Search results for " SENSING"

showing 10 items of 1517 documents

Living on the edge of a shrinking habitat: the ivory gull, Pagophila eburnea, an endangered sea-ice specialist.

2016

International audience; The ongoing decline of sea ice threatens many Arctic taxa, including the ivory gull. Understanding how ice-edges and ice concentrations influence the distribution of the endangered ivory gulls is a prerequisite to the implementation of adequate conservation strategies. From 2007 to 2013, we used satellite transmitters to monitor the movements of 104 ivory gulls originating from Canada, Greenland, Svalbard-Norway and Russia. Although half of the positions were within 41 km of the ice-edge (75% within 100 km), approximately 80% were on relatively highly concentrated sea ice. Ivory gulls used more concentrated sea ice in summer, when close to their high-Arctic breeding …

0106 biological sciencesSatellite trackingCharadriiformesseabirdEndangered speciesContext (language use)[SDV.BID]Life Sciences [q-bio]/Biodiversity010603 evolutionary biology01 natural sciencesice-edgeCharadriiformesArcticbiology.animalIce concentrationSatellite microwave radiometersSea iceAnimalsIce CoverIce-edge14. Life underwaterEcosystem[ SDV.BID ] Life Sciences [q-bio]/Biodiversitygeography[ SDE.BE ] Environmental Sciences/Biodiversity and Ecologygeography.geographical_feature_categorybiologyArctic RegionsEcologysatellite tracking010604 marine biology & hydrobiologyEndangered SpeciesSpecial Featuresatellite microwave radiometersSeabird15. Life on landbiology.organism_classificationAgricultural and Biological Sciences (miscellaneous)FisheryHabitatArcticRemote Sensing TechnologyConservation statusAnimal MigrationSeasonsice concentrationSeabird[SDE.BE]Environmental Sciences/Biodiversity and EcologyGeneral Agricultural and Biological Sciences
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Downscaling rice yield simulation at sub-field scale using remotely sensed LAI data

2019

Abstract Crop modeling and remote sensing are key tools to gain deeper understanding on cropping system dynamics and, ultimately, to increase the sustainability of agricultural productions. This study presents a system to estimate rice yields at sub-field scale based on the integration of a biophysical model and remotely sensed products. Leaf area index (LAI) data derived from decametric optical imageries (i.e., Landsat-8, Landsat-7 and Sentinel–2A) were assimilated into the WARM rice model via automatic recalibration of crop parameters at a fine spatial resolution (30 m × 30 m), targeting the lowest error between simulated and remotely sensed LAI. The performance of the system was evaluate…

0106 biological sciencesSoil SciencePlant Science01 natural sciencesYield (wine)WARM modelCrop modelLeaf area indexCropping systemDecision support systemRemote sensing2. Zero hungerCrop yieldYield predictions04 agricultural and veterinary sciencesRemote sensing15. Life on landAgronomyData assimilation040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental sciencePrecision agricultureScale (map)Agronomy and Crop ScienceCropping010606 plant biology & botanyDownscalingEuropean Journal of Agronomy
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Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images

2018

High Amplitude Internal Waves (HAIWs) are physical processes observed in the Strait of Gibraltar (the narrow channel between the Atlantic Ocean and the Mediterranean Sea). These internal waves are generated over the Camarinal Sill (western side of the strait) during the tidal outflow (toward the Atlantic Ocean) when critical hydraulic conditions are established. HAIWs remain over the sill for up to 4 h until the outflow slackens, being then released (mostly) towards the Mediterranean Sea. These have been previously observed using Synthetic Aperture Radar (SAR), which captures variations in surface water roughness. However, in this work we use high resolution optical remote sensing, with the…

0106 biological sciencesSynthetic aperture radargeographygeography.geographical_feature_category010504 meteorology & atmospheric sciencesStrait of GibraltarHICO010604 marine biology & hydrobiologyMultispectral imageHigh amplitude internal wavesHyperspectral imagingAquatic ScienceInternal waveOceanography01 natural sciencesMediterranean seaAlgeciras baySillOutflowSatelliteSentinel-2Geology0105 earth and related environmental sciencesRemote sensingEstuarine, Coastal and Shelf Science
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Vegetation structure and greenness in Central Africa from Modis multi-temporal data.

2013

African forests within the Congo Basin are generally mapped at regional scale as broad-leaved evergreen forests, with a main distinction between terra-firme and swamp forests types. At the same time, commercial forest inventories, as well as national maps, have highlighted a strong spatial heterogeneity of forest types. A detailed vegetation map generated using consistent methods is needed to inform decision makers about spatial forest organisation and theirs relationships with environmental drivers in the context of global change. We propose a multi-temporal remotely sensed data approach to characterize vegetation types using vegetation index annual profiles. The classifications identified…

0106 biological scienceshttp://aims.fao.org/aos/agrovoc/c_28568Time Factors010504 meteorology & atmospheric sciencesDatabases FactualRainEcological Parameter Monitoringhttp://aims.fao.org/aos/agrovoc/c_900018001 natural sciencesTrees[ SDE ] Environmental Sciencesremote sensinghttp://aims.fao.org/aos/agrovoc/c_3062K01 - Foresterie - Considérations généralesDynamique des populationsForêt tropicale humidehttp://aims.fao.org/aos/agrovoc/c_6498http://aims.fao.org/aos/agrovoc/c_29008geography.geographical_feature_categoryCentral AfricaEcologyInventaire forestierVegetationArticlesClassificationSpatial heterogeneity[ SDE.MCG ] Environmental Sciences/Global ChangesDeciduoushttp://aims.fao.org/aos/agrovoc/c_7976CongoP31 - Levés et cartographie des solsForêt[SDE]Environmental SciencesSeasonshttp://aims.fao.org/aos/agrovoc/c_1432General Agricultural and Biological Scienceshttp://aims.fao.org/aos/agrovoc/c_34911Research ArticleF40 - Écologie végétaleTélédétectionClimate Change[SDE.MCG]Environmental Sciences/Global ChangesSpectroscopie infrarougeContext (language use)69Typologie010603 evolutionary biologySwampGeneral Biochemistry Genetics and Molecular BiologyCarbon Cycle[ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces environmentHumansAfrica Centralhttp://aims.fao.org/aos/agrovoc/c_1666http://aims.fao.org/aos/agrovoc/c_1344http://aims.fao.org/aos/agrovoc/c_8176[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmenthttp://aims.fao.org/aos/agrovoc/c_6111Ecosystem0105 earth and related environmental sciencesChangement climatiquegeographyCartographiehttp://aims.fao.org/aos/agrovoc/c_24174Enhanced vegetation index15. Life on landEvergreenVégétationStructure du peuplement13. Climate actionCouvert forestierPhysical geographyU30 - Méthodes de recherchehttp://aims.fao.org/aos/agrovoc/c_1653tropical rainforestTropical rainforest
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Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science

2021

Remote sensing methods enable detection of solar-induced chlorophyll a fluorescence. However, to unleash the full potential of this signal, intensive cross-disciplinary work is required to harmonize biophysical and ecophysiological studies. For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-in…

0106 biological sciencesklorofylliChlorophyll a010504 meteorology & atmospheric sciencesEarth scienceEcology (disciplines)Plant Scienceekofysiologia01 natural sciencesFluorescencebiofysiikkayhteyttäminenchemistry.chemical_compoundLEAFLEAVESWATERPhotosynthesisCO2 ASSIMILATIONSCOTS PINE[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentMolecular Biology0105 earth and related environmental sciences[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereChlorophyll ASUN-INDUCED FLUORESCENCEfluoresenssiBiogeochemistrykasvillisuus15. Life on land11831 Plant biologyReflectivityREFLECTANCEPlant LeavesEarth system scienceddc:580RESOLUTIONchemistryPHOTOSYSTEM-I13. Climate actionRemote Sensing TechnologyEarth SciencessatelliittikuvausEnvironmental sciencekaukokartoitus010606 plant biology & botanyNature Plants
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The flex end-to-end simulator: From concept phase (A/B1) to ground segment and operations (C/D)

2018

ESA's FLEX/Sentinel-3 tandem mission aims at mapping Sun-induced fluorescence (SIF) as a proxy to quantify photosynthetic activity of terrestrial vegetation. Due to the complexity of the mission concept and stringent requirements for the data processing algorithms, ESA developed a Phase A/B1 End-to-End Mission Performance Simulator (E2ES) tool to reproduce the expected mission performance and check the mission and instrument concepts. In the current Phase C/D, the E2ES concept must evolve to consolidate the whole data processing chain, providing an accurate figures of the whole mission error budget and serving as a roadmap for the future development of FLEX Ground Segment. This paper gives …

0106 biological sciencesproductivityComputer scienceFIS/06 - FISICA PER IL SISTEMA TERRA E PER IL MEZZO CIRCUMTERRESTRE0211 other engineering and technologiesGEO/12 - OCEANOGRAFIA E FISICA DELL'ATMOSFERA02 engineering and technologyMission simulator01 natural sciencesFLEXremote sensingEnd-to-end principleHyperspectralvegetationSun-induced chlorophyll fluorescenceSoftware designRadiometryFLEXfluorescenceGround segmentSentinel-3Simulation010606 plant biology & botany021101 geological & geomatics engineering
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Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study

2019

Traditional industry is seeing an increasing demand for more autonomous and flexible manufacturing in unstructured settings, a shift away from the fixed, isolated workspaces where robots perform predefined actions repetitively. This work presents a case study in which a robotic manipulator, namely a KUKA KR90 R3100, is provided with smart sensing capabilities such as vision and adaptive reasoning for real-time collision avoidance and online path planning in dynamically-changing environments. A machine vision module based on low-cost cameras and color detection in the hue, saturation, value (HSV) space is developed to make the robot aware of its changing environment. Therefore, this vision a…

0209 industrial biotechnologyComputer scienceMachine visionTKReal-time computingRobot manipulator02 engineering and technologyWorkspaceAdaptive Reasoninglcsh:Chemical technologyBiochemistryHuman–robot interactionArticleAnalytical ChemistrySettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchinehuman-robot interaction020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringlcsh:TP1-1185Motion planningElectrical and Electronic EngineeringInstrumentationpath planningCollision avoidancerobot controlsmart sensingAdaptive reasoningdynamic environmentsAtomic and Molecular Physics and OpticsRobot control:Engineering::Mechanical engineering [DRNTU]ObstacleDynamic EnvironmentsRobot020201 artificial intelligence & image processingadaptive reasoning
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Nonlinear statistical retrieval of surface emissivity from IASI data

2017

Emissivity is one of the most important parameters to improve the determination of the troposphere properties (thermodynamic properties, aerosols and trace gases concentration) and it is essential to estimate the radiative budget. With the second generation of infrared sounders, we can estimate emissivity spectra at high spectral resolution, which gives us a global view and long-term monitoring of continental surfaces. Statistically, this is an ill-posed retrieval problem, with as many output variables as inputs. We here propose nonlinear multi-output statistical regression based on kernel methods to estimate spectral emissivity given the radiances. Kernel methods can cope with high-dimensi…

0211 other engineering and technologies020206 networking & telecommunications02 engineering and technologyAtmospheric modelInfrared atmospheric sounding interferometerLeast squaresKernel method13. Climate actionKernel (statistics)Linear regression0202 electrical engineering electronic engineering information engineeringEmissivityKernel regressionPhysics::Atmospheric and Oceanic Physics021101 geological & geomatics engineeringRemote sensingMathematics2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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An Artificial Bee Colony Approach for Classification of Remote Sensing Imagery

2018

This paper presents a novel Artificial Bee Colony (ABC) approach for supervised classification of remote sensing images. One proposes to apply an ABC algorithm to optimize the coefficients of the set of polynomial discriminant functions. We have experimented the proposed ABC-based classifier algorithm for a Landsat 7 ETM+ image database, evaluating the influence of the ABC model parameters on the classifier performances. Such ABC model parameters are: numbers of employed/onlooker/scout bees, number of epochs, and polynomial degree. One has compared the best ABC classifier Overall Accuracy (OA) with the performances obtained using a set of benchmark classifiers (NN, NP, RBF, and SVM). The re…

021103 operations researchArtificial neural networkComputer science0211 other engineering and technologies02 engineering and technologyArtificial bee colony algorithmSupport vector machineStatistical classificationAbc modelComputingMethodologies_PATTERNRECOGNITIONDiscriminant0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingDegree of a polynomialClassifier (UML)Remote sensing2018 10th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)
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Détection cérébrale du glucose, plasticité neuronale et métabolisme énergétique

2017

Resume L’apport d’energie est, dans la plupart des cas extremement, bien controle et est ajuste aux depenses d’energie d’un individu donne, c’est ce que l’on nomme l’homeostasie energetique. Cet equilibre repose en grande partie sur la capacite du systeme nerveux central a evaluer le statut energetique de l’organisme, en integrant differents signaux provenant de la peripherie dont le glucose. Cette revue porte sur les decouvertes recentes concernant l’identification des differents mecanismes cellulaires et moleculaires, des types cellulaires et de leur phenotype, des reseaux neuronaux et de leur plasticite. Ainsi il est maintenant etabli qu’il existe differents types de neurones repondant, …

0301 basic medicine03 medical and health sciences030104 developmental biologyNutrition and DieteticsChemistryEnergy metabolismMedicine (miscellaneous)Glucose sensingMolecular biologyCahiers de Nutrition et de Diététique
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