Search results for "ATIS"

showing 10 items of 15276 documents

Automatic emulator and optimized look-up table generation for radiative transfer models

2017

This paper introduces an automatic methodology to construct emulators for costly radiative transfer models (RTMs). The proposed method is sequential and adaptive, and it is based on the notion of the acquisition function by which instead of optimizing the unknown RTM underlying function we propose to achieve accurate approximations. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of the method in toy examples and for the construction of an…

010504 meteorology & atmospheric sciencesComputer scienceFlatness (systems theory)0211 other engineering and technologiesAtmospheric correctionSampling (statistics)02 engineering and technologyFunction (mathematics)Atmospheric model01 natural sciencessymbols.namesakeKernel (statistics)Lookup tableRadiative transfersymbolsGaussian process emulatorGaussian processAlgorithm021101 geological & geomatics engineering0105 earth and related environmental sciencesInterpolation2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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Multioutput Automatic Emulator for Radiative Transfer Models

2018

This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…

010504 meteorology & atmospheric sciencesComputer scienceFlatness (systems theory)Bayesian optimizationSampling (statistics)02 engineering and technologyFunction (mathematics)Atmospheric model01 natural sciencessymbols.namesakeSampling (signal processing)0202 electrical engineering electronic engineering information engineeringsymbolsRadiative transfer020201 artificial intelligence & image processingGaussian process emulatorGaussian processAlgorithm0105 earth and related environmental sciencesInterpolationIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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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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Anticipating the impact of pitfalls in kinetic biodegradation parameter estimation from substrate depletion curves of organic pollutants

2019

[EN] Accurate and reliable estimation of kinetic parameters of pollutant biodegradation processes is essential for environmental and health risk assessment. Common biodegradation models proposed in the literature, such as the nonlinear Monod equation and its simplified versions (e.g. Michaelis-Menten-like and first-order equations), are problematic in terms of accuracy of kinetic parameters due to the parameter correlation. However, a comparison between these models in terms of accuracy and reliability, related to data imprecision, has not been performed in the literature. This task is necessary, mainly because the model selection cannot be straightforward, as shown in this work. To facilit…

010504 meteorology & atmospheric sciencesComputer scienceHealth Toxicology and Mutagenesis010501 environmental sciencesToxicology01 natural sciencesRisk AssessmentModelling depletion curveMonod equationLimit (mathematics)Reliability (statistics)0105 earth and related environmental sciencesPollutantObservational errorEstimation theoryModel selectionReproducibility of ResultsModel comparisonGeneral MedicineModels TheoreticalPollutionNonlinear systemKineticsBiodegradation EnvironmentalParameter estimationsBiodegradationEnvironmental PollutantsBiochemical engineeringPitfallsAlgorithms
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Soil organic carbon stock on the Majorca Island: temporal change in agricultural soil over the last 10 years

2019

8 Pags.- 5 Tabls.- 3 Figs.

010504 meteorology & atmospheric sciencesConservation agricultureLand managementMediterranean soil organic carbonspatial variationSpatial and temporal variationCarbon sequestration01 natural sciencestemporal changeSoil managementMediterranean soil carbonsoil carbon sequestrationAgricultural landGeostatistics0105 earth and related environmental sciencesEarth-Surface ProcessesAgroforestrySoil organic matter04 agricultural and veterinary sciencesSoil carbonCrop rotationMajorca carbon storage040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental scienceCrop management
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Efficient remote sensing image classification with Gaussian processes and Fourier features

2017

This paper presents an efficient methodology for approximating kernel functions in Gaussian process classification (GPC). Two models are introduced. We first include the standard random Fourier features (RFF) approximation into GPC, which largely improves the computational efficiency and permits large scale remote sensing data classification. In addition, we develop a novel approach which avoids randomly sampling a number of Fourier frequencies, and alternatively learns the optimal ones using a variational Bayes approach. The performance of the proposed methods is illustrated in complex problems of cloud detection from multispectral imagery.

010504 meteorology & atmospheric sciencesContextual image classificationComputer scienceMultispectral imageData classification0211 other engineering and technologiesSampling (statistics)02 engineering and technology01 natural sciencessymbols.namesakeBayes' theoremFourier transformKernel (statistics)symbolsGaussian process021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Diving into exoplanets: Are water seas the most common?

2019

One of the basic tenets of exobiology is the need for a liquid substratum in which life can arise, evolve, and develop. The most common version of this idea involves the necessity of water to act as such a substratum, both because that is the case on Earth and because it seems to be the most viable liquid for chemical reactions that lead to life. Other liquid media that could harbor life, however, have occasionally been put forth. In this work, we investigate the relative probability of finding superficial seas on rocky worlds that could be composed of nine different, potentially abundant, liquids, including water. We study the phase space size of habitable zones defined for those substance…

010504 meteorology & atmospheric sciencesExtraterrestrial EnvironmentMilky WayOrigin of LifePlanets01 natural sciencesAstrobiologyAbundance (ecology)Planet0103 physical sciencesExobiology010303 astronomy & astrophysicsEcosystem0105 earth and related environmental sciencesProbabilityExoseasModels StatisticalHabitable zoneExoplanetsLead (sea ice)WaterAgricultural and Biological Sciences (miscellaneous)ExoplanetTidal lockingSpace and Planetary ScienceSolventsAstrophysics::Earth and Planetary AstrophysicsRelative probabilityCircumstellar habitable zoneGeology
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Geochemistry of Noble Gases and CO2 in Fluid Inclusions From Lithospheric Mantle Beneath Wilcza Góra (Lower Silesia, Southwest Poland)

2018

Knowledge of the products originating from the subcontinental lithospheric mantle (SCLM) is crucial for constraining the geochemical features and evolution of the mantle. This study investigated the chemistry and isotope composition (noble gases and CO2 ) of fluid inclusions (FI) from selected mantle xenoliths originating from Wilcza Góra (Lower Silesia, southwest Poland), with the aim of integrating their petrography and mineral chemistry. Mantle xenoliths are mostly harzburgites and sometimes bear amphiboles, and are brought to the surface by intraplate alkaline basalts that erupted outside the north-easternmost part of the Eger (Ohře) Rift in Lower Silesia. Olivine (Ol) is classified int…

010504 meteorology & atmospheric sciencesGeochemistryengineering.material010502 geochemistry & geophysics01 natural sciencesMantle (geology)chemistry.chemical_compoundNoble gasenoble gases CO2 fluid inclusions mantle xenoliths European mantle SCLM MORB metasomatismFluid inclusionsMetasomatismlcsh:ScienceAmphibole0105 earth and related environmental sciencesBasaltEuropean mantleOlivineSCLMmetasomatismPartial meltingAmbientaleFluid inclusionMORBMantle xenolithSilicatemantle xenolithsfluid inclusionschemistrynoble gasesengineeringGeneral Earth and Planetary Scienceslcsh:QCO2Geology
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Gas mass derived by infrasound and UV cameras: Implications for mass flow rate

2016

Abstract Mass Flow Rate is one of the most crucial eruption source parameter used to define magnitude of eruption and to quantify the ash dispersal in the atmosphere. However, this parameter is in general difficult to be derived and no valid technique has been developed yet to measure it in real time with sufficient accuracy. Linear acoustics has been applied to infrasonic pressure waves generated by explosive eruptions to indirectly estimate the gas mass erupted and then the mass flow rate. Here, we test on Stromboli volcano (Italy) the performance of such methodology by comparing the acoustic derived results with independent gas mass estimates obtained with UV cameras, and constraining th…

010504 meteorology & atmospheric sciencesInfrasoundMass flowVolcano acousticMagnitude (mathematics)ThrustGeophysicsMass flow rate010502 geochemistry & geophysics01 natural sciencesAtmosphereGeophysicsSulphur dioxide cameraThermal imagery13. Climate actionGeochemistry and PetrologyMass flow rateRange (statistics)WaveformGeology0105 earth and related environmental sciencesJournal of Volcanology and Geothermal Research
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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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