Search results for "Mathematic"

showing 10 items of 24974 documents

Mapping land surface emissivity from NDVI: Application to European, African, and South American areas

1996

Thermal infrared emissivity is an important parameter both for surface characterization and for atmospheric correction methods. Mapping the emissivity from satellite data is therefore a very important question to solve. The main problem is the coupling of the temperature and emissivity effects in the thermal radiances. Several methods have been developed to obtain surface emissivity from satellite data. In this way we propose a theoretical model that relates the emissivity to the NDVI (normalized difference vegetation index) of a given surface and explains the experimental behavior observed by van de Griend and Owe. We can use it to obtain the emissivity in any thermal channel, but in this …

010504 meteorology & atmospheric sciencesMathematical model0211 other engineering and technologiesAtmospheric correctionSoil ScienceGeology02 engineering and technologySurface finish01 natural sciencesNormalized Difference Vegetation Index13. Climate actionMiddle latitudesThermalEmissivityEnvironmental scienceSatelliteComputers in Earth SciencesAstrophysics::Galaxy Astrophysics021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
researchProduct

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
researchProduct

Crop specific algorithms trained over ground measurements provide the best performance for GAI and fAPAR estimates from Landsat-8 observations

2021

Abstract Estimation of Green Area Index (GAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) from decametric satellites was investigated in this study using a large database of ground measurements over croplands. It covers six main crop types including rice, corn, wheat and barley, sunflower, soybean and other types of crops. Ground measurements were completed using either digital hemispherical cameras, LAI-2000 or AccuPAR devices over sites representative of a decametric pixel. Sites were spread over the globe and the data collected at several growth stages concurrently to the acquisition of Landsat-8 images. Several machine learning techniques were investigated to re…

010504 meteorology & atmospheric sciencesMean squared errorArtificial neural networkCalibration (statistics)0208 environmental biotechnologyEmpirical modellingSoil ScienceGeology02 engineering and technology01 natural sciencesNormalized Difference Vegetation Index020801 environmental engineeringSupport vector machineData pointKrigingComputers in Earth SciencesAlgorithm0105 earth and related environmental sciencesRemote sensingMathematicsRemote Sensing of Environment
researchProduct

Optimizing Gaussian Process Regression for Image Time Series Gap-Filling and Crop Monitoring

2020

Image processing entered the era of artificial intelligence, and machine learning algorithms emerged as attractive alternatives for time series data processing. Satellite image time series processing enables crop phenology monitoring, such as the calculation of start and end of season. Among the promising algorithms, Gaussian process regression (GPR) proved to be a competitive time series gap-filling algorithm with the advantage of, as developed within a Bayesian framework, providing associated uncertainty estimates. Nevertheless, the processing of time series images becomes computationally inefficient in its standard per-pixel usage, mainly for GPR training rather than the fitting step. To…

010504 meteorology & atmospheric sciencesMean squared errorComputer science0211 other engineering and technologiesImage processing02 engineering and technologycomputer.software_genre01 natural scienceslcsh:AgricultureKrigingTime series021101 geological & geomatics engineering0105 earth and related environmental sciences2. Zero hungerHyperparameterPixelSeries (mathematics)lcsh:SGaussian processes regressionSatellite Image Time SeriesData miningtime seriesSentinel-2optimizationAgronomy and Crop Sciencecomputercrop monitoringphenology indicatorsAgronomy
researchProduct

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
researchProduct

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
researchProduct

A space-time rainfall generator for highly convective Mediterranean rainstorms

2003

Distributed hydrological models require fine resolution rainfall inputs, enhancing the practical interest of space-time rainfall models, capable of generating through numerical simulation realistic space-time rainfall intensity fields. Among different mathematical approaches, those based on point processes and built upon a convenient analytical description of the raincell as the fundamental unit, have shown to be particularly suitable and well adapted when extreme rainfall events of convective nature are considered. Starting from previous formulations, some analytical refinements have been considered, allowing practical generation of space-time rainfall intensity fields for that type of rai…

010504 meteorology & atmospheric sciencesMeteorology0207 environmental engineering[SDU.STU]Sciences of the Universe [physics]/Earth Sciences02 engineering and technologyMethod of moments (statistics)01 natural sciencesPoint processlcsh:TD1-1066lcsh:Environmental technology. Sanitary engineering020701 environmental engineering[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentlcsh:Environmental sciences0105 earth and related environmental scienceslcsh:GE1-350[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereComputer simulationRain gauge[SDU.OCEAN] Sciences of the Universe [physics]/Ocean AtmosphereSpace timelcsh:QE1-996.5lcsh:Geography. Anthropology. Recreation[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces environment6. Clean waterRunoff modellcsh:Geologylcsh:G13. Climate actionClimatology[SDU.STU] Sciences of the Universe [physics]/Earth SciencesGeneral Earth and Planetary SciencesEnvironmental scienceIntensity (heat transfer)Generator (mathematics)
researchProduct

Towards Understanding the Interconnection between Celestial Pole Motion and Earth’s Magnetic Field Using Space Geodetic Techniques

2021

The understanding of forced temporal variations in celestial pole motion (CPM) could bring us significantly closer to meeting the accuracy goals pursued by the Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG), i.e., 1 mm accuracy and 0.1 mm/year stability on global scales in terms of the Earth orientation parameters. Besides astronomical forcing, CPM excitation depends on the processes in the fluid core and the core–mantle boundary. The same processes are responsible for the variations in the geomagnetic field (GMF). Several investigations were conducted during the last decade to find a possible interconnection of GMF changes with the length of day (…

010504 meteorology & atmospheric sciencesMotion (geometry)TP1-1185010502 geochemistry & geophysicsSpace (mathematics)01 natural sciencesBiochemistryArticleAnalytical ChemistryPhysics::Geophysicscelestial pole offsetCelestial polegeomagnetic fieldCelestial pole offsetVery-long-baseline interferometryElectrical and Electronic EngineeringInstrumentation0105 earth and related environmental sciencesPhysicsInterconnectionChemical technologyEuropean researchGeodetic datumMatemática AplicadaGeodesyAtomic and Molecular Physics and OpticsEarth's magnetic field13. Climate actionPhysics::Space Physicsddc:620VLBIGeomagnetic fieldSensors
researchProduct

Spectropolarimetric evidence for a siphon flow along an emerging magnetic flux tube

2016

©2017 The American Astronomical Society. All rights reserved.We study the dynamics and topology of an emerging magnetic flux concentration using high spatial resolution spectropolarimetric data acquired with the Imaging Magnetograph eXperiment on board the sunrise balloon-borne solar observatory. We obtain the full vector magnetic field and the line of sight (LOS) velocity through inversions of the Fe i line at 525.02 nm with the SPINOR code. The derived vector magnetic field is used to trace magnetic field lines. Two magnetic flux concentrations with different polarities and LOS velocities are found to be connected by a group of arch-shaped magnetic field lines. The positive polarity footp…

010504 meteorology & atmospheric sciencesPolarity (physics)photosphere [Sun]FOS: Physical sciencesAstrophysicspolarimetric [Techniques]01 natural sciencesMethods: observational0103 physical sciencesSunriseAstrophysics::Solar and Stellar Astrophysicsobservational [Methods]010303 astronomy & astrophysicsSun: magnetic fieldsSolar and Stellar Astrophysics (astro-ph.SR)0105 earth and related environmental sciencesLine (formation)PhysicsSolar observatoryPolarity symbolsTechniques: polarimetricSun: photosphereAstronomy and AstrophysicsMagnetic fluxMagnetic fieldAstrophysics - Solar and Stellar AstrophysicsFlow (mathematics)magnetic fields [Sun]Space and Planetary Science
researchProduct

2016

The spatial context is criticalwhen assessing present-day climate anomalies, attributing them to potential forcings and making statements regarding their frequency and severity in a long-term perspective. Recent international initiatives have expanded the number of high-quality proxy-records and developed new statistical reconstruction methods. These advances allow more rigorous regional past temperature reconstructions and, in turn, the possibility of evaluating climate models on policy-relevant, spatiotemporal scales. Here we provide a new proxy-based, annually-resolved, spatial reconstruction of the European summer (June-August) temperature fields back to 755 CE based on Bayesian hierarc…

010504 meteorology & atmospheric sciencesRenewable Energy Sustainability and the EnvironmentPublic Health Environmental and Occupational HealthClimate changeContext (language use)Forcing (mathematics)010502 geochemistry & geophysicsSolar irradianceAtmospheric temperature01 natural sciences13. Climate actionClimatologyPaleoclimatologyClimate modelMean radiant temperature0105 earth and related environmental sciencesGeneral Environmental ScienceEnvironmental Research Letters
researchProduct