Search results for "Earth Observation"

showing 10 items of 82 documents

Statistical Learning for End-to-End Simulations

2018

End-to-end mission performance simulators (E2ES) are suitable tools to accelerate satellite mission development from concet to deployment. One core element of these E2ES is the generation of synthetic scenes that are observed by the various instruments of an Earth Observation mission. The generation of these scenes rely on Radiative Transfer Models (RTM) for the simulation of light interaction with the Earth surface and atmosphere. However, the execution of advanced RTMs is impractical due to their large computation burden. Classical interpolation and statistical emulation methods of pre-computed Look-Up Tables (LUT) are therefore common practice to generate synthetic scenes in a reasonable…

Signal Processing (eess.SP)Earth observation010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesFOS: Physical sciences02 engineering and technologyLinear interpolation01 natural sciencesSpectral lineComputational sciencesymbols.namesakeSampling (signal processing)Radiative transferFOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal ProcessingGaussian processInstrumentation and Methods for Astrophysics (astro-ph.IM)021101 geological & geomatics engineering0105 earth and related environmental sciencesEmulationGround-penetrating radarLookup tableRadiancesymbolsAstrophysics - Instrumentation and Methods for AstrophysicsInterpolation
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Toward a Collective Agenda on AI for Earth Science Data Analysis

2021

In the last years we have witnessed the fields of geosciences and remote sensing and artificial intelligence to become closer. Thanks to both the massive availability of observational data, improved simulations, and algorithmic advances, these disciplines have found common objectives and challenges to advance the modeling and understanding of the Earth system. Despite such great opportunities, we also observed a worrying tendency to remain in disciplinary comfort zones applying recent advances from artificial intelligence on well resolved remote sensing problems. Here we take a position on research directions where we think the interface between these fields will have the most impact and be…

Signal Processing (eess.SP)FOS: Computer and information sciences010504 meteorology & atmospheric sciencesGeneral Computer Science530 PhysicsInterface (Java)Computer Vision and Pattern Recognition (cs.CV)Earth sciencedata analysisComputer Science - Computer Vision and Pattern Recognition0211 other engineering and technologiesearth observation02 engineering and technology01 natural sciencesEnvironmental scienceData modelingFOS: Electrical engineering electronic engineering information engineeringClimate science1700 General Computer ScienceElectrical Engineering and Systems Science - Signal ProcessingElectrical and Electronic EngineeringInstrumentation021101 geological & geomatics engineering0105 earth and related environmental sciences11476 Digital Society Initiative3105 Instrumentation2208 Electrical and Electronic Engineering1900 General Earth and Planetary SciencesDeep learninginterpretable AIRemote sensingartificial intelligencehybrid modelsEarth system scienceAIRemote sensing (archaeology)10231 Institute for Computational ScienceGeneral Earth and Planetary SciencesPotential gameDisciplineIEEE Geoscience and Remote Sensing Magazine
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Deep Gaussian processes for biogeophysical parameter retrieval and model inversion

2020

Parameter retrieval and model inversion are key problems in remote sensing and Earth observation. Currently, different approximations exist: a direct, yet costly, inversion of radiative transfer models (RTMs); the statistical inversion with in situ data that often results in problems with extrapolation outside the study area; and the most widely adopted hybrid modeling by which statistical models, mostly nonlinear and non-parametric machine learning algorithms, are applied to invert RTM simulations. We will focus on the latter. Among the different existing algorithms, in the last decade kernel based methods, and Gaussian Processes (GPs) in particular, have provided useful and informative so…

Signal Processing (eess.SP)FOS: Computer and information sciencesComputer Science - Machine LearningEarth observation010504 meteorology & atmospheric sciencesIASIComputer science0211 other engineering and technologiesExtrapolation02 engineering and technologyDeep Gaussian Processes01 natural sciencesArticleMachine Learning (cs.LG)symbols.namesakeCopernicus programmeSentinelsMachine learningRadiative transferFOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal ProcessingComputers in Earth SciencesModel inversionStatistical retrievalEngineering (miscellaneous)Gaussian processChlorophyll contentMoisture021101 geological & geomatics engineering0105 earth and related environmental sciencesbusiness.industryInorganic suspended matterTemperatureInversion (meteorology)Statistical modelAtomic and Molecular Physics and OpticsComputer Science ApplicationsInfrared sounderNonlinear systemsymbolsGlobal Positioning SystemColoured dissolved matterbusinessAlgorithm
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Synergistic integration of optical and microwave satellite data for crop yield estimation

2019

Developing accurate models of crop stress, phenology and productivity is of paramount importance, given the increasing need of food. Earth observation (EO) remote sensing data provides a unique source of information to monitor crops in a temporally resolved and spatially explicit way. In this study, we propose the combination of multisensor (optical and microwave) remote sensing data for crop yield estimation and forecasting using two novel approaches. We first propose the lag between Enhanced Vegetation Index (EVI) derived from MODIS and Vegetation Optical Depth (VOD) derived from SMAP as a new joint metric combining the information from the two satellite sensors in a unique feature or des…

Signal Processing (eess.SP)FOS: Computer and information sciencesEarth observationCoefficient of determinationTeledetecció010504 meteorology & atmospheric sciencesEnhanced vegetation index0208 environmental biotechnologyFOS: Physical sciencesSoil Science02 engineering and technologyStatistics - Applications01 natural sciencesArticleModerate resolution imaging spectroradiometer (MODIS)Robustness (computer science)Machine learningLinear regressionFOS: Electrical engineering electronic engineering information engineeringFeature (machine learning)Kernel ridge regressionCrop yield estimationVegetation optical depthApplications (stat.AP)Electrical Engineering and Systems Science - Signal ProcessingComputers in Earth Sciences0105 earth and related environmental sciencesRemote sensingMathematics2. Zero hungerCrop yieldProcessos estocàsticsGeologyEnhanced vegetation indexAgro-ecosystems020801 environmental engineeringPhysics - Data Analysis Statistics and ProbabilityMetric (mathematics)Soil moisture active passive (SMAP)Data Analysis Statistics and Probability (physics.data-an)Imatges Processament
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Quantifying residential PV feed-in power in low voltage grids based on satellite-derived irradiance data with application to power flow calculations

2016

AbstractA scheme using satellite-derived irradiance measurements to model the feed-in power of residential photovoltaic (PV) systems in a low voltage distribution grid is described. It is validated against smart meter measurements from a test site with 12 residential PV systems in the city of Ulm, Germany, during May 2013 to December 2014. The PV feed-in power is simulated in a 15-min time resolution based on irradiance data derived from Meteosat Second Generation satellite images by the physically based retrieval scheme Heliosat-4. The PV simulation is based on the nominal power and location of the PV systems as provided by the distribution system operator. Orientation angles are taken fro…

Smart meter020209 energyCAMS radiation serviceIrradiance02 engineering and technology7. Clean energyMaximum power point trackinglaw.inventionMaterials Science(all)law0202 electrical engineering electronic engineering information engineeringGrid-connected photovoltaic power systemResidential photovoltaicGeneral Materials ScienceTransformerRemote sensingEarth observationRenewable Energy Sustainability and the EnvironmentPhotovoltaic systemDeutsches FernerkundungsdatenzentrumDistribution networkHeliosat methodLow voltage gridEnvironmental scienceAtmosphäreLow voltageNominal power (photovoltaic)Solar Energy
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Urban monitoring using multi-temporal SAR and multi-spectral data

2006

In some key operational domains, the joint use of synthetic aperture radar (SAR) and multi-spectral sensors has shown to be a powerful tool for Earth observation. In this paper, we analyze the potentialities of combining interferometric SAR and multi-spectral data for urban area characterization and monitoring. This study is carried out following a standard multi-source processing chain. First, a pre-processing stage is performed taking into account the underlying physics, geometry, and statistical models for the data from each sensor. Second, two different methodologies, one for supervised and another for unsupervised approaches, are followed to obtain features that optimize the urban rela…

Synthetic aperture radarEarth observationFeature selectionStatistical modelcomputer.software_genreData setData acquisitionArtificial IntelligenceSignal ProcessingStandard algorithmsComputer Vision and Pattern RecognitionData miningcomputerSoftwareMulti-sourcePattern Recognition Letters
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Space-borne frequency comb metrology

2016

Precision time references in space are of major importance to satellite-based fundamental science, global satellite navigation, earth observation, and satellite formation flying. Here we report on the operation of a compact, rugged, and automated optical frequency comb setup on a sounding rocket in space under microgravity. The experiment compared two clocks, one based on the optical D2 transition in Rb, and another on hyperfine splitting in Cs. This represents the first frequency comb based optical clock operation in space, which is an important milestone for future satellite-based precision metrology. Based on the approach demonstrated here, future space-based precision metrology can be i…

Synthetic aperture radarPhysicsEarth observationSounding rocketOrders of magnitude (temperature)business.industryPhysics::Optics02 engineering and technology021001 nanoscience & nanotechnology01 natural sciencesAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsMetrology010309 opticsFrequency combOpticsPhysics::Space Physics0103 physical sciencesSatelliteSatellite navigation0210 nano-technologybusinessOptica
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Quantification of land-atmosphere exchanges of water, energy and carbon dioxide in space and time over the heterogeneous Barrax site

2008

International audience; To advance our understanding of land-atmosphere exchanges of water, energy and carbon dioxide (CO2) in space and time over heterogeneous land surfaces, two intensive field campaigns were carried out at the Barrax agricultural test site in Spain during 12-21 July 2004 (SPARC 2004) and 8-14 July 2005 (SEN2FLEX 2005) involving multiple field, satellite and airborne instruments for characterizing the state of the atmosphere, the vegetation and the soil from the visible to the microwave range of the spectrum. Part of the experimental area is a core site of area 25 km2, within which numerous crops are grown, on both irrigated and dry land, alongside fields of bare soil. Th…

[SPI.OTHER]Engineering Sciences [physics]/Otherenergie-uitwisselingEarth observation010504 meteorology & atmospheric sciences02 engineering and technologyatmosferische grenslaag01 natural sciencesBARRAXAIRBORNE INSTRUMENTchemistry.chemical_compoundremote sensingmetingLaboratory of Geo-information Science and Remote SensingAlterra - Centre for Water and ClimateWageningen Environmental Research020701 environmental engineeringWater energySATELLITEatmospheric boundary-layerENVIRONMENTAL SCIENCEVegetationCentre Geo-informationPE&RCkooldioxideRemote sensing (archaeology)Carbon dioxideaardoppervlakAlterra - Centrum Water en KlimaatPlanetary boundary layerAlterra - Centrum Geo-informatiewater0207 environmental engineeringWRSvegetatieAtmospherevegetationLaboratorium voor Geo-informatiekunde en Remote Sensingatmosfeer0105 earth and related environmental sciencesRemote sensingland surfaceSPAINCROPcarbon dioxide15. Life on landLAND ATMOSPHERERELATION SOL-PLANTE-ATMOSPHEREHETEROGENEOUS LAND SURFACEenergy exchangeSOILADLIB-ART-2682chemistry13. Climate actionITC-ISI-JOURNAL-ARTICLEatmosphereGeneral Earth and Planetary SciencesEnvironmental scienceSatellitemeasurement
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Monitoring Water and Energy Cycles at Climate Scale in the Third Pole Environment (CLIMATE-TPE)

2021

A better understanding of the water and energy cycles at climate scale in the Third Pole Environment is essential for assessing and understanding the causes of changes in the cryosphere and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and for predicting the possible changes in water resources in South and East Asia. This paper reports the following results: (1) A platform of in situ observation stations is briefly described for quantifying the interactions in hydrosphere-pedosphere-atmosphere-cryosphere-biosphere over the Tibetan Plateau. (2) A multiyear in situ L-Band microwave radiometry of land surface processes is used to develop a new microwave r…

ddc:621.3Scienceearth observationAtmospheric sciencesevaporationTroposphereEvapotranspirationTibetan PlateauCryosphereEast Asian MonsoonmonsoonStratosphereThird Pole EnvironmentgeographyPlateaugeography.geographical_feature_categoryQITC-ISI-JOURNAL-ARTICLEGeneral Earth and Planetary SciencesEnvironmental scienceddc:620soil moistureITC-GOLDWater vaporThird Pole Environment; Tibetan Plateau; monsoon; earth observation; evaporation; soil moisture; microwave remote sensingHydrosphereRemote Sensing
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Advanced earth observation approach for multiscale forest ecosystem services modeling and mapping (MIMOSE)

2014

In the last decade ecosystem services (ES) have been proposed as a method for quantifying the multifunctional role of forest ecosystems. Their spatial distribution on large areas is frequently limited by the lack of information, because field data collection with traditional methods requires much effort in terms of time and cost. In this contribution we propose a methodology (namely, MultIscale Mapping Of ecoSystem servicEs - MIMOSE) based on the integration of remotely sensed images and field observation to produce a wall-to-wall geodatabase of forest parcels accompanied with several information useful as a basis for future trade-off analysis of different ES. Here, we present the applicat…

forests mappingSettore AGR/05 - Assestamento Forestale E Selvicolturaearth observationForestsMimose Projectearth observation; ecosystem services; forests; mapping; mimose project; remote sensing;lcsh:QK1-989ecosystem serviceremote sensingecosystem services; earth observation; remote sensing; Mimose Project; forests mappingMappinglcsh:BotanyEcosystem servicesMIMOSE
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