Search results for "Logic"

showing 10 items of 33629 documents

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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A Comparison between Drifter and X-Band Wave Radar for Sea Surface Current Estimation

2016

This paper deals with exploitation of the wave radar system for sea surface current estimation in a coastal zone. In particular, we present the results of the processing of the radar data collected by an X-band marine radar installed in Capo Granitola site, which is located in the south-west part of Sicily, on 15 May 2015. The effectiveness of the data processing is analyzed by comparing the wave radar estimated sea surface current with that provided by the Lagrangian drifters along its movement trajectory. During the measurement campaign, three drifter releases are carried out and for each one the comparison is provided in terms of the mean error and standard deviation. In addition, we rep…

010504 meteorology & atmospheric sciencesmarine X-band radar0211 other engineering and technologiesX bandsea state monitoring02 engineering and technologySea state01 natural sciencesStandard deviationlaw.inventionlawLagrangian driftersRadarsea surface current estimationlcsh:SciencePhysics::Atmospheric and Oceanic Physics021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaGeodesyDrifterWavelengthWave radarGeneral Earth and Planetary Scienceslcsh:QSignificant wave heightGeologyRemote Sensing
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Evaluation of different methods to retrieve the hemispherical downwelling irradiance in the thermal infrared region for field measurements

2013

International audience; The thermal infrared hemispherical downwelling irradiance (HDI) emitted by the atmosphere and surrounding elements contributes through reflection to the signal measured over an observed surface by remote sensing. This irradiance must be estimated in order to obtain accurate values of land-surface temperature (LST). There are some fast methods to measure the HDI with a single measurement pointing to the sky at a specified viewing direction, but these methods require completely cloud-free or cloudy skies, and they do not account for the radiative contribution of surrounding elements. Another method is the use of a diffuse reflectance panel (usually, a rough gold-coated…

010504 meteorology & atmospheric sciencesmedia_common.quotation_subject[SDV]Life Sciences [q-bio]0211 other engineering and technologiesIrradiance02 engineering and technologyAtmospheric sciences01 natural sciencesBANDAtmosphereRadiative transferEmissivityElectrical and Electronic EngineeringTEMPERATURE021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingmedia_commonRadiometerMODTRANdiffuse reflectance panelAngular measurementsthermal infrared (TIR)EMISSIVITYSOILShemispherical downwelling radiance13. Climate actionSkyfield measurements[SDE]Environmental SciencesReflection (physics)General Earth and Planetary SciencesEnvironmental science
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Driving through floodwater: Exploring driver decisions through the lived experience

2019

Abstract More than half of unintentional flood-related drowning deaths in Australia are due to driving through floodwater, despite on-going public campaigns. Currently, there is a knowledge gap in understanding why individuals choose to drive through floodwater and the decisions that may lead to such actions. We propose that a more complete understanding of individuals’ decisions to drive through floodwater needs to be considered in the context of the lived experience. Australian drivers (N = 20) who had intentionally driven through floodwater participated in semi-structured interviews. Data were analysed using a thematic analysis based in an interpretivist approach. Past experience, indivi…

010504 meteorology & atmospheric sciencesmedia_common.quotation_subjectflooded waterways0211 other engineering and technologiesPsychological interventionContext (language use)02 engineering and technologydriving skills01 natural sciencesuskomuksetkäyttäytymismallithukkuminenPerceptiondrivingHuman geographyta5150105 earth and related environmental sciencesmedia_common021110 strategic defence & security studiesdrowningbusiness.industryLived experienceGeologytulvatajotaitofloodPublic relationsGeotechnical Engineering and Engineering GeologybeliefsThematic analysisConstruct (philosophy)businessPsychologySafety ResearchInternational Journal of Disaster Risk Reduction
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Analysis of the radar vegetation index and assessment of potential for improvement

2018

The Radar Vegetation Index (RVI) is widely applied to indicate vegetation cover. The index includes the backscattering intensities of co- and cross-polarization that do not only contain information coming from vegetation scattering at longer wavelength (L-band), but also from the soil underneath. A forward modelling approach using active and passive microwave-derived parameters to obtain the scattering contribution of the soil is pursued. The idea of this research study is a subtraction of the attenuated soil scattering contribution from the measured backscattering intensities, to provide a clean vegetation-based solution, called improved RVI (RVII). For latter analysis, the vegetation volu…

010504 meteorology & atmospheric sciencesmicrowave[SDV]Life Sciences [q-bio]0211 other engineering and technologiesSoil science02 engineering and technology01 natural scienceslaw.inventionVegetation coverlawmedicineRange (statistics)RadarComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRadarVegetationScatteringSMAP15. Life on landWavelength[SDE]Environmental SciencesVegetation water contentEnvironmental scienceactive-passive sensingmedicine.symptomVegetation IndexVegetation (pathology)Cartography
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Global Sensitivity Analysis of Leaf-Canopy-Atmosphere RTMs: Implications for Biophysical Variables Retrieval from Top-of-Atmosphere Radiance Data.

2019

Knowledge of key variables driving the top of the atmosphere (TOA) radiance over a vegetated surface is an important step to derive biophysical variables from TOA radiance data, e.g., as observed by an optical satellite. Coupled leaf-canopy-atmosphere Radiative Transfer Models (RTMs) allow linking vegetation variables directly to the at-sensor TOA radiance measured. Global Sensitivity Analysis (GSA) of RTMs enables the computation of the total contribution of each input variable to the output variance. We determined the impacts of the leaf-canopy-atmosphere variables into TOA radiance using the GSA to gain insights into retrievable variables. The leaf and canopy RTM PROSAIL was coupled with…

010504 meteorology & atmospheric sciencesradiative transfer models0211 other engineering and technologiesemulation02 engineering and technologytop-of-atmosphere radiance data01 natural sciencesEmulation; Global sensitivity analysis; Machine learning; MODTRAN; PROSAIL; Radiative transfer models; Retrieval; Sentinel-2; Top-of-atmosphere radiance dataKrigingRange (statistics)Radiative transferLeaf area indexlcsh:Scienceretrieval021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingMODTRANPROSAILMODTRANAtmospheric correctionradiative transfer models; global sensitivity analysis; emulation; machine learning; top-of-atmosphere radiance data; PROSAIL; MODTRAN; retrieval; Sentinel-2machine learningglobal sensitivity analysisLookup tableRadianceGeneral Earth and Planetary SciencesEnvironmental sciencelcsh:QSentinel-2Remote sensing
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Rare earth element and neodymium isotope tracing of sedimentary rock weathering

2020

Chemical weathering plays an important role in sequestering atmospheric CO2, but its potential influence on global climate over geological timescales remains debated. To some extent, this uncertainty arises from the difficulty in separating the respective contribution of sedimentary and crystalline silicate rocks to past weathering rates in the geological record; two types of rocks having presumably different impact on the long-term carbon cycle. In this study, we investigate the use of rare earth element (REE) and neodymium isotopes (εNd) in leached iron oxide fractions of river sediments for tracing the origin of weathered rocks on continents. A new index, called ‘concavity index’ (CI), i…

010504 meteorology & atmospheric sciencessub-01Mid-REE enrichmentGeochemistrySilicate weatheringWeatheringConcavity indexengineering.materialStructural basin010502 geochemistry & geophysicsGeologic record01 natural sciencesIron oxideschemistry.chemical_compoundGeochemistry and Petrology[SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry[CHIM]Chemical Sciences0105 earth and related environmental sciencesgeographygeography.geographical_feature_categorySulphide weatheringNeodymium isotopesGeology15. Life on landWorld riversSilicateCratonchemistry13. Climate actionCarbonate weatheringengineeringCarbonateSedimentary rockPyriteGeology
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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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Global-Scale Evaluation of Roughness Effects on C-Band AMSR-E Observations

2015

Quantifying roughness effects on ground surface emissivity is an important step in obtaining high-quality soil moisture products from large-scale passive microwave sensors. In this study, we used a semi-empirical method to evaluate roughness effects (parameterized here by the parameter) on a global scale from AMSR-E (Advanced Microwave Scanning Radiometer for EOS) observations. AMSR-E brightness temperatures at 6.9 GHz obtained from January 2009 to September 2011, together with estimations of soil moisture from the SMOS (Soil Moisture and Ocean Salinity) L3 products and of soil temperature from ECMWF’s (European Centre for Medium-range Weather Forecasting) were used as inputs in a retrieval…

010504 meteorology & atmospheric sciencestélédétectionScience0211 other engineering and technologiesWeather forecasting[SDU.STU]Sciences of the Universe [physics]/Earth SciencesElectromagnétismesoil surface roughness02 engineering and technologySurface finishcomputer.software_genredonnée satellite01 natural sciencesSciences de la TerreNormalized Difference Vegetation Indexsoil moisture;soil surface roughness;AMSR-EElectromagnetismEmissivitySurface roughnessTraitement du signal et de l'image14. Life underwaterWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometercapteur smosQSignal and Image processingradiométrie microondesVegetationAMSR-E15. Life on land[SPI.ELEC]Engineering Sciences [physics]/ElectromagnetismEarth SciencesGeneral Earth and Planetary SciencesEnvironmental sciencesoil moisturecomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingRemote Sensing
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