting approach to quantify inter-annual anomalies in LAI seasonality. A consistent archive of daily LAI estimates was first derived from historical AVHRR satellite data for the 1981-2000 period over a globally representative sample of sites. The climatology values were then computed by averaging multi-year LAI profiles, gap filling and smoothing to eliminate possible high temporal frequency residual artifacts. The inter-annual variations in LAI were finally quantified by scaling and shifting the seasonal cli…

AVHRR010504 meteorology & atmospheric sciencesPhenology0211 other engineering and technologiesGlobal change02 engineering and technologyAtmospheric modelVegetationclimatology fittingSeasonalityResidualmedicine.disease01 natural sciencesLAIClimatology[SDE]Environmental SciencesmedicineEnvironmental scienceIndex Terms— inter-annual anomaliesTime seriesSmoothing021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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