Search results for "LIDA"

showing 10 items of 7334 documents

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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NPP VIIRS land surface temperature product validation using worldwide observation networks.

2013

International audience; Thermal infrared satellite observations of the Earth's surface are key components in estimating the surface skin temperature over global land areas. This work presents validation methodologies to estimate the quantitative uncertainty in Land Surface Temperature (LST) product derived from the Visible Infrared Imager Radiometer Suite (VIIRS) onboard Suomi National Polar-orbiting Partnership (NPP) using ground-based measurements currently made operationally at many field and weather stations around the world. Over heterogeneous surfaces in terms of surface types or biophysical properties (e.g., vegetation density, emissivity), the validation protocol accounts for land s…

010504 meteorology & atmospheric sciencesMeteorologyLand surface temperature0211 other engineering and technologies02 engineering and technology01 natural sciencesIndex Terms— Land Surface TemperaturePhysics::Geophysics[SDU] Sciences of the Universe [physics]EmissivityProduct (category theory)ComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingvalidationThermal infraredRadiometerspatial heterogeneityVegetationNPP VIIRS13. Climate actionground-based LST[SDU]Sciences of the Universe [physics][SDE]Environmental SciencesEnvironmental scienceSatelliteSpatial variability
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A Cloud masking algorithm for the XBAER aerosol retrieval using MERIS data

2017

Abstract To determine aerosol optical thickness, AOT, and other geophysical parameters describing conditions in the atmosphere and at the earth's surface by inversion of remote sensing measurements from space based instrumentation, it is necessary to separate ground scenes into cloud free and cloudy or cloud contaminated. Identifying the presence of cloud in a ground scene and establishing an accurate and adequate cloud mask is a challenging task. In this study, measurements by the European Space Agency (ESA) MEdium Resolution Imaging Spectrometer (MERIS) have been used to develop a cloud identification and cloud mask algorithm for preprocessing prior to application of the new algorithm cal…

010504 meteorology & atmospheric sciencesMeteorologySYNOPbusiness.industryCloud topCloud fraction0211 other engineering and technologiesSoil ScienceGeologyCloud computing02 engineering and technology01 natural sciencesSCIAMACHYLidarCloud heightRadianceEnvironmental scienceComputers in Earth SciencesbusinessAlgorithm021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Hydrological drivers of wetland vegetation community distribution within Everglades National Park, Florida

2010

The influence of hydrological dynamics on vegetation distribution and the structuring of wetland environments is of growing interest as wetlands are modified by human action and the increasing threat from climate change. Hydrological properties have long been considered a driving force in structuring wetland communities. We link hydrological dynamics with vegetation distribution across Everglades National Park (ENP) using two publicly available datasets to study the probability structure of the frequency, duration, and depth of inundation events along with their relationship to vegetation distribution. This study is among the first to show hydrologic structuring of vegetation communities at…

010504 meteorology & atmospheric sciencesRange (biology)Climate changeWetland010501 environmental sciences01 natural sciencesModelsVegetation typeValidationLandscapeTemporal scales0105 earth and related environmental sciencesWater Science and TechnologyHydrologyEverglades Vegetation Hydrology Wetlandsgeographygeography.geographical_feature_categoryVegetationNational parkSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaCommunity structureVegetation15. Life on landEvergladesScale13. Climate actionWetlandsEnvironmental scienceHydrology
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PHYSICS-based retrieval of scattering albedo and vegetation optical depth using multi-sensor data integration

2017

Vegetation optical depth and scattering albedo are crucial parameters within the widely used τ-ω model for passive microwave remote sensing of vegetation and soil. A multi-sensor data integration approach using ICESat lidar vegetation heights and SMAP radar as well as radiometer data enables a direct retrieval of the two parameters on a physics-derived basis. The crucial step within the retrieval methodology is the calculus of the vegetation scattering coefficient KS, where one exact and three approximated solutions are provided. It is shown that, when using the assumption of a randomly oriented volume, the backscatter measurements of the radar provide a sufficient first order estimate and …

010504 meteorology & atmospheric sciencesScattering albedo0208 environmental biotechnologyradiometry02 engineering and technologyretrieval methodologycomputer.software_genre01 natural scienceslaw.inventionlawremote sensing by radarRadaractive-passive microwavesPhysics::Atmospheric and Oceanic PhysicsIndexespassive microwave remote sensingRemote sensingremote sensing by laser beamGeographyLidaroptical radarcrucial parametersmedicine.symptomvegetation scattering coefficientData integrationBackscattervegetation mappingta1171τ-ω modelsoilPhysics::GeophysicsICESat lidar vegetation heightsvegetationmedicineVegetation optical depthbackscatter0105 earth and related environmental sciencesRemote sensingsensor fusionRadiometerScatteringnovel multisensor approachSMAPAlbedoMulti-sensor020801 environmental engineeringradiometer dataVegetation (pathology)multisensor data integration approachcomputerICESatalbedo
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Sun-Induced Chlorophyll Fluorescence I: Instrumental Considerations for Proximal Spectroradiometers

2019

Growing interest in the proximal sensing of sun-induced chlorophyll fluorescence (SIF) has been boosted by space-based retrievals and up-coming missions such as the FLuorescence EXplorer (FLEX). The European COST Action ES1309 “Innovative optical tools for proximal sensing of ecophysiological processes” (OPTIMISE, ES1309; https://optimise.dcs.aber.ac.uk/) has produced three manuscripts addressing the main current challenges in this field. This article provides a framework to model the impact of different instrument noise and bias on the retrieval of SIF; and to assess uncertainty requirements for the calibration and characterization of state-of-the-art SIF-oriented spectroradiom…

010504 meteorology & atmospheric sciencesUFSP13-8 Global Change and BiodiversitySensor model0211 other engineering and technologiesEarth and Planetary Sciences(all)02 engineering and technology01 natural sciencesErrorsensor modelSpectroradiometerSun-induced chlorophyll fluorescencesun-induced chlorophyll fluorescence; spectroradiometer; sensor model; uncertainty; errorCalibrationCost actionuncertaintylcsh:ScienceChlorophyll fluorescencesun-induced chlorophyll fluorescence/dk/atira/pure/subjectarea/asjc/1900021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingNoise (signal processing)1900 General Earth and Planetary SciencesUncertaintySensor modelReflectivityerror3. Good healthValidation methodsSpectroradiometerspectroradiometerEnvironmental science570 Life sciences; biologyGeneral Earth and Planetary Scienceslcsh:QRemote Sensing
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Predicting year of plantation with hyperspectral and lidar data

2017

This paper introduces a methodology for predicting the year of plantation (YOP) from remote sensing data. The application has important implications in forestry management and inventorying. We exploit hyperspectral and LiDAR data in combination with state-of-the-art machine learning classifiers. In particular, we present a complete processing chain to extract spectral, textural and morphological features from both sensory data. Features are then combined and fed a Gaussian Process Classifier (GPC) trained to predict YOP in a forest area in North Carolina (US). The GPC algorithm provides accurate YOP estimates, reports spatially explicit maps and associated confidence maps, and provides sens…

010504 meteorology & atmospheric sciencesbusiness.industryComputer scienceForest managementFeature extraction0211 other engineering and technologiesHyperspectral imagingPattern recognition02 engineering and technologyVegetation15. Life on land01 natural sciencessymbols.namesakeLidarsymbolsLidar dataArtificial intelligencebusinessClassifier (UML)Gaussian process021101 geological & geomatics engineering0105 earth and related environmental sciences2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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Estimating Gravimetric Moisture of Vegetation Using an Attenuation-Based Multi-Sensor Approach

2018

Estimating parameters for global climate models via combined active and passive microwave remote sensing data has been a subject of intensive research in recent years. A variety of retrieval algorithms has been proposed for the estimation of soil moisture, vegetation optical depth and other parameters. A novel attenuation-based retrieval approach is proposed here to globally estimate the gravimetric moisture of vegetation (m g ) and retrieve information about the amount of water [kg] per amount of wet vegetation [kg]. The parameter m g is particularly interesting for agro-ecosystems, to assess the status of growing vegetation. The key feature of the proposed approach is that it relies on mu…

010504 meteorology & atmospheric sciencesgravimetric moisture0211 other engineering and technologies02 engineering and technology01 natural scienceslaw.inventionlawVegetation optical depthRadarWater contentattenuation021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingLidarRadarVegetationMoistureAttenuationMicrowave radiometerVegetationSMAPMulti-sensorLidarGravimetric analysisRadiometer
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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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Un assemblage inhabituel d’insectivores au Miocène inférieur du Sud-Ouest de l’Europe : les talpidés et les dimylidés du bassin de Ribesalbes–Alcora …

2019

The Miocene record of talpids and dimylids in south-western Europe is very scarce. In the present work, we study for the first time the talpids and complete the description of the dimylids, already started with a new species of the genus Plesiodimylus from the Ribesalbes–Alcora Basin (MN4, lower Aragonian, early Miocene) by Crespo et al. (2018). The talpids recovered inRibesalbes–Alcora comprise themost common Desmanodon daamsi and Desmanella fejfari, for which the last known occurrence is recorded here. The dimylids comprise the species Plesiodimylus ilercavonicus, which expands the biostratigraphic record of the genus and species and has been found in a new site. On the other hand, we dis…

010506 paleontology060101 anthropologyGeneral EngineeringInsectivorePALAEOECOLOGY06 humanities and the artsStructural basin01 natural sciencesPaleontologíaCiencias de la Tierra y relacionadas con el Medio Ambiente//purl.org/becyt/ford/1 [https]Paleontology//purl.org/becyt/ford/1.5 [https]GeographyGenusEARLY MIOCENEDIMYLIDAEAssemblage (archaeology)0601 history and archaeologyRIBESALBES–ALCORA BASINTALPIDAECIENCIAS NATURALES Y EXACTAS0105 earth and related environmental sciences
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