Search results for " Life"

showing 10 items of 18406 documents

Radiometric calibration of SeaWIFS in the near infrared

2005

The radiometric calibration of the Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) in the near infrared (band 8, centered on 865 nm) is evaluated by use of ground-based radiometer measurements of solar extinction and sky radiance in the Sun's principal plane at two sites, one located 13 km off Venice, Italy, and the other on the west coast of Lanai Island, Hawaii. The aerosol optical thickness determined from solar extinction is used in an iterative scheme to retrieve the pseudo aerosol phase function, i.e., the product of single-scattering albedo and phase function, in which sky radiance is corrected for multiple scattering effects. No assumption about the aerosol model is required. The ae…

010504 meteorology & atmospheric sciencesMaterials Science (miscellaneous)Solar zenith angle01 natural sciencesIndustrial and Manufacturing Engineering010309 optics[SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/ClimatologyOptics0103 physical sciences14. Life underwaterBusiness and International ManagementRadiometric calibration0105 earth and related environmental sciencesRemote sensingRadiometerbusiness.industryAtmospheric correctionAerosolSeaWiFS13. Climate action[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/ClimatologyInfrared windowRadianceEnvironmental science[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/Climatologybusiness
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Quantifying vegetation biophysical variables from the Sentinel-3/FLEX tandem mission: Evaluation of the synergy of OLCI and FLORIS data sources

2020

The ESA’s forthcoming FLuorescence EXplorer (FLEX) mission is dedicated to the global monitoring of the vegetation’s chlorophyll fluorescence by means of an imaging spectrometer, FLORIS. In order to properly interpret the fluorescence signal in relation to photosynthetic activity, essential vegetation variables need to be retrieved concomitantly. FLEX will fly in tandem with Sentinel-3 (S3), which conveys the Ocean and Land Colour Instrument (OLCI) that is designed to characterize the atmosphere and the terrestrial vegetation at a spatial resolution of 300 m. In this work we present the retrieval models of four essential biophysical variables: (1) Leaf Area Index (LAI), (2) leaf chlorophyll…

010504 meteorology & atmospheric sciencesMean squared error0208 environmental biotechnologyImaging spectrometerSoil ScienceGeology02 engineering and technologyVegetationSpectral bands15. Life on land01 natural sciencesArticle020801 environmental engineeringPhotosynthetically active radiationKrigingEnvironmental scienceComputers in Earth SciencesLeaf area indexImage resolution0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Hybrid inversion of radiative transfer models based on high spatial resolution satellite reflectance data improves fractional vegetation cover retrie…

2021

In forest landscapes affected by fire, the estimation of fractional vegetation cover (FVC) from remote sensing data using radiative transfer models (RTMs) enables to evaluate the ecological impact of such disturbance across plant communities at different spatio-temporal scales. Even though, when landscapes are highly heterogeneous, the fine-scale ground spatial variation might not be properly captured if FVC products are provided at moderate or coarse spatial scales, as typical of most of operational Earth observing satellite missions. The objective of this study was to evaluate the potential of a RTM inversion approach for estimating FVC from satellite reflectance data at high spatial reso…

010504 meteorology & atmospheric sciencesMean squared error0208 environmental biotechnologySoil Science02 engineering and technology01 natural sciencesArticleWorldView-3Radiative transferComputers in Earth SciencesImage resolution0105 earth and related environmental sciencesRemote sensingFractional vegetation coverForest fireGeologyInversion (meteorology)15. Life on landEcología. Medio ambienteRadiative transfer modeling020801 environmental engineering13. Climate actionGround-penetrating radarEnvironmental scienceSatelliteSpatial variabilitySentinel-2Scale (map)Remote Sensing of Environment
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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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Gaussian Processes Retrieval of LAI from Sentinel-2 Top-of-Atmosphere Radiance Data

2020

Abstract Retrieval of vegetation properties from satellite and airborne optical data usually takes place after atmospheric correction, yet it is also possible to develop retrieval algorithms directly from top-of-atmosphere (TOA) radiance data. One of the key vegetation variables that can be retrieved from at-sensor TOA radiance data is leaf area index (LAI) if algorithms account for variability in atmosphere. We demonstrate the feasibility of LAI retrieval from Sentinel-2 (S2) TOA radiance data (L1C product) in a hybrid machine learning framework. To achieve this, the coupled leaf-canopy-atmosphere radiative transfer models PROSAIL-6SV were used to simulate a look-up table (LUT) of TOA radi…

010504 meteorology & atmospheric sciencesMean squared errorComputer science0211 other engineering and technologiesAtmospheric correctionFOS: Physical sciences02 engineering and technology15. Life on land01 natural sciencesAtomic and Molecular Physics and OpticsArticleComputer Science ApplicationsPhysics - Atmospheric and Oceanic PhysicsAtmospheric radiative transfer codesKrigingAtmospheric and Oceanic Physics (physics.ao-ph)RadianceSatelliteComputers in Earth SciencesLeaf area indexScale (map)Engineering (miscellaneous)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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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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Empirical and physical estimation of Canopy Water Content from CHRIS/PROBA data

2013

20 páginas, 4 tablas, 7 figuras.

010504 meteorology & atmospheric sciencesMean squared errorScience0211 other engineering and technologies02 engineering and technologyCHRIS/PROBA01 natural sciencescanopy water content;model inversion;neural networks;look up tables;empirical up-scalingmodel inversionEmpirical up-scalingAtmospheric radiative transfer codeslook up tablesRadiative transferModel inversion021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingArtificial neural networkCanopy water contentQHyperspectral imagingInversion (meteorology)Sigmoid functionSpectral bandsempirical up-scaling15. Life on landneural networks[SDE]Environmental SciencesGeneral Earth and Planetary SciencesLook up tablescanopy water contentNeural networkscanopy water content; model inversion; neural networks; look up tables; empirical up-scaling; CHRIS/PROBA
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Top-of-Atmosphere Retrieval of Multiple Crop Traits Using Variational Heteroscedastic Gaussian Processes within a Hybrid Workflow.

2021

In support of cropland monitoring, operational Copernicus Sentinel-2 (S2) data became available globally and can be explored for the retrieval of important crop traits. Based on a hybrid workflow, retrieval models for six essential biochemical and biophysical crop traits were developed for both S2 bottom-of-atmosphere (BOA) L2A and S2 top-of-atmosphere (TOA) L1C data. A variational heteroscedastic Gaussian process regression (VHGPR) algorithm was trained with simulations generated by the combined leaf-canopy reflectance model PROSAILat the BOA scale and further combined with the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) atmosphere model at the TOA scale. Establishe…

010504 meteorology & atmospheric sciencesMean squared errorScienceReference data (financial markets)MathematicsofComputing_GENERAL0211 other engineering and technologieshybrid model02 engineering and technologyAtmospheric model01 natural sciencessymbols.namesaketop-of-atmosphere reflectanceKrigingLeaf area indexGaussian process021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensing2. Zero hungerQbiophysical and biochemical traits; top-of-atmosphere reflectance; Sentinel-2; variational heteroscedastic Gaussian process regression; hybrid modelvariational heteroscedastic Gaussian process regressionVegetation15. Life on landsymbolsGeneral Earth and Planetary Sciencesbiophysical and biochemical traitsSentinel-2Scale (map)Remote sensing
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Bioconcentration, biotransformation and elimination of pyrene in the arctic crustacean Gammarus setosus (Amphipoda) at two temperatures

2015

The influence of temperature on the bioaccumulation, toxicokinetics, biotransformation and depuration of pyrene was studied in the arctic marine amphipod Gammarus setosus. A two-compartment model was used to fit experimental values of total body burden, total metabolites and parent pyrene concentrations and to calculate toxicokinetic variables derived for two experimental treatments (2 and 8 °C). No statistically significant differences were observed with temperature for these toxicokinetic variables or bioconcentration factors. Contrarily, the Q10 values suggested that the toxicokinetic variables ke and km were temperature-dependent. This may be explained by the high standard deviation of …

010504 meteorology & atmospheric sciencesMetaboliteta1172polycyclic aromatic hydrocarbonsQ10Bioconcentration010501 environmental sciencesAquatic ScienceOceanography01 natural sciencesGammarus setosusSvalbardchemistry.chemical_compoundBiotransformationtoxicokineticsAnimalsToxicokineticsAmphipoda14. Life underwaterBiotransformation0105 earth and related environmental sciencesPyrenesbiologyArctic RegionsChemistryTemperatureGeneral Medicinebiology.organism_classificationPollutiondepurationarctic invertebratesKinetics13. Climate actionuptakeBioaccumulationEnvironmental chemistryPyreneWater Pollutants ChemicalEnvironmental MonitoringMarine Environmental Research
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2016

Gianluca Tramontana was supported by the GEOCARBON EU FP7 project (GA 283080). Dario Papale, Martin Jung and Markus Reichstein acknowledge funding from the EU FP7 project GEOCARBON (grant agreement no. 283080) and the EU H2020 BACI project (grant agreement no. 640176). Gustau Camps-Valls wants to acknowledge the support by an ERC Consolidator Grant with grant agreement 647423 (SEDAL). Kazuhito Ichii was supported by Environment Research and Technology Development Funds (2-1401) from the Ministry of the Environment of Japan and the JAXA Global Change Observation Mission (GCOM) project (no. 115). Christopher R. Schwalm was supported by National Aeronautics and Space Administration (NASA) gran…

010504 meteorology & atmospheric sciencesMeteorologyFLUXNET0208 environmental biotechnology0207 environmental engineeringlcsh:Life02 engineering and technologySensible heatAtmospheric sciences7. Clean energy01 natural sciencesFlux (metallurgy)FluxNetMachine learning; Carbon fluxes; Energy fluxes; FLUXNET; Remote sensing; FLUXCOMlcsh:QH540-549.5Latent heatMachine learningCarbon fluxes020701 environmental engineeringEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEarth-Surface ProcessesFLUXCOMMultivariate adaptive regression splineslcsh:QE1-996.5Empirical modellingPrimary production15. Life on landRemote sensingEnergy fluxes020801 environmental engineeringlcsh:Geologylcsh:QH501-531Kernel method13. Climate actionEnvironmental sciencelcsh:EcologyBiogeosciences
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