Search results for "Rumen"

showing 10 items of 5946 documents

Automotive Radar in a UAV to Assess Earth Surface Processes and Land Responses

2020

The use of unmanned aerial vehicles (UAVs) in earth science research has drastically increased during the last decade. The reason being innumerable advantages to detecting and monitoring various environmental processes before and after certain events such as rain, wind, flood, etc. or to assess the current status of specific landforms such as gullies, rills, or ravines. The UAV equipped sensors are a key part to success. Besides commonly used sensors such as cameras, radar sensors are another possibility. They are less known for this application, but already well established in research. A vast number of research projects use professional radars, but they are expensive and difficult to hand…

010504 meteorology & atmospheric sciencesComputer scienceUAVReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION0211 other engineering and technologiesComputerApplications_COMPUTERSINOTHERSYSTEMS77 GHz02 engineering and technologylcsh:Chemical technology01 natural sciencesBiochemistryArticleAnalytical Chemistrylaw.inventionARS-408lawlcsh:TP1-1185ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMSElectrical and Electronic EngineeringRadarInstrumentationARS-404021101 geological & geomatics engineering0105 earth and related environmental sciencesRadarAtomic and Molecular Physics and OpticsEarth surfaceAutomotive radarKey (cryptography)Sensors
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Estimating Missing Information by Cluster Analysis and Normalized Convolution

2018

International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.

010504 meteorology & atmospheric sciencesComputer sciencemedia_common.quotation_subjectReal-time computingEnergy Engineering and Power Technology02 engineering and technologyIterative reconstructionsmart city dealsCluster (spacecraft)01 natural sciencesIndustrial and Manufacturing Engineeringnormalized convolutionstandard clustering technique[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]ConvolutionArtificial IntelligenceSmart city11. Sustainability0202 electrical engineering electronic engineering information engineeringLimit (mathematics)SimplicityCluster analysisInstrumentationad-hoc sensors0105 earth and related environmental sciencesmedia_commonSettore INF/01 - InformaticaRenewable Energy Sustainability and the EnvironmentComputer Science Applications1707 Computer Vision and Pattern Recognitionenvironmental informationmissing informationComputer Networks and CommunicationKernel (image processing)020201 artificial intelligence & image processingcluster analysis2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)
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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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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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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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On the timing between terrestrial gamma ray flashes, radio atmospherics, and optical lightning emission

2017

On 25 October 2012 the Reuven Ramaty High Energy Solar Spectroscope Imager (RHESSI) and the Tropical Rainfall Measuring Mission (TRMM) satellites passed over a thunderstorm on the coast of Sri Lanka. RHESSI observed a terrestrial gamma ray flash (TGF) originating from this thunderstorm. Optical measurements of the causative lightning stroke were made by the lightning imaging sensor (LIS) on board TRMM. The World Wide Lightning Location Network (WWLLN) detected the very low frequency (VLF) radio emissions from the lightning stroke. The geolocation from WWLLN, which we also assume is the TGF source location, was in the convective core of the cloud. By using new information about both RHESSI a…

010504 meteorology & atmospheric sciencesGamma rayFOS: Physical sciencesRadio atmosphericLight curve01 natural sciencesLightningSpace Physics (physics.space-ph)GeophysicsPhysics - Space PhysicsSpace and Planetary Science0103 physical sciencesThunderstormEnvironmental scienceAtmosphericsVery low frequencyAstrophysics - Instrumentation and Methods for AstrophysicsInstrumentation and Methods for Astrophysics (astro-ph.IM)010303 astronomy & astrophysics0105 earth and related environmental sciencesTerrestrial gamma-ray flashRemote sensingJournal of Geophysical Research: Space Physics
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HF radar for wind waves measurements in the Malta-Sicily Channel

2018

Abstract The CALYPSO HF radar network is a permanent and fully operational observing system currently composed of four CODAR SeaSonde stations. The system is providing real-time hourly maps of sea surface currents and waves data in the Malta-Sicily Channel. The present work aims to compare significant wave height measurements by HF Radar to wave data from numerical models and satellite altimeter. This is the first time that this set of wave data are analysed since the four HF radars were installed between 2012 and 2015. Results suggest that CODAR HF Radar wave data are a reliable source of wave information even in the case of extreme events, providing an avenue to improve and complete the o…

010504 meteorology & atmospheric sciencesHF radar010505 oceanographyWave modelApplied MathematicsInstrumentationOcean currentMalta-Sicily ChannelWave parameterCondensed Matter Physics01 natural sciencesSatellite altimeterlaw.inventionWave modellawWind waveSatellite altimeterElectrical and Electronic EngineeringRadarSignificant wave heightInstrumentationGeology0105 earth and related environmental sciencesRemote sensingCommunication channelMeasurement
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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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On the Dependence of Cirrus Parametrizations on the Cloud Origin

2019

<p>Particle size distributions (PSDs) for cirrus clouds are important for both climate models as well as many remote sensing retrieval methods. Therefore, PSD parametrizations are required. This study presents parametrizations of Arctic cirrus PSDs. The dataset used for this purpose originates from balloon-borne measurements carried out during winter above Kiruna (Sweden), i.e. north of the Arctic circle. The observations are sorted into two types of cirrus cloud origin, either in-situ or liquid. The cloud origin describes the formation pathway of the ice particles. At temperatures below −38 °C, ice particles form in-situ from solution or ice nuclea…

010504 meteorology & atmospheric sciencesMeteorologyMeteorologi och atmosfärforskningAerospace EngineeringCloud computing010502 geochemistry & geophysics01 natural sciencescirrus cloudsddc:550Parametrization (atmospheric modeling)Astrophysics::Galaxy AstrophysicsPhysics::Atmospheric and Oceanic Physics0105 earth and related environmental sciencesbusiness.industryAstrophysics::Instrumentation and Methods for AstrophysicsparametrizationData setRymd- och flygteknikGeophysicsArcticice particle size distribution (PSD)Meteorology and Atmospheric SciencesPhysics::Space PhysicsGeneral Earth and Planetary SciencesEnvironmental scienceCirrusbusinessArctic cloud origin
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A multisensor fusion approach to improve LAI time series

2011

International audience; High-quality and gap-free satellite time series are required for reliable terrestrial monitoring. Moderate resolution sensors provide continuous observations at global scale for monitoring spatial and temporal variations of land surface characteristics. However, the full potential of remote sensing systems is often hampered by poor quality or missing data caused by clouds, aerosols, snow cover, algorithms and instrumentation problems. A multisensor fusion approach is here proposed to improve the spatio-temporal continuity, consistency and accuracy of current satellite products. It is based on the use of neural networks, gap filling and temporal smoothing techniques. …

010504 meteorology & atmospheric sciencesMeteorologytélédétectionsatellite0211 other engineering and technologiesSoil Scienceréseau neuronal02 engineering and technology01 natural sciencessuivi de culturesInstrumentation (computer programming)Computers in Earth SciencesLeaf area index021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingVegetationGeologyVegetationData fusionLAI time seriesSensor fusionMissing dataLAI time series;Vegetation;Modis;Temporal smoothing;Gap filling;Data fusionqualité des données13. Climate actionAutre (Sciences de l'ingénieur)Gap filling[SDE]Environmental SciencesEnvironmental scienceSatelliteModisTemporal smoothingScale (map)Smoothing
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