Search results for " DA"

showing 10 items of 14241 documents

Contribution of environmental factors to temperature distribution at different resolution levels on the forefield of the Loven Glaciers (Svalbard)

2007

ABSTRACTThe climate and its components (temperature and precipitation) are organised according to different spatial scales that are structured hierarchically. The aim of this paper is to explore the dependence between temperature and deterministic factors at different scales on a 10 km2 study area on the northwestern coast of Svalbard. A GIS was developed which contained three sources of information: temperature, remotely sensed imagery and digital elevation models (DEM), and derived raster data layers. The first layer, temperatures, was acquired at regularly observed temporal intervals from 53 stations. The second layer comprised remotely sensed images (aerial photography and SPOT imagery)…

010504 meteorology & atmospheric sciencesEcology[SHS.GEO] Humanities and Social Sciences/GeographyGeography Planning and Development0207 environmental engineeringElevation02 engineering and technology[SHS.GEO]Humanities and Social Sciences/Geography15. Life on land01 natural sciences[ SHS.GEO ] Humanities and Social Sciences/GeographyRaster dataAerial photography13. Climate actionLinear regressionSpatial ecologyGeneral Earth and Planetary Sciences020701 environmental engineeringDigital elevation modelScale (map)Image resolutionGeology0105 earth and related environmental sciencesRemote sensing
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Downscaling of American National Aeronautics and Space Administration (NASA) daily air temperature in Sicily, Italy, and effects on crop reference ev…

2018

Abstract Air temperature (Ta) is one of the key factors in agro-hydrological studies including estimation of crop reference evapotranspiration (ET0), which is crucial for irrigation water management and sustainability of agro-ecosystem productivity. Because direct measurements of ET0 are difficult, expensive and time consuming, the use of physically based or empirical approaches linked to meteorological information is often preferred. The Prediction of Worldwide Energy Resource project developed by the American National Aeronautics and Space Administration (POWER-NASA) provides daily meteorological information on a 1° latitude by 1° longitude grid. Despite the poor spatial resolution charac…

010504 meteorology & atmospheric sciencesElevationSoil ScienceLapse rateHargreaves equation04 agricultural and veterinary sciences01 natural sciencesLatitudeAeronauticsEvapotranspirationTurc equationWeather dat040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental scienceSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliPenman–Monteith equationDigital elevation modelLongitudeAgronomy and Crop Science0105 earth and related environmental sciencesDownscalingPOWER-NASAWater Science and TechnologyEarth-Surface Processes
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THEMIS: A Parameter Estimation Framework for the Event Horizon Telescope

2020

This is an open access article.-- Full list of authors: Broderick, Avery E.; Gold, Roman; Karami, Mansour; Preciado-López, Jorge A.; Tiede, Paul; Pu, Hung-Yi; Akiyama, Kazunori; Alberdi, Antxon; Alef, Walter; Asada, Keiichi; Azulay, Rebecca; Baczko, Anne-Kathrin; Baloković, Mislav; Barrett, John; Bintley, Dan; Blackburn, Lindy; Boland, Wilfred; Bouman, Katherine L.; Bower, Geoffrey C.; Bremer, Michael; Brinkerink, Christiaan D.; Brissenden, Roger; Britzen, Silke; Broguiere, Dominique; Bronzwaer, Thomas; Byun, Do-Young; Carlstrom, John E.; Chael, Andrew; Chatterjee, Shami; Chatterjee, Koushik; Chen, Ming-Tang; Chen, Yongjun; Cho, Ilje; Conway, John E.; Cordes, James M.; Crew, Geoffrey B.; Cu…

010504 meteorology & atmospheric sciencesExploitAstronomy01 natural sciencesData typeSet (abstract data type)Galactic center0103 physical sciencesVery-long-baseline interferometry16471769010303 astronomy & astrophysics0105 earth and related environmental sciencesVery long baseline interferometryPhysicsEvent Horizon TelescopeSupermassive black holeAstrophysical black holesGalactic CenterAstronomy and Astrophysics98565Black hole[SDU]Sciences of the Universe [physics]Space and Planetary ScienceAstronomy data analysis1858[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]AlgorithmSubmillimeter astronomy
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Mapping Vegetation Density in a Heterogeneous River Floodplain Ecosystem Using Pointable CHRIS/PROBA Data

2012

River floodplains in the Netherlands serve as water storage areas, while they also have the function of nature rehabilitation areas. Floodplain vegetation is therefore subject to natural processes of vegetation succession. At the same time, vegetation encroachment obstructs the water flow into the floodplains and increases the flood risk for the hinterland. Spaceborne pointable imaging spectroscopy has the potential to quantify vegetation density on the basis of leaf area index (LAI) from a desired view zenith angle. In this respect, hyperspectral pointable CHRIS data were linked to the ray tracing canopy reflectance model FLIGHT to retrieve vegetation density estimates over a heterogeneous…

010504 meteorology & atmospheric sciencesFloodplainWater flowpointable sensors; CHRIS/PROBA; leaf area index (LAI); inversion; radiative transfer (RT) model; FLIGHT; river floodplain ecosystem; vegetation density; hydraulic roughnessleaf area index (LAI)0211 other engineering and technologiesClimate change02 engineering and technologyCHRIS/PROBA01 natural sciencesforestinversionLaboratory of Geo-information Science and Remote SensingLaboratorium voor Geo-informatiekunde en Remote SensingLeaf area indexcoverlcsh:ScienceZenithriver floodplain ecosystem021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinggeographychris-proba datahyperspectral brdf datageography.geographical_feature_categoryFLIGHTFlood mythrhine basinradiative-transfer modelHyperspectral imagingEnhanced vegetation index15. Life on landpointable sensorsPE&RCradiative transfer (RT) modelsugar-beetclimate-changeGeneral Earth and Planetary SciencesEnvironmental sciencehydraulic roughnesslcsh:Qflow resistanceleaf-area indexvegetation densityRemote Sensing
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Explosive eruptive history of Pantelleria, Italy: Repeated caldera collapse and ignimbrite emplacement at a peralkaline volcano

2018

A new, pre-Green Tuff (46 ka) volcanic stratigraphy is presented for the peralkaline Pantelleria Volcano, Italy. New 40Ar/39Ar and paleomagnetic data are combined with detailed field studies to develop a comprehensive stratigraphic reconstruction of the island.We find that the pre-46 ka succession is characterised by eight silicarich peralkaline (trachyte to pantellerite) ignimbrites,many ofwhich blanketed the entire island. The ignimbrites are typically welded to rheomorphic, and are commonly associated with lithic breccias and/or pumice deposits. They record sustained radial pyroclastic density currents fed by lowpyroclastic fountains. The onset of ignimbrite emplacement is typically prec…

010504 meteorology & atmospheric sciencesGeochemistryPyroclastic rockTrachyte010502 geochemistry & geophysics01 natural sciencesPeralkaline rock40Ar/39Ar datingEffusive eruptionGeochemistry and PetrologyPumiceBreccia[SDU.STU.VO]Sciences of the Universe [physics]/Earth Sciences/VolcanologyCalderaEruptive history0105 earth and related environmental sciencesgeographygeography.geographical_feature_categoryIgnimbritesPeralkaline volcanismSettore GEO/07 - Petrologia E PetrografiaSettore GEO/08 - Geochimica E VulcanologiaCaldera collapsePeralkaline volcanism Pantelleria Ignimbrites Caldera collapse Eruptive history 40Ar/39Ar datingGeophysicsVolcano13. Climate actionSeismologyGeologyPantelleria
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GIGJ: a crustal gravity model of the Guangdong Province for predicting the geoneutrino signal at the JUNO experiment

2019

Gravimetric methods are expected to play a decisive role in geophysical modeling of the regional crustal structure applied to geoneutrino studies. GIGJ (GOCE Inversion for Geoneutrinos at JUNO) is a 3D numerical model constituted by ~46 x 10$^{3}$ voxels of 50 x 50 x 0.1 km, built by inverting gravimetric data over the 6{\deg} x 4{\deg} area centered at the Jiangmen Underground Neutrino Observatory (JUNO) experiment, currently under construction in the Guangdong Province (China). The a-priori modeling is based on the adoption of deep seismic sounding profiles, receiver functions, teleseismic P-wave velocity models and Moho depth maps, according to their own accuracy and spatial resolution. …

010504 meteorology & atmospheric sciencesGeoneutrinogeophysical uncertaintieInverse transform samplingFOS: Physical sciences01 natural sciencesBayesian methodUpper middle and lower crustStandard deviationNOSouth China BlockmiddlePhysics - GeophysicsMonte Carlo stochastic optimizationGOCE data gravimetric inversionGeophysical uncertaintiesGeochemistry and PetrologyEarth and Planetary Sciences (miscellaneous)Bayesian method; geophysical uncertainties; GOCE data gravimetric inversion; Monte Carlo stochastic optimization; South China Block; upper middle and lower crustImage resolution0105 earth and related environmental sciencesSubdivisionJiangmen Underground Neutrino Observatoryupper and middle and lower crustbusiness.industrySettore FIS/01 - Fisica SperimentaleCrustupperGeodesy[PHYS.PHYS.PHYS-GEN-PH]Physics [physics]/Physics [physics]/General Physics [physics.gen-ph]Geophysics (physics.geo-ph)and lower crustDepth soundingGeophysics13. Climate actionSpace and Planetary SciencebusinessGeologyBayesian method geophysical uncertainties GOCE data gravimetric inversion Monte Carlo stochastic optimization South China Blockupper and middle and lower crust
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Applications of a new set of methane line parameters to the modeling of Titan's spectrum in the 1.58 μm window

2012

International audience; In this paper we apply a recently released set of methane line parameters (Wang et al., 2011) to the modeling of Titan spectra in the 1.58 mu m window at both low and high spectral resolution. We first compare the methane absorption based on this new set of methane data to that calculated from the methane absorption coefficients derived in situ from DISR/Huygens (Tomasko et al., 2008a; Karkoschka and Tomasko, 2010) and from the band models of Irwin et al. (2006) and Karkoschka and Tomasko (2010). The Irwin et al. (2006) band model clearly underestimates the absorption in the window at temperature-pressure conditions representative of Titan's troposphere, while the Ka…

010504 meteorology & atmospheric sciencesInfraredCASSINI VIMSHUYGENS PROBEMONODEUTERATED METHANEAtmospheric sciences01 natural sciences7. Clean energyMethaneSpectral lineTropospherechemistry.chemical_compoundsymbols.namesake0103 physical sciencesSpectral resolutionSpectroscopy010303 astronomy & astrophysicsCLOUD STRUCTURE0105 earth and related environmental sciencesPhysics[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph][PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics][ PHYS.PHYS.PHYS-OPTICS ] Physics [physics]/Physics [physics]/Optics [physics.optics]Astronomy and Astrophysics9500 CM(-1)SPECTROSCOPIC DATABASEM TRANSPARENCY WINDOWComputational physicsAerosolchemistry[ PHYS.PHYS.PHYS-AO-PH ] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]TEMPERATURE-DEPENDENCE13. Climate actionSpace and Planetary SciencesymbolsSHIFT COEFFICIENTSOUTER SOLAR-SYSTEMTitan (rocket family)
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Humusica 2, article 19: Techno humus systems and global change - Conservation agriculture and 4/1000 proposal

2018

International audience; Philosophy can overlap pedology. It is not casual that life begins and finishes in the soil. We separated the concepts of Humipedon, Copedon and Lithopedon. Some sections were dedicated to the founders of the movement for a new type of agriculture (agroecology). They simply proclaim to accompany the process of natural evolution instead of spending a lot of energy in hunting competitor organisms with pesticides or boosting the soil with mineral fertilisation and tillage. The core of the article is built on a biological concept of the soil and shows researches supporting this view. After pointing to the soil structure and illustrating its natural genesis, explaining wh…

010504 meteorology & atmospheric sciencesMarcel Bouché01 natural sciencesAgricultural economicsMatt DamonSoilEnvironmental protectionGreenhouse effect2. Zero hungerOrganic AgricultureAllan SavoryEcologyAgriculture04 agricultural and veterinary sciencesAgricultural and Biological Sciences (miscellaneous)HumusAgriculture; Allan Savory; Andy Weir; Charles Darwin; Conservation agriculture; Earthworms; Homo sapiens; Humus; Humusica; Jeff Lowenfels; Marcel Bouché; Masanobu Fukuoka; Matt Damon; Natural farming; Organic Agriculture; Peat; Soil; Soil aggregates; Soil C sequestration; Soil Organic Carbon; Ecology; Agricultural and Biological Sciences (miscellaneous); Soil ScienceTillageHumusicaSoil aggregatesConservation agricultureAndy Weir[ SDV.SA.SDS ] Life Sciences [q-bio]/Agricultural sciences/Soil studySoil Science[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studyHumus[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsMarcel BouchéMasanobu FukuokaEarthwormsAgroecology0105 earth and related environmental sciences[ SDE.BE ] Environmental Sciences/Biodiversity and EcologyHomo sapiensJeff LowenfelsNatural farmingSoil organic matterSoil C sequestrationGlobal warmingPeatSoil carbon15. Life on land[ SDV.EE.ECO ] Life Sciences [q-bio]/Ecology environment/EcosystemsSoil structureCharles DarwinSoil Organic Carbon13. Climate action040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental science[SDE.BE]Environmental Sciences/Biodiversity and Ecology
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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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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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