Search results for "NDI"

showing 10 items of 20275 documents

IGR J17329-2731: The birth of a symbiotic X-ray binary

2018

We report on the results of the multiwavelength campaign carried out after the discovery of the INTEGRAL transient IGR J17329-2731. The optical data collected with the SOAR telescope allowed us to identify the donor star in this system as a late M giant at a distance of 2.7$^{+3.4}_{-1.2}$ kpc. The data collected quasi-simultaneously with XMM-Newton and NuSTAR showed the presence of a modulation with a period of 6680$\pm$3 s in the X-ray light curves of the source. This unveils that the compact object hosted in this system is a slowly rotating neutron star. The broadband X-ray spectrum showed the presence of a strong absorption ($\gg$10$^{23}$ cm$^{-2}$) and prominent emission lines at 6.4 …

010504 meteorology & atmospheric sciencesAstrophysics::High Energy Astrophysical PhenomenaX-ray binaryFOS: Physical sciencesFluxAstrophysicsCompact star01 natural sciencesSpectral linelaw.inventionTelescopeSettore FIS/05 - Astronomia E Astrofisicalaw0103 physical sciencesAstrophysics::Solar and Stellar AstrophysicsEmission spectrum010303 astronomy & astrophysicsAstrophysics::Galaxy Astrophysics0105 earth and related environmental sciencesastro-ph.HEHigh Energy Astrophysical Phenomena (astro-ph.HE)PhysicsAstronomy and AstrophysicsAstronomy and AstrophysicLight curveX-rays: binarieNeutron starX-rays: individuals: IGR J17329-273113. Climate actionSpace and Planetary ScienceAstrophysics - High Energy Astrophysical Phenomena
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Coastal precipitation regimes in Kenya.

1997

Kenya is under the influence of the seasonal reversal of the Indian ocean monsoons. However, its coastal belt, up to about 50 km inland, exhibits original climatic features. Hierarchical clustering...

010504 meteorology & atmospheric sciencesAtmospheric circulation[SHS.GEO] Humanities and Social Sciences/GeographyGeography Planning and Development0207 environmental engineeringSoil resilienceGeology02 engineering and technology[SHS.GEO]Humanities and Social Sciences/GeographySeasonality010502 geochemistry & geophysicsMonsoonmedicine.disease01 natural sciences[ SHS.GEO ] Humanities and Social Sciences/GeographyIndian oceanSea breeze13. Climate actionClimatologymedicineEnvironmental sciencePrecipitationSurface runoff020701 environmental engineering0105 earth and related environmental sciences
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Vegetation vulnerability to drought in Spain

2014

[EN] Frequency of climatic extremes like long duration droughts has increased in Spain over the last century.The use of remote sensing observations for monitoring and detecting drought is justified on the basis that vegetation vigor is closely related to moisture condition. We derive satellite estimates of bio-physical variables such as fractional vegetation cover (FVC) from MODIS/EOS and SEVIRI/MSG time series. The study evaluates the strength of temporal relationships between precipitation and vegetation condition at time-lag and cumulative rainfall intervals. From this analysis, it was observed that the climatic disturbances affected both the growing season and the total amount of vegeta…

010504 meteorology & atmospheric sciencesClimateGeography Planning and Development0211 other engineering and technologiesSPIGrowing seasonlcsh:G1-92202 engineering and technology01 natural sciencesSequíaVegetation coverTropical vegetationEarth and Planetary Sciences (miscellaneous)medicineTeledetecciónPrecipitation021101 geological & geomatics engineering0105 earth and related environmental sciencesSequíasMoistureDroughtÍndices meteorológicos de sequíaVegetaciónVegetation cover15. Life on landRemote sensingVegetation dynamicsAridGeography13. Climate actionClimatologyClimamedicine.symptomVegetation (pathology)lcsh:Geography (General)
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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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Astrometric detection of a low-mass companion orbiting the star AB Doradus

1997

International audience; We report submilliarcsecond-precise astrometric measurements for the late-type star AB Doradus via a combination of VLBI (very long baseline interferometry) and HIPPARCOS data. Our astrometric analysis results in the precise determination of the kinematics of this star, which reveals an orbital motion readily explained as caused by gravitational interaction with a low-mass companion. From the portion of the reÑex orbit covered by our data and using a revised mass of the primary star (0.76 M _) derived from our new value of the parallax (66.3 mas \ n \ 67.2 mas), we Ðnd the dynamical mass of the newly discovered companion to be between 0.08 and 0.11 If accurate photom…

010504 meteorology & atmospheric sciencesGalactic astronomyStellar massBrown dwarfAstrophysicsAstrophysics::Cosmology and Extragalactic Astrophysics01 natural sciencesstars: low-mass0103 physical sciencesVery-long-baseline interferometryAstrophysics::Solar and Stellar Astrophysics010303 astronomy & astrophysicsAstrophysics::Galaxy Astrophysics0105 earth and related environmental sciencesPhysicsstars: individual (AB Doradus)[SDU.ASTR.SR]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Solar and Stellar Astrophysics [astro-ph.SR]Astrophysics::Instrumentation and Methods for AstrophysicsAstronomyAstronomy and AstrophysicsAstrometryInterferometrySpace and Planetary Sciencetechniques: interferometricOrbital motionastrometryAstrophysics::Earth and Planetary Astrophysics[SDU.ASTR.GA]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Galactic Astrophysics [astro-ph.GA]stars: kinematicsLow Massbrown dwarfs
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GIGJ: a crustal gravity model of the Guangdong Province for predicting the geoneutrino signal at the JUNO experiment

2019

Gravimetric methods are expected to play a decisive role in geophysical modeling of the regional crustal structure applied to geoneutrino studies. GIGJ (GOCE Inversion for Geoneutrinos at JUNO) is a 3D numerical model constituted by ~46 x 10$^{3}$ voxels of 50 x 50 x 0.1 km, built by inverting gravimetric data over the 6{\deg} x 4{\deg} area centered at the Jiangmen Underground Neutrino Observatory (JUNO) experiment, currently under construction in the Guangdong Province (China). The a-priori modeling is based on the adoption of deep seismic sounding profiles, receiver functions, teleseismic P-wave velocity models and Moho depth maps, according to their own accuracy and spatial resolution. …

010504 meteorology & atmospheric sciencesGeoneutrinogeophysical uncertaintieInverse transform samplingFOS: Physical sciences01 natural sciencesBayesian methodUpper middle and lower crustStandard deviationNOSouth China BlockmiddlePhysics - GeophysicsMonte Carlo stochastic optimizationGOCE data gravimetric inversionGeophysical uncertaintiesGeochemistry and PetrologyEarth and Planetary Sciences (miscellaneous)Bayesian method; geophysical uncertainties; GOCE data gravimetric inversion; Monte Carlo stochastic optimization; South China Block; upper middle and lower crustImage resolution0105 earth and related environmental sciencesSubdivisionJiangmen Underground Neutrino Observatoryupper and middle and lower crustbusiness.industrySettore FIS/01 - Fisica SperimentaleCrustupperGeodesy[PHYS.PHYS.PHYS-GEN-PH]Physics [physics]/Physics [physics]/General Physics [physics.gen-ph]Geophysics (physics.geo-ph)and lower crustDepth soundingGeophysics13. Climate actionSpace and Planetary SciencebusinessGeologyBayesian method geophysical uncertainties GOCE data gravimetric inversion Monte Carlo stochastic optimization South China Blockupper and middle and lower crust
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Comparing flow resistance law for fixed and mobile bed rills

2019

Rills caused by run-off concentration on erodible hillslopes have very irregular profiles and cross-section shapes. Rill erosion directly depends on the hydraulics of flow in the rills, which may differ greatly from hydraulics of flow in larger and regular channels. In this paper, a recently theoretically deduced rill flow resistance equation, based on a power–velocity profile, was tested experimentally on plots of varying slopes (ranging from 9% to 26%) in which mobile and fixed bed rills were incised. Initially, measurements of flow velocity, water depth, cross-section area, wetted perimeter, and bed slope, carried out in 320 reaches of mobile bed rills and in 165 reaches of fixed rills, …

010504 meteorology & atmospheric sciencesHydraulicsfixed bedFlow (psychology)0207 environmental engineering02 engineering and technology01 natural scienceslaw.inventionWetted perimetersymbols.namesakelawFroude numberSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-Forestalirill hydraulic020701 environmental engineering0105 earth and related environmental sciencesWater Science and Technologygeographysoil erosiongeography.geographical_feature_categoryrill flowplot measurementRillFlow conditionsFlow velocitymobile bedsymbolsflow resistanceSediment transportGeologyHydrological Processes
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Multi-Crop Green LAI Estimation with a New Simple Sentinel-2 LAI Index (SeLI)

2019

The spatial quantification of green leaf area index (LAIgreen), the total green photosynthetically active leaf area per ground area, is a crucial biophysical variable for agroecosystem monitoring. The Sentinel-2 mission is with (1) a temporal resolution lower than a week, (2) a spatial resolution of up to 10 m, and (3) narrow bands in the red and red-edge region, a highly promising mission for agricultural monitoring. The aim of this work is to define an easy implementable LAIgreen index for the Sentinel-2 mission. Two large and independent multi-crop datasets of in situ collected LAIgreen measurements were used. Commonly used LAIgreen indices applied on the Sentinel-2 10 m &times

010504 meteorology & atmospheric sciencesMean squared error0211 other engineering and technologiesRed edge02 engineering and technologylcsh:Chemical technology01 natural sciencesBiochemistryArticleAnalytical Chemistryremote sensingred-edgelcsh:TP1-1185Sensitivity (control systems)Electrical and Electronic EngineeringLeaf area indexInstrumentationImage resolution021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingMathematics2. Zero hungerPixelleaf area indexVegetation15. Life on landcropsAtomic and Molecular Physics and OpticsTemporal resolutionvegetation indicesSentinel-2Sensors
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Optimizing Gaussian Process Regression for Image Time Series Gap-Filling and Crop Monitoring

2020

Image processing entered the era of artificial intelligence, and machine learning algorithms emerged as attractive alternatives for time series data processing. Satellite image time series processing enables crop phenology monitoring, such as the calculation of start and end of season. Among the promising algorithms, Gaussian process regression (GPR) proved to be a competitive time series gap-filling algorithm with the advantage of, as developed within a Bayesian framework, providing associated uncertainty estimates. Nevertheless, the processing of time series images becomes computationally inefficient in its standard per-pixel usage, mainly for GPR training rather than the fitting step. To…

010504 meteorology & atmospheric sciencesMean squared errorComputer science0211 other engineering and technologiesImage processing02 engineering and technologycomputer.software_genre01 natural scienceslcsh:AgricultureKrigingTime series021101 geological & geomatics engineering0105 earth and related environmental sciences2. Zero hungerHyperparameterPixelSeries (mathematics)lcsh:SGaussian processes regressionSatellite Image Time SeriesData miningtime seriesSentinel-2optimizationAgronomy and Crop Sciencecomputercrop monitoringphenology indicatorsAgronomy
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Comparison of SMOS and SMAP soil moisture retrieval approaches using tower-based radiometer data over a vineyard field

2014

International audience; The objective of this study was to compare several approaches to soil moisture (SM) retrieval using l-band microwave radiometry. The comparison was based on a brightness temperature (TB) data set acquired since 2010 by the L-band radiometer ELBARA-II over a vineyard field at the Valencia Anchor Station (VAS) site. ELBARA-II, provided by the European Space Agency (ESA) within the scientific program of the SMOS (Soil Moisture and Ocean Salinity) mission, measures multiangular TB data at horizontal and vertical polarization for a range of incidence angles (30°–60°). Based on a three year data set (2010–2012), several SM retrieval approaches developed for spaceborne miss…

010504 meteorology & atmospheric sciencesMean squared errorMeteorology[SDE.MCG]Environmental Sciences/Global Changes0211 other engineering and technologiesSoil Science02 engineering and technologyAstrophysics::Cosmology and Extragalactic Astrophysics01 natural sciencesPhysics::Geophysics14. Life underwaterComputers in Earth SciencesTime series021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingAtmospheric soundingValencia Anchor StationRadiometerGeologyInversion (meteorology)SMAP15. Life on landBrightness temperatureSoil waterEnvironmental scienceRadiometrySoil moisture retrievalELBARA[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSMOSRemote Sensing of Environment
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