Search results for "Atmospheric radiative transfer codes"

showing 10 items of 60 documents

Joint Gaussian processes for inverse modeling

2017

Solving inverse problems is central in geosciences and remote sensing. Very often a mechanistic physical model of the system exists that solves the forward problem. Inverting the implied radiative transfer model (RTM) equations numerically implies, however, challenging and computationally demanding problems. Statistical models tackle the inverse problem and predict the biophysical parameter of interest from radiance data, exploiting either in situ data or simulated data from an RTM. We introduce a novel nonlinear and nonparametric statistical inversion model which incorporates both real observations and RTM-simulated data. The proposed Joint Gaussian Process (JGP) provides a solid framework…

010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesNonparametric statisticsInverseInversion (meteorology)Statistical model02 engineering and technologyInverse problem01 natural sciencesData modelingNonlinear systemsymbols.namesakeAtmospheric radiative transfer codesRadiancesymbolsGaussian processAlgorithm021101 geological & geomatics engineering0105 earth and related environmental sciences
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Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with …

2011

International audience; Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test dataset…

010504 meteorology & atmospheric sciencesComputer scienceGaussian0211 other engineering and technologiesSoil ScienceCANOPY BIOPHYSICAL CHARACTERISTICS02 engineering and technologyNEURAL NETWORK01 natural sciencesTransfer functionsymbols.namesakeAtmospheric radiative transfer codesRadiative transferRange (statistics)Sensitivity (control systems)Computers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingArtificial neural networkGeologySigmoid functionRELATION SOL-PLANTE-ATMOSPHEREMODEL INVERSION[SDE]Environmental SciencessymbolsINDICE FOLIAIRE
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Gaussian Processes Retrieval of LAI from Sentinel-2 Top-of-Atmosphere Radiance Data

2020

Abstract Retrieval of vegetation properties from satellite and airborne optical data usually takes place after atmospheric correction, yet it is also possible to develop retrieval algorithms directly from top-of-atmosphere (TOA) radiance data. One of the key vegetation variables that can be retrieved from at-sensor TOA radiance data is leaf area index (LAI) if algorithms account for variability in atmosphere. We demonstrate the feasibility of LAI retrieval from Sentinel-2 (S2) TOA radiance data (L1C product) in a hybrid machine learning framework. To achieve this, the coupled leaf-canopy-atmosphere radiative transfer models PROSAIL-6SV were used to simulate a look-up table (LUT) of TOA radi…

010504 meteorology & atmospheric sciencesMean squared errorComputer science0211 other engineering and technologiesAtmospheric correctionFOS: Physical sciences02 engineering and technology15. Life on land01 natural sciencesAtomic and Molecular Physics and OpticsArticleComputer Science ApplicationsPhysics - Atmospheric and Oceanic PhysicsAtmospheric radiative transfer codesKrigingAtmospheric and Oceanic Physics (physics.ao-ph)RadianceSatelliteComputers in Earth SciencesLeaf area indexScale (map)Engineering (miscellaneous)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Empirical and physical estimation of Canopy Water Content from CHRIS/PROBA data

2013

20 páginas, 4 tablas, 7 figuras.

010504 meteorology & atmospheric sciencesMean squared errorScience0211 other engineering and technologies02 engineering and technologyCHRIS/PROBA01 natural sciencescanopy water content;model inversion;neural networks;look up tables;empirical up-scalingmodel inversionEmpirical up-scalingAtmospheric radiative transfer codeslook up tablesRadiative transferModel inversion021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingArtificial neural networkCanopy water contentQHyperspectral imagingInversion (meteorology)Sigmoid functionSpectral bandsempirical up-scaling15. Life on landneural networks[SDE]Environmental SciencesGeneral Earth and Planetary SciencesLook up tablescanopy water contentNeural networkscanopy water content; model inversion; neural networks; look up tables; empirical up-scaling; CHRIS/PROBA
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Exploitation of SAR and Optical Sentinel Data to Detect Rice Crop and Estimate Seasonal Dynamics of Leaf Area Index

2017

This paper presents and evaluates multitemporal LAI estimates derived from Sentinel-2A data on rice cultivated area identified using time series of Sentinel-1A images over the main European rice districts for the 2016 crop season. This study combines the information conveyed by Sentinel-1A and Sentinel-2A into a high-resolution LAI retrieval chain. Rice crop was detected using an operational multi-temporal rule-based algorithm, and LAI estimates were obtained by inverting the PROSAIL radiative transfer model with Gaussian process regression. Direct validation was performed with in situ LAI measurements acquired in coordinated field campaigns in three countries (Italy, Spain and Greece). Res…

010504 meteorology & atmospheric sciencesMean squared errorScienceleaf area index (LAI)0211 other engineering and technologies02 engineering and technology01 natural sciencesCropAtmospheric radiative transfer codesConsistency (statistics)KrigingSpatial consistencyArròs Malalties i plaguesSentinel-1ALeaf area indexmappingSentinel021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing2. Zero hungerLeaf Area IndexSentinel-2AQCiències de la terrarice mapGeneral Earth and Planetary SciencesEnvironmental sciencerice map; leaf area index (LAI); Sentinel-1A; Sentinel-2A; Gaussian process regressionRice cropGaussian process regressionRemote Sensing
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Primary production calculations for sea ice from bio-optical observations in the Baltic Sea

2016

Abstract Bio-optics is a powerful approach for estimating photosynthesis rates, but has seldom been applied to sea ice, where measuring photosynthesis is a challenge. We measured absorption coefficients of chromophoric dissolved organic matter (CDOM), algae, and non-algal particles along with solar radiation, albedo and transmittance at four sea-ice stations in the Gulf of Finland, Baltic Sea. This unique compilation of optical and biological data for Baltic Sea ice was used to build a radiative transfer model describing the light field and the light absorption by algae in 1-cm increments. The maximum quantum yields and photoadaptation of photosynthesis were determined from 14C-incorporatio…

0106 biological sciencesAtmospheric ScienceEnvironmental Engineering010504 meteorology & atmospheric scienceseducationOceanographySolar irradianceAtmospheric sciences01 natural sciencesAtmospheric radiative transfer codesprimary production calculationsbiogeochemistrySea ice14. Life underwaterAbsorption (electromagnetic radiation)1172 Environmental scienceslcsh:Environmental sciences0105 earth and related environmental scienceslcsh:GE1-350geographygeography.geographical_feature_categoryEcologyChemistry010604 marine biology & hydrobiologySea IceGeologyAlbedoGeotechnical Engineering and Engineering GeologyColored dissolved organic matterFast ice13. Climate actionClimatologySea ice thickness
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Compensation of Oxygen Transmittance Effects for Proximal Sensing Retrieval of Canopy–Leaving Sun–Induced Chlorophyll Fluorescence

2018

Estimates of Sun–Induced vegetation chlorophyll Fluorescence (SIF) using remote sensing techniques are commonly determined by exploiting solar and/or telluric absorption features. When SIF is retrieved in the strong oxygen (O 2 ) absorption features, atmospheric effects must always be compensated. Whereas correction of atmospheric effects is a standard airborne or satellite data processing step, there is no consensus regarding whether it is required for SIF proximal–sensing measurements nor what is the best strategy to be followed. Thus, by using simulated data, this work provides a comprehensive analysis about how atmospheric effects impact SIF estimations on proximal sensing, regarding: (…

1171 GeosciencesFLUXspectral fitting method (SFM)AIRBORNE010504 meteorology & atmospheric sciencesScience0211 other engineering and technologiesFlux02 engineering and technologyfraunhofer line discriminator (FLD)Surface pressure01 natural sciencesO2 transmittanceAtmospheric radiative transfer codesatmospheric pressureFIELD SPECTROSCOPYTransmittanceAstrophysics::Solar and Stellar AstrophysicsSPACESpectral resolutionAbsorption (electromagnetic radiation)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingproximal sensing4112 Forestrysun-induced chlorophyll fluorescence (SIF)Atmospheric pressureSTRESS DETECTIONPHOTOSYNTHESISQAtmospheric correctionO-2 transmittanceair temperatureREFLECTANCEsun–induced chlorophyll fluorescence (SIF)Physics::Space Physicssun–induced chlorophyll fluorescence (SIF); proximal sensing; O<sub>2</sub> transmittance; fraunhofer line discriminator (FLD); spectral fitting method (SFM); air temperature; atmospheric pressureLUMINESCENCEGeneral Earth and Planetary SciencesEnvironmental scienceABSORPTION-BANDSAstrophysics::Earth and Planetary AstrophysicsVEGETATIONRemote Sensing
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Towards Quantifying Non-Photosynthetic Vegetation for Agriculture Using Spaceborne Imaging Spectroscopy

2021

Non-photosynthetic vegetation (NPV) has been identified as priority variable in the context of new spaceborne imaging spectroscopy missions. In this study we provide a first attempt to quantify NPV biomass from these unprecedented data streams to be provided by multiple recently launched or planned instruments. A hybrid workflow is proposed including Gaussian process regression (GPR) trained over radiative transfer model (RTM) simulations and applying active learning strategies. A soybean field data set including two dates with NPV measurements on yellow and senescent (brown) plant organs was used for model validation, resulting in relative errors of 13.4%. This prototype retrieval model wa…

2. Zero hunger010504 meteorology & atmospheric sciencesData stream mining0211 other engineering and technologiesEnMAPHyperspectral imagingContext (language use)PRISMA02 engineering and technologyVegetationVegetation functional trait01 natural sciencesLigninImaging spectroscopyAtmospheric radiative transfer codesWorkflowHybrid approacheCHIMEKrigingEnvironmental scienceCelluloseGaussian process regression021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Multitemporal and multiresolution leaf area index retrieval for operational local rice crop monitoring

2016

Abstract This paper presents an operational chain for high-resolution leaf area index (LAI) retrieval from multiresolution satellite data specifically developed for Mediterranean rice areas. The proposed methodology is based on the inversion of the PROSAIL radiative transfer model through the state-of-the-art nonlinear Gaussian process regression (GPR) method. Landsat and SPOT5 data were used for multitemporal LAI retrievals at high-resolution. LAI estimates were validated using time series of in situ LAI measurements collected during the rice season in Spain and Italy. Ground LAI data were collected with smartphones using PocketLAI, a specific phone application for LAI estimation. Temporal…

2. Zero hunger010504 meteorology & atmospheric sciencesMean squared error0211 other engineering and technologiesSoil ScienceGeologyInversion (meteorology)02 engineering and technologyCrop monitoring; Rice; Leaf area index (LAI) retrieval; PROSAIL; Smartphone; Gaussian process regression (GPR); Landsat; SPOT5 Take501 natural sciencesAtmospheric radiative transfer codesKrigingSatellite dataGround-penetrating radarEnvironmental scienceComputers in Earth SciencesLeaf area indexRice crop021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Predicting the time variation of radio emission from MHD simulations of a flaring T-Tauri star

2020

ABSTRACT We model the time-dependent radio emission from a disc accretion event in a T-Tauri star using 3D, ideal magnetohydrodynamic simulations combined with a gyrosynchrotron emission and radiative transfer model. We predict for the first time, the multifrequency (1–1000 GHz) intensity and circular polarization from a flaring T-Tauri star. A flux tube, connecting the star with its circumstellar disc, is populated with a distribution of non-thermal electrons that is allowed to decay exponentially after a heating event in the disc and the system is allowed to evolve. The energy distribution of the electrons, as well as the non-thermal power-law index and loss rate, are varied to see their …

Astrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesAstrophysics::Cosmology and Extragalactic AstrophysicsAstrophysics01 natural sciencesPower lawSpectral linelaw.inventionAtmospheric radiative transfer codeslaw0103 physical sciencesAstrophysics::Solar and Stellar Astrophysics010303 astronomy & astrophysicsSolar and Stellar Astrophysics (astro-ph.SR)Astrophysics::Galaxy AstrophysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)PhysicsFlux tube010308 nuclear & particles physicsAstronomy and AstrophysicsAccretion (astrophysics)StarsT Tauri starAstrophysics - Solar and Stellar AstrophysicsSpace and Planetary ScienceAstrophysics::Earth and Planetary AstrophysicsAstrophysics - High Energy Astrophysical PhenomenaFlareMonthly Notices of the Royal Astronomical Society
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