Search results for "AF"

showing 10 items of 23539 documents

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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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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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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Exploitation of SAR and Optical Sentinel Data to Detect Rice Crop and Estimate Seasonal Dynamics of Leaf Area Index

2017

This paper presents and evaluates multitemporal LAI estimates derived from Sentinel-2A data on rice cultivated area identified using time series of Sentinel-1A images over the main European rice districts for the 2016 crop season. This study combines the information conveyed by Sentinel-1A and Sentinel-2A into a high-resolution LAI retrieval chain. Rice crop was detected using an operational multi-temporal rule-based algorithm, and LAI estimates were obtained by inverting the PROSAIL radiative transfer model with Gaussian process regression. Direct validation was performed with in situ LAI measurements acquired in coordinated field campaigns in three countries (Italy, Spain and Greece). Res…

010504 meteorology & atmospheric sciencesMean squared errorScienceleaf area index (LAI)0211 other engineering and technologies02 engineering and technology01 natural sciencesCropAtmospheric radiative transfer codesConsistency (statistics)KrigingSpatial consistencyArròs Malalties i plaguesSentinel-1ALeaf area indexmappingSentinel021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing2. Zero hungerLeaf Area IndexSentinel-2AQCiències de la terrarice mapGeneral Earth and Planetary SciencesEnvironmental sciencerice map; leaf area index (LAI); Sentinel-1A; Sentinel-2A; Gaussian process regressionRice cropGaussian process regressionRemote Sensing
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Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products

2018

The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperatur…

010504 meteorology & atmospheric sciencesMeteorologySettore AGR/05 - ASSESTAMENTO FORESTALE E SELVICOLTURAWater stressBiome0211 other engineering and technologiesEddy covarianceDaily02 engineering and technologyManagement Monitoring Policy and LawAtmospheric sciences01 natural sciencesLight-Use EfficiencyEvapotranspirationComputers in Earth SciencesMSG021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesGlobal and Planetary ChangeConsistency analysisRelative biasPrimary production15. Life on landGeographyPhysical Geography13. Climate actionLSA SAFForest vegetationSatelliteLight-use efficiencyGPP
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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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Abiotic and biotic controls on methane formation down to 2.5 km depth within the Precambrian Fennoscandian Shield

2017

Abstract Despite a geological history characterised by high temperature and pressure processes and organic carbon deprived crystalline bedrock, large amounts of hydrocarbons are found in deep groundwaters within Precambrian continental shields. In many sites, methane comprises more that 80% of the dissolved gas phase reaching concentrations of tens of mmol l −1 . In this study, we used isotopic methods to study the carbon isotope systematics and sources of crustal methane within the Fennoscandian Shield. The main study sites were the Outokumpu Deep Drill Hole and the Pyhasalmi mine in Finland, both of which allow groundwater sampling down to 2.5 km depth and have been previously studied for…

010504 meteorology & atmospheric sciencesMethanogenesista1171GeochemistryMineralogychemistry.chemical_element010502 geochemistry & geophysicsmetaani01 natural sciencesMethanechemistry.chemical_compoundPrecambrianPyhäsalmikalsiittiGeochemistry and PetrologyNatural gasgrafiitti0105 earth and related environmental sciencesTotal organic carbongraphitebusiness.industrymethane15. Life on landethaneOutokumpuchemistryvetycarbon isotopes13. Climate actionIsotopes of carbonhydrogenFennoscandian shieldbusinesscalciteCarbonGroundwaterGeologyGeochimica et Cosmochimica Acta
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2018

The Radar Vegetation Index (RVI) is a well-established microwave metric of vegetation cover. The index utilizes measured linear scattering intensities from co- and cross-polarization and is normalized to ideally range from 0 to 1, increasing with vegetation cover. At long wavelengths (L-band) microwave scattering does not only contain information coming from vegetation scattering, but also from soil scattering (moisture & roughness) and therefore the standard formulation of RVI needs to be revised. Using global level SMAP L-band radar data, we illustrate that RVI runs up to 1.2, due to the pre-factor in the standard formulation not being adjusted to the scattering mechanisms at these lo…

010504 meteorology & atmospheric sciencesMoistureScattering0211 other engineering and technologiesPolarimetry02 engineering and technology15. Life on land01 natural scienceslaw.inventionlawSurface roughnessmedicineGeneral Earth and Planetary SciencesLeaf area indexRadarmedicine.symptomVegetation (pathology)Water content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing
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The high overtone and combination levels of SF6 revisited at Doppler-limited resolution: A global effective rovibrational model for highly excited vi…

2017

Abstract Sulfur hexafluoride is an important prototypal molecule for modeling highly excited vibrational energy flow and multi quanta absorption processes in hexafluoride molecules of technological importance. It is also a strong greenhouse gas of anthropogenic origin. This heavy species, however, features many hot bands at room temperature (at which only 30% of the molecules lie in the ground vibrational state), especially those originating from the lowest, v 6 =1 vibrational state. Using a cryogenic long path cell with variable optical path length and temperatures regulated between 120 and 163 K, coupled to Synchrotron Radiation and a high resolution interferometer, Doppler-limited spectr…

010504 meteorology & atmospheric sciencesOvertoneInfrared spectroscopylow temperature01 natural sciences7. Clean energyHot bandSpectral linechemistry.chemical_compoundHexafluorideFar infraredhot bandRotation-vibration spectroscopy of SF 60103 physical sciencesSpectroscopy0105 earth and related environmental sciencesPhysics[PHYS]Physics [physics]Radiation[ PHYS ] Physics [physics]010304 chemical physicsRotational–vibrational spectroscopyAtomic and Molecular Physics and Opticschemistry13. Climate actiongreenhouse gasExcited stateinfrared absorptionAtomic physicstensorial formalismLong path cell
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