Search results for " Satellite"

showing 10 items of 155 documents

The BepiColombo MORE gravimetry and rotation experiments with the ORBIT14 software

2016

The BepiColombo mission to Mercury is an ESA/JAXA cornerstone mission, consisting of two spacecraft in orbit around Mercury addressing several scientific issues. One spacecraft is the Mercury Planetary Orbiter, with full instrumentation to perform radio science experiments. Very precise radio tracking from Earth, on-board accelerometer and optical measurements will provide large data sets. From these it will be possible to study the global gravity field of Mercury and its tidal variations, its rotation state and the orbit of its centre of mass. With the gravity field and rotation state, it is possible to constrain the internal structure of the planet. With the orbit of Mercury, it is possib…

010504 meteorology & atmospheric sciencesAccelerometer01 natural scienceslaw.inventionmethods: numericalGravitationOrbiterMethods: numerical; Planets and satellites: individual: Mercury; Space vehicles: instruments; Astronomy and Astrophysics; Space and Planetary ScienceGravitational fieldmethods: numerical – space vehicles: instruments – planets and satellites: individual: Mercurylaw0103 physical sciencesGravimetryAerospace engineeringspace vehicles: instrumentsSettore MAT/07 - Fisica Matematica010303 astronomy & astrophysics0105 earth and related environmental sciencesRemote sensingRadio SciencePhysicsSpacecraftbusiness.industryAstronomy and AstrophysicsSpace and Planetary SciencePhysics::Space PhysicsLove numberAstrophysics::Earth and Planetary Astrophysicsbusinessplanets and satellites: individual: Mercury
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Cloud detection on the Google Earth engine platform

2017

The vast amount of data acquired by current high resolution Earth observation satellites implies some technical challenges to be faced. Google Earth Engine (GEE) platform provides a framework for the development of algorithms and products built over this data in an easy and scalable manner. In this paper, we take advantage of the GEE platform capabilities to exploit the wealth of information in the temporal dimension by processing a long time series of satellite images. A cloud detection algorithm for Landsat-8, which uses previous images of the same location to detect clouds, is implemented and tested on the GEE platform.

010504 meteorology & atmospheric sciencesComputer scienceReal-time computingScalability0211 other engineering and technologiesCloud detectionSatellite02 engineering and technologyDimension (data warehouse)Earth observation satellite01 natural sciences021101 geological & geomatics engineering0105 earth and related environmental sciences2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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The size, shape, density and ring of the dwarf planet Haumea from a stellar occultation

2017

Ortiz, José Luis et. al.

010504 meteorology & atmospheric sciencesEuropean communityTrans Neptunian ObjectDwarf planetHaumeaFOS: Physical sciencesLibrary scienceshape01 natural sciencessizedwarf planetNeptuneFísica Aplicada0103 physical sciencesHaumeamedia_common.cataloged_instanceEuropean unionInstrumentation and Methods for Astrophysics (astro-ph.IM)010303 astronomy & astrophysicsComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesmedia_commonEarth and Planetary Astrophysics (astro-ph.EP)Physics[PHYS]Physics [physics]density2003 EL61 ; Kuiper-belt ; photometric-observations ; collisional family ; object ; bodies ; albedo ; satellites ; UranusDwarf planetsMultidisciplinaryEuropean researchAsteroidTrans-NeptunianAstronomyStellar occultationMoons of HaumeaStellar occultationstellar occultationAstrophysics::Earth and Planetary AstrophysicsAstrophysics - Instrumentation and Methods for Astrophysics[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]ringAstrophysics - Earth and Planetary Astrophysics
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Transferring deep learning models for cloud detection between Landsat-8 and Proba-V

2020

Abstract Accurate cloud detection algorithms are mandatory to analyze the large streams of data coming from the different optical Earth observation satellites. Deep learning (DL) based cloud detection schemes provide very accurate cloud detection models. However, training these models for a given sensor requires large datasets of manually labeled samples, which are very costly or even impossible to create when the satellite has not been launched yet. In this work, we present an approach that exploits manually labeled datasets from one satellite to train deep learning models for cloud detection that can be applied (or transferred) to other satellites. We take into account the physical proper…

010504 meteorology & atmospheric sciencesExploitComputer sciencebusiness.industryDeep learning0211 other engineering and technologiesCloud detectionCloud computing02 engineering and technologyEarth observation satellitecomputer.software_genre01 natural sciencesConvolutional neural networkAtomic and Molecular Physics and OpticsComputer Science ApplicationsSatelliteData miningArtificial intelligenceComputers in Earth SciencesbusinessTransfer of learningEngineering (miscellaneous)computer021101 geological & geomatics engineering0105 earth and related environmental sciencesISPRS Journal of Photogrammetry and Remote Sensing
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Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress

2019

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF – especially from space – is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using high-resolution spectral sensors in …

010504 meteorology & atmospheric sciencesFIS/06 - FISICA PER IL SISTEMA TERRA E PER IL MEZZO CIRCUMTERRESTRE0208 environmental biotechnologySoil ScienceReview02 engineering and technologyPhotochemical Reflectance Index01 natural sciencesArticleGEO/11 - GEOFISICA APPLICATASIF retrieval methodsRadiative transfer modellingRadiative transfer910 Geography & travelComputers in Earth SciencesChlorophyll fluorescence1111 Soil Science1907 GeologyAirborne instruments0105 earth and related environmental sciencesRemote sensingStress detectionGEO/12 - OCEANOGRAFIA E FISICA DELL'ATMOSFERA1903 Computers in Earth SciencesPrimary productionGeologyVegetationPassive optical techniquesField (geography)020801 environmental engineeringGEO/10 - GEOFISICA DELLA TERRA SOLIDA10122 Institute of GeographySun-induced fluorescenceRemote sensing (archaeology)Sun-induced fluorescence Steady-state photosynthesis Stress detection Radiative transfer modelling SIF retrieval methods. Satellite sensors Airborne instruments Applications Terrestrial vegetation Passive optical techniques. ReviewApplicationsTerrestrial vegetationEnvironmental scienceSatelliteSteady-state photosynthesisSatellite sensors
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GJ 357 b: A Super-Earth Orbiting an Extremely Inactive Host Star

2020

Aims. In this paper we present a deep X-ray observation of the nearby M dwarf GJ 357 and use it to put constraints on the atmospheric evolution of its planet, GJ 357 b. We also analyse the systematic errors in the stellar parameters of GJ 357 in order to see how they affect the perceived planetary properties. Methods. By comparing the observed X-ray luminosity of its host star, we estimate the age of GJ 357 b as derived from a recent XMM-Newton observation (log Lx [erg s-1] = 25.73), with Lx-age relations for M dwarfs. We find that GJ 357 presents one of the lowest X-ray activity levels ever measured for an M dwarf, and we put a lower limit on its age of 5 Gyr. Using this age limit, we perf…

010504 meteorology & atmospheric sciencesOpacityFOS: Physical sciencesAstrophysicsStar (graph theory)01 natural sciencesLuminosityPlanet0103 physical sciences010303 astronomy & astrophysicsstars [X rays]Solar and Stellar Astrophysics (astro-ph.SR)physical evolution [Planets and satellites]0105 earth and related environmental sciencesEnvelope (waves)PhysicsEarth and Planetary Astrophysics (astro-ph.EP)Secondary atmosphereSuper-EarthAstronomy and AstrophysicsRadiusPlanet star interactionsAstrophysics - Solar and Stellar Astrophysics13. Climate actionSpace and Planetary Scienceterrestrial planets [Planets and satellites]atmospheres [Planets and satellites]Astrophysics - Earth and Planetary Astrophysics
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The GAPS Programme with HARPS-N at TNG: . Atmospheric Rossiter-McLaughlin effect and improved parameters of KELT-9b

2019

In the framework of the GAPS project, we observed the planet-hosting star KELT-9 (A-type star, VsinI$\sim$110 km/s) with the HARPS-N spectrograph at the TNG. In this work we analyse the spectra and the extracted radial velocities (RVs), to constrain the physical parameters of the system and to detect the planetary atmosphere of KELT-9b. We extracted from the high-resolution optical spectra the mean stellar line profiles with an analysis based on the Least Square Deconvolution technique. Then, we computed the stellar RVs with a method optimized for fast rotators, by fitting the mean stellar line profile with a purely rotational profile instead of using a Gaussian function. The new spectra an…

010504 meteorology & atmospheric sciencesRossiter–McLaughlin effectFOS: Physical sciencesAstrophysics01 natural sciencesSpectral lineAtmospheretechniques: radial velocities0103 physical sciencesAstrophysics::Solar and Stellar Astrophysicsplanetary systems010303 astronomy & astrophysicsSolar and Stellar Astrophysics (astro-ph.SR)0105 earth and related environmental sciencesEarth and Planetary Astrophysics (astro-ph.EP)planets and satellites: atmospheresPhysicsSettore FIS/05Astronomy and AstrophysicsPlanetary systemstars: individual: KELT-9ExoplanetRadial velocityAmplitudeAstrophysics - Solar and Stellar AstrophysicsSpace and Planetary ScienceAstrophysics::Earth and Planetary AstrophysicsPlanetary masstechniques: spectroscopicAstrophysics - Earth and Planetary Astrophysics
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Global-Scale Evaluation of Roughness Effects on C-Band AMSR-E Observations

2015

Quantifying roughness effects on ground surface emissivity is an important step in obtaining high-quality soil moisture products from large-scale passive microwave sensors. In this study, we used a semi-empirical method to evaluate roughness effects (parameterized here by the parameter) on a global scale from AMSR-E (Advanced Microwave Scanning Radiometer for EOS) observations. AMSR-E brightness temperatures at 6.9 GHz obtained from January 2009 to September 2011, together with estimations of soil moisture from the SMOS (Soil Moisture and Ocean Salinity) L3 products and of soil temperature from ECMWF’s (European Centre for Medium-range Weather Forecasting) were used as inputs in a retrieval…

010504 meteorology & atmospheric sciencestélédétectionScience0211 other engineering and technologiesWeather forecasting[SDU.STU]Sciences of the Universe [physics]/Earth SciencesElectromagnétismesoil surface roughness02 engineering and technologySurface finishcomputer.software_genredonnée satellite01 natural sciencesSciences de la TerreNormalized Difference Vegetation Indexsoil moisture;soil surface roughness;AMSR-EElectromagnetismEmissivitySurface roughnessTraitement du signal et de l'image14. Life underwaterWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometercapteur smosQSignal and Image processingradiométrie microondesVegetationAMSR-E15. Life on land[SPI.ELEC]Engineering Sciences [physics]/ElectromagnetismEarth SciencesGeneral Earth and Planetary SciencesEnvironmental sciencesoil moisturecomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingRemote Sensing
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Modelling forest decline using SMOS soil moisture and vegetation optical depth

2018

Global change is increasing the risk of forest decline worldwide, impacting carbon and water cycles. Hence, there is an urgent need for predicting forest decline occurrence. To that purpose, this study links forest decline events in Catalonia, detected by the DEBOSCAT forest monitoring program, with information from the Soil Moisture and Ocean Salinity (SMOS) satellite. Firstly, this study reviews the role of the SMOS soil moisture in a previous forest decline episode occurred in 2012, where the authors concluded that dry soils increased the probability of observing decline in broadleaved forests. Secondly, the present study detects that forest decline in 2012 and 2016 was linked to very dr…

0106 biological sciences010504 meteorology & atmospheric sciencesArtificial satellites in navigationClimate changeGlobal change010603 evolutionary biology01 natural sciencesMonitoring programForest declineSalinitySatèl·lits artificials en navegacióHydric soil:Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció [Àrees temàtiques de la UPC]Soil waterEnvironmental scienceClimate changeVegetation optical depthPhysical geography:Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços [Àrees temàtiques de la UPC]Soil moistureSòls -- HumitatWater cycleWater content0105 earth and related environmental sciencesSMOS
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Spatial and Temporal Variability in Migration of a Soaring Raptor Across Three Continents

2019

Disentangling individual- and population-level variation in migratory movements is necessary for understanding migration at the species level. However, very few studies have analyzed these patterns across large portions of species' distributions. We compiled a large telemetry dataset on the globally endangered egyptian vulture neophron percnopterus (94 individuals, 188 completed migratory journeys), tracked across similar to 70% of the species' global range, to analyze spatial and temporal variability of migratory movements within and among individuals and populations. We found high migratory connectivity at large spatial scales (i.e., different subpopulations showed little overlap in winte…

0106 biological sciences0301 basic medicineSatellite trackingconservation biologyEnvironmental changeRange (biology)GPSPopulationlcsh:EvolutionEndangered speciesPhenotypic plasticity010603 evolutionary biology01 natural sciencesphenotypic plasticityMovement ecology03 medical and health sciencesmigration connectivitylcsh:QH540-549.5Flywaybiology.animalNeophron percnopteruslcsh:QH359-425ZoologíaeducationEcology Evolution Behavior and SystematicsVulture2. Zero hunger[SDV.EE]Life Sciences [q-bio]/Ecology environmenteducation.field_of_studyEcologybiologyConservation biologyEcologysatellite tracking[SDV.BA]Life Sciences [q-bio]/Animal biology15. Life on landMigration connectivity; Neophron percnopterus; Conservation biology; Movement ecology; Satellite tracking; GPS; Phenotypic plasticityBiology; Environmental sciences and ecology030104 developmental biologyGeographymovement ecologyNeophron percnopteruslcsh:EcologyConservation biologyMigration connectivity
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