Search results for "Radiometer"

showing 10 items of 272 documents

Towards a long-term dataset of ELBARA-II measurements assisting SMOS level-3 land product and algorithm validation at the Valencia Anchor Station

2015

[EN] The Soil Moisture and Ocean Salinity (SMOS) mission was launched on 2nd November 2009 with the objective of providing global estimations of soil moisture and sea salinity. The main activity of the Valencia Anchor Station (VAS) is currently to assist in a long-term validation of SMOS land products. This study focus on a level 3 SMOS data validation with in situ measurements carried out in the period 2010-2012 over the VAS. ELBARA-II radiometer is placed in the VAS area, observing a vineyard field considered as representative of a major proportion of an area of 50×50 km, enough to cover a SMOS footprint. Brightness temperatures (TB) acquired by ELBARA-II have been compared to those obser…

010504 meteorology & atmospheric sciencesMeteorologyGeography Planning and Development0211 other engineering and technologiesData validationlcsh:G1-92202 engineering and technology01 natural sciencesVineyardSoil roughnessFootprintEarth and Planetary Sciences (miscellaneous)Vegetation optical depth14. Life underwaterPrecipitationWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRadiometerHumedad del suelobrightness temperature ELBARA-II L-MEB SMOS SMOS level 3 data soil moisture soil roughness Valencia Anchor Station vegetation optical depth15. Life on landEspesor óptico de la vegetaciónTerm (time)GeographyL-MEB13. Climate actionBrightness temperatureRugosidad del sueloTemperatura de brilloSoil moistureBrightness temperaturelcsh:Geography (General)
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NPP VIIRS land surface temperature product validation using worldwide observation networks.

2013

International audience; Thermal infrared satellite observations of the Earth's surface are key components in estimating the surface skin temperature over global land areas. This work presents validation methodologies to estimate the quantitative uncertainty in Land Surface Temperature (LST) product derived from the Visible Infrared Imager Radiometer Suite (VIIRS) onboard Suomi National Polar-orbiting Partnership (NPP) using ground-based measurements currently made operationally at many field and weather stations around the world. Over heterogeneous surfaces in terms of surface types or biophysical properties (e.g., vegetation density, emissivity), the validation protocol accounts for land s…

010504 meteorology & atmospheric sciencesMeteorologyLand surface temperature0211 other engineering and technologies02 engineering and technology01 natural sciencesIndex Terms— Land Surface TemperaturePhysics::Geophysics[SDU] Sciences of the Universe [physics]EmissivityProduct (category theory)ComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingvalidationThermal infraredRadiometerspatial heterogeneityVegetationNPP VIIRS13. Climate actionground-based LST[SDU]Sciences of the Universe [physics][SDE]Environmental SciencesEnvironmental scienceSatelliteSpatial variability
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Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values

2016

Land Surface Temperature (LST) as provided by remote sensing onboard satellites is a key parameter for a number of applications in Earth System studies, such as numerical modelling or regional estimation of surface energy and water fluxes. In the case of Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra or Aqua, pixels have resolutions near 1 km 2 , LST values being an average of the real subpixel variability of LST, which can be significant for heterogeneous terrain. Here, we use Landsat 7 LST decametre-scale fields to evaluate the temporal and spatial variability at the kilometre scale and compare the resulting average values to those provided by MODIS for the same obser…

010504 meteorology & atmospheric sciencesMeteorologyLandsat 7Science0211 other engineering and technologiesland surface temperatureTerrain02 engineering and technology01 natural sciencesNet radiometertime-space variabilityTermodinàmicaSuperfícies (Fisica)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingGround truthRadiometerQSubpixel renderingsurface heterogeneitysurface heterogeneity; land surface temperature; MODIS; Landsat 7; time-space variability; ground truthMODISGeneral Earth and Planetary SciencesEnvironmental scienceSpatial variabilityModerate-resolution imaging spectroradiometerScale (map)ground truthRemote Sensing
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Evaluation of the MODIS Albedo product over a heterogeneous agricultural area

2013

In this article, the Moderate Resolution Imaging Spectroradiometer MODIS Bidirectional Reflectance Distribution Function BRDF/Albedo product MCD43 is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction EODIX project campaign, which was developed in Barrax Spain in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal RTLSR which corresponds to the MODIS BRDF algorithm and the RossThick-Maignan-LiSparse-Reciprocal RTLSR-HS, were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner AHS sensor. During the campaign, airborne im…

010504 meteorology & atmospheric sciencesMeteorologyPixel0211 other engineering and technologiesHyperspectral imaging02 engineering and technologyAlbedo01 natural sciencesGeneral Earth and Planetary SciencesEnvironmental scienceSatelliteSatellite imageryModerate-resolution imaging spectroradiometerBidirectional reflectance distribution functionZenith021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingInternational Journal of Remote Sensing
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PHYSICS-based retrieval of scattering albedo and vegetation optical depth using multi-sensor data integration

2017

Vegetation optical depth and scattering albedo are crucial parameters within the widely used τ-ω model for passive microwave remote sensing of vegetation and soil. A multi-sensor data integration approach using ICESat lidar vegetation heights and SMAP radar as well as radiometer data enables a direct retrieval of the two parameters on a physics-derived basis. The crucial step within the retrieval methodology is the calculus of the vegetation scattering coefficient KS, where one exact and three approximated solutions are provided. It is shown that, when using the assumption of a randomly oriented volume, the backscatter measurements of the radar provide a sufficient first order estimate and …

010504 meteorology & atmospheric sciencesScattering albedo0208 environmental biotechnologyradiometry02 engineering and technologyretrieval methodologycomputer.software_genre01 natural scienceslaw.inventionlawremote sensing by radarRadaractive-passive microwavesPhysics::Atmospheric and Oceanic PhysicsIndexespassive microwave remote sensingRemote sensingremote sensing by laser beamGeographyLidaroptical radarcrucial parametersmedicine.symptomvegetation scattering coefficientData integrationBackscattervegetation mappingta1171τ-ω modelsoilPhysics::GeophysicsICESat lidar vegetation heightsvegetationmedicineVegetation optical depthbackscatter0105 earth and related environmental sciencesRemote sensingsensor fusionRadiometerScatteringnovel multisensor approachSMAPAlbedoMulti-sensor020801 environmental engineeringradiometer dataVegetation (pathology)multisensor data integration approachcomputerICESatalbedo
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Sun-Induced Chlorophyll Fluorescence I: Instrumental Considerations for Proximal Spectroradiometers

2019

Growing interest in the proximal sensing of sun-induced chlorophyll fluorescence (SIF) has been boosted by space-based retrievals and up-coming missions such as the FLuorescence EXplorer (FLEX). The European COST Action ES1309 “Innovative optical tools for proximal sensing of ecophysiological processes” (OPTIMISE, ES1309; https://optimise.dcs.aber.ac.uk/) has produced three manuscripts addressing the main current challenges in this field. This article provides a framework to model the impact of different instrument noise and bias on the retrieval of SIF; and to assess uncertainty requirements for the calibration and characterization of state-of-the-art SIF-oriented spectroradiom…

010504 meteorology & atmospheric sciencesUFSP13-8 Global Change and BiodiversitySensor model0211 other engineering and technologiesEarth and Planetary Sciences(all)02 engineering and technology01 natural sciencesErrorsensor modelSpectroradiometerSun-induced chlorophyll fluorescencesun-induced chlorophyll fluorescence; spectroradiometer; sensor model; uncertainty; errorCalibrationCost actionuncertaintylcsh:ScienceChlorophyll fluorescencesun-induced chlorophyll fluorescence/dk/atira/pure/subjectarea/asjc/1900021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingNoise (signal processing)1900 General Earth and Planetary SciencesUncertaintySensor modelReflectivityerror3. Good healthValidation methodsSpectroradiometerspectroradiometerEnvironmental science570 Life sciences; biologyGeneral Earth and Planetary Scienceslcsh:QRemote Sensing
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Estimating Gravimetric Moisture of Vegetation Using an Attenuation-Based Multi-Sensor Approach

2018

Estimating parameters for global climate models via combined active and passive microwave remote sensing data has been a subject of intensive research in recent years. A variety of retrieval algorithms has been proposed for the estimation of soil moisture, vegetation optical depth and other parameters. A novel attenuation-based retrieval approach is proposed here to globally estimate the gravimetric moisture of vegetation (m g ) and retrieve information about the amount of water [kg] per amount of wet vegetation [kg]. The parameter m g is particularly interesting for agro-ecosystems, to assess the status of growing vegetation. The key feature of the proposed approach is that it relies on mu…

010504 meteorology & atmospheric sciencesgravimetric moisture0211 other engineering and technologies02 engineering and technology01 natural scienceslaw.inventionlawVegetation optical depthRadarWater contentattenuation021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingLidarRadarVegetationMoistureAttenuationMicrowave radiometerVegetationSMAPMulti-sensorLidarGravimetric analysisRadiometer
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Evaluation of different methods to retrieve the hemispherical downwelling irradiance in the thermal infrared region for field measurements

2013

International audience; The thermal infrared hemispherical downwelling irradiance (HDI) emitted by the atmosphere and surrounding elements contributes through reflection to the signal measured over an observed surface by remote sensing. This irradiance must be estimated in order to obtain accurate values of land-surface temperature (LST). There are some fast methods to measure the HDI with a single measurement pointing to the sky at a specified viewing direction, but these methods require completely cloud-free or cloudy skies, and they do not account for the radiative contribution of surrounding elements. Another method is the use of a diffuse reflectance panel (usually, a rough gold-coated…

010504 meteorology & atmospheric sciencesmedia_common.quotation_subject[SDV]Life Sciences [q-bio]0211 other engineering and technologiesIrradiance02 engineering and technologyAtmospheric sciences01 natural sciencesBANDAtmosphereRadiative transferEmissivityElectrical and Electronic EngineeringTEMPERATURE021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingmedia_commonRadiometerMODTRANdiffuse reflectance panelAngular measurementsthermal infrared (TIR)EMISSIVITYSOILShemispherical downwelling radiance13. Climate actionSkyfield measurements[SDE]Environmental SciencesReflection (physics)General Earth and Planetary SciencesEnvironmental science
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Modelling soil moisture at SMOS scale by use of a SVAT model over the Valencia Anchor Station

2010

16 páginas, 9 figuras, 5 tablas.

010504 meteorology & atmospheric sciencestélédétectionMISSION SMOS0211 other engineering and technologiesSpaceespagne02 engineering and technologylcsh:Technology01 natural sciencesValidationTraitement du signal et de l'imagelcsh:Environmental technology. Sanitary engineering020701 environmental engineeringWater contentlcsh:Environmental sciencesComputingMilieux_MISCELLANEOUSlcsh:GE1-350InclusionRetrievalMoistureModelling soil moistureSignal and Image processinglcsh:Geography. Anthropology. RecreationRemote sensingDISPOSITIF EXPERIMENTAL; MISSION SMOSProductseurope[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSMOS[SDE.MCG]Environmental Sciences/Global Changessatellite0207 environmental engineeringGrowing seasonParameterizationSpatial distributionlcsh:TD1-1066SchemeHapexspectroradiomètre14. Life underwater[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometerlcsh:TAMSR-Epays méditerranéenSalinityERS scatterometerlcsh:G13. Climate actionDISPOSITIF EXPERIMENTALSoil waterEnvironmental scienceRadiometry
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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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