Search results for "Scatterometer"

showing 10 items of 12 documents

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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Autocorrelation Metrics to Estimate Soil Moisture Persistence From Satellite Time Series: Application to Semiarid Regions

2021

Satellite-derived soil moisture (SM) products have become an important information source for the study of land surface processes in hydrology and land monitoring. Characterizing and estimating soil memory and persistence from satellite observations is of paramount relevance, and has deep implications in ecology, water management, and climate modeling. In this work, we address the problem of SM persistence estimation from microwave sensors using several autocorrelation metrics that, unlike traditional approaches, build on accurate estimates of the autocorrelation function from nonuniformly sampled time series. We show how the choice of the autocorrelation estimator can have a dramatic impac…

Autocorrelation0211 other engineering and technologiesEstimator02 engineering and technology15. Life on landScatterometer6. Clean waterPhysics::GeophysicsAdvanced Microwave Scanning Radiometer-2 (AMSR2) Advanced Scatterometer (ASCAT) autocorrelation e-folding time Least Absolute Shrinkage and Selection Operator (LASSO) Lomb-Scargle periodogram microwave sensors persistence soil moisture Soil Moisture and Ocean Salinity (SMOS) spatial-temporal13. Climate actionConsistency (statistics)General Earth and Planetary SciencesEnvironmental scienceClimate modelSatelliteElectrical and Electronic EngineeringTransectPersistence (discontinuity)021101 geological & geomatics engineeringRemote sensingIEEE Transactions on Geoscience and Remote Sensing
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Global L-band vegetation volume fraction estimates for modeling vegetation optical depth

2021

The attenuation of microwave emissions through the canopy is quantified by the vegetation optical depth (VOD), which is related to the amount of water, the biomass and the structure of vegetation. To provide microwave-derived plant water estimates, one must account for biomass/structure contributions in order to extract the water component from the VOD. This study uses Aquarius scatterometer data to build an L-band global seasonality of vegetation volume fraction (d), representative of biomass/structure dynamics. The dynamic range of d is adapted for its application in a gravimetric moisture (Mg) retrieval model. Results show that d ranging from 0 to 3.35.10- 4 is needed for modelling physi…

CanopyBiomass (ecology)RadarTeledeteccióbiomassMoisturePhenologyAttenuationvegetation gravimetric moisture contentSeasonality:Enginyeria de la telecomunicació [Àrees temàtiques de la UPC]Remote sensingmedicine.diseaseAtmospheric sciencesVegetation gravimetric moisture contentAquarius scatterometerVegetation structuremedicineSpatial ecologyEnvironmental scienceBiomassmedicine.symptomVegetation (pathology)
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Analysis of the linkages between rainfall and land surface conditions in the West African monsoon through CMAP, ERS-WSC, and NOAA-AVHRR data

2005

International audience; The European Remote Sensing Wind Scatterometer (ERS-WSC) backscattering coefficient, NOAA Advanced Very High Resolution Radiometer (NOAA-AVHRR) Normalized Difference Vegetation Index (NDVI), and Climate Prediction Center Merged Analysis Precipitation ( CMAP) precipitation data sets are studied over the period August 1991 to December 2000 to document ( 1) the interannual and intra-annual evolutions of vegetation photosynthetic activity and soil-vegetation water content over West Africa and ( 2) their two-way links with precipitation. Over the Sahel, at interannual timescales the strongest relationships between vegetation, soil moisture, and precipitation are observed …

DYNAMICSAtmospheric Science010504 meteorology & atmospheric sciencesAdvanced very-high-resolution radiometerDIFFERENCE VEGETATION INDEX0211 other engineering and technologiesSoil ScienceTIME-SERIES02 engineering and technologyWIND SCATTEROMETER DATAAquatic ScienceOceanographyMonsoonSOIL-MOISTURE01 natural sciencesNormalized Difference Vegetation Index[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsGeochemistry and PetrologyCIRCULATIONSEarth and Planetary Sciences (miscellaneous)[ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces environmentPrecipitation[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentWater contentTEMPERATURE021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesWater Science and TechnologyEcologyMoisturePaleontologyForestry15. Life on landScatterometerVARIABILITYGeophysics13. Climate actionSpace and Planetary ScienceClimatologyPRECIPITATIONSoil waterEnvironmental scienceSAHEL RAINFALL
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A carbon sink-driven approach to estimate gross primary production from microwave satellite observations

2019

Abstract Global estimation of Gross Primary Production (GPP) - the uptake of atmospheric carbon dioxide by plants through photosynthesis - is commonly based on optical satellite remote sensing data. This presents a source-driven approach since it uses the amount of absorbed light, the main driver of photosynthesis, as a proxy for GPP. Vegetation Optical Depth (VOD) estimates obtained from microwave sensors provide an alternative and independent data source to estimate GPP on a global scale, which may complement existing GPP products. Recent studies have shown that VOD is related to aboveground biomass, and that both VOD and temporal changes in VOD relate to GPP. In this study, we build upon…

Earth observationTeledetecció010504 meteorology & atmospheric sciences0208 environmental biotechnologySoil ScienceComputerApplications_COMPUTERSINOTHERSYSTEMS02 engineering and technologyData_CODINGANDINFORMATIONTHEORY01 natural sciencesCross-validationFluxNetVegetacióComputers in Earth Sciences0105 earth and related environmental sciencesRemote sensingRadiometerComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSPrimary productionGeology15. Life on landScatterometer020801 environmental engineeringSpectroradiometer13. Climate actionEnvironmental scienceSpatial variability
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Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions

2022

The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing the system. Such models, however, need the correct specification of all interactions between variables in the problem and the appropriate parameterization is a challenge in itself. On the other hand, machine learning approaches are flexible data-driven tools, able to approximate arbitrarily complex functions, but lack interpretability and struggle when data is scarce or in extrapolation regimes. In this paper, we argue that hybrid learning schemes that combine both approa…

FOS: Computer and information sciencesComputer Science - Machine LearningEarth observationAdvanced microwave scanning radiometer-2 (AMSR-2)moderate resolution imaging spectroradiometer (MODIS)Computer scienceleaf area index (LAI)0211 other engineering and technologiesExtrapolationMachine Learning (stat.ML)02 engineering and technologycomputer.software_genreMachine Learning (cs.LG)Data-drivenConvolutionsymbols.namesakeadvanced scatterometer (ASCAT)Statistics - Machine Learningordinary differential equation (ODE)Electrical and Electronic EngineeringGaussian processsoil moisture and ocean salinity (SMOS)021101 geological & geomatics engineeringInterpretabilityForcing (recursion theory)machine learning (ML)soil moisture (SM)time series analysisgaussian process (GP)symbolsGeneral Earth and Planetary SciencesDomain knowledgeData mininggap fillingphysicscomputerfraction of absorbed photosynthetically active radiation (faPAR)IEEE Transactions on Geoscience and Remote Sensing
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Assessing the relationship between microwave vegetation optical depth and gross primary production

2018

At the global scale, the uptake of atmospheric carbon dioxide by terrestrial ecosystems through photosynthesis is commonly estimated through vegetation indices or biophysical properties derived from optical remote sensing data. Microwave observations of vegetated areas are sensitive to different components of the vegetation layer than observations in the optical domain and may therefore provide complementary information on the vegetation state, which may be used in the estimation of Gross Primary Production (GPP). However, the relation between GPP and Vegetation Optical Depth (VOD), a biophysical quantity derived from microwave observations, is not yet known. This study aims to explore the …

Global and Planetary ChangeCarbon dioxide in Earth's atmosphereRadiometerTeledetecció010504 meteorology & atmospheric sciences0208 environmental biotechnologyBiomePrimary production02 engineering and technology15. Life on landManagement Monitoring Policy and LawScatterometer01 natural sciences020801 environmental engineeringGeography13. Climate actionTerrestrial ecosystemVegetacióComputers in Earth SciencesEcosystem respirationMicrowave0105 earth and related environmental sciencesEarth-Surface ProcessesRemote sensingInternational Journal of Applied Earth Observation and Geoinformation
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Europe's offshore winds assessed with synthetic aperture radar, ASCAT and WRF

2020

Europe's offshore wind resource mapping is part of the New European Wind Atlas (NEWA) international consortium effort. This study presents the results of analysis of synthetic aperture radar (SAR) ocean wind maps based on Envisat and Sentinel-1 with a brief description of the wind retrieval process and Advanced Scatterometer (ASCAT) ocean wind maps. The wind statistics at 10 and 100 m above mean sea level (a.m.s.l.) height using an extrapolation procedure involving simulated long-term stability over oceans are presented for both SAR and ASCAT. Furthermore, the Weather Research and Forecasting (WRF) offshore wind atlas of NEWA is presented. This has 3 km grid spacing with data …

Synthetic aperture radar010504 meteorology & atmospheric sciencesMeteorologyRenewable Energy Sustainability and the Environmentlcsh:TJ807-8300211 other engineering and technologieslcsh:Renewable energy sourcesEnergy Engineering and Power Technology02 engineering and technologyScatterometer01 natural sciencesWind speedOffshore wind powerWeather Research and Forecasting ModelWind atlasSubmarine pipelineGeologySea level021101 geological & geomatics engineering0105 earth and related environmental sciencesWind Energy Science
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Europe’s offshore winds assessed from SAR, ASCAT and WRF

2019

Abstract. Europe’s offshore wind resource mapping is part of the New European Wind Atlas (NEWA) international consortium effort. This study presents the results of analysis of Synthetic Aperture Radar (SAR) ocean wind maps based on Envisat and Sentinel-1 with a brief description of the wind retrieval process and Advanced SCATterometer (ASCAT) ocean wind maps. The wind statistics at 10m and 100m height using an extrapolation procedure involving simulated long-term stability over oceans is presented for both SAR and ASCAT. Furthermore, the Weather Research and Forecasting (WRF) offshore wind atlas of NEWA is presented. This has 3 km grid resolution with data every 30 minutes during 30 years f…

Synthetic aperture radarOffshore wind powerMeteorologyWeather Research and Forecasting ModelWind atlasEnvironmental scienceSubmarine pipelineScatterometerScale (map)Wind speed
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Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements

2019

Soil moisture (SM) is a key state variable in understanding the climate system through its control on the land surface energy, water budget partitioning, and the carbon cycle. Monitoring SM at regional scale has become possible thanks to microwave remote sensing. In the past two decades, several satellites were launched carrying on board either radiometer (passive) or radar (active) or both sensors in different frequency bands with various spatial and temporal resolutions. Soil moisture algorithms are in rapid development and their improvements/revisions are ongoing. The latest SM retrieval products and versions of products that have been recently released are not yet, to our knowledge, com…

TechnologyPassive microwave remote sensing010504 meteorology & atmospheric sciences0208 environmental biotechnologyActive microwave remote sensingReview02 engineering and technology01 natural sciences7. Clean energylaw.inventionRemote SensinglawRadarEvaluationComputingMilieux_MISCELLANEOUSevaluationGeologypassive microwave remote sensingDATA SETSLife Sciences & Biomedicineactive microwave remote sensingSMOSLAND SURFACESreviewSoil ScienceClimate changeEnvironmental Sciences & EcologyLand coverVALIDATIONRETRIEVALSInternational soil moisture networkComputers in Earth SciencesImaging Science & Photographic Technology[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment0105 earth and related environmental sciencesRemote sensingScience & TechnologyRadiometerAMSR-ESMAPScatterometerinternational soil moisture network020801 environmental engineeringCLIMATEASCAT13. Climate actionSoil waterEnvironmental scienceSpatial variabilitySatelliteSoil moisturesoil moistureEnvironmental SciencesL-BANDRemote Sensing of Environment
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