Search results for " electronic engineering"

showing 10 items of 8284 documents

Two-year global simulation of L-band brightness temperatures over land

2003

International audience; This letter presents a synthetic L-band (1.4 GHz) multiangular brightness temperature dataset over land surfaces that was simulated at a half-degree resolution and at the global scale. The microwave emission of various land-covers (herbaceous and woody vegetation, frozen and unfrozen bare soil, snow, etc.) was computed using a simple model [L-band Microwave Emission of the Biosphere (L-MEB)] based on radiative transfer equations. The soil and vegetation characteristics needed to initialize the L-MEB model were derived from existing land-cover maps. Continuous simulations from a land-surface scheme for 1987 and 1988 provided time series of the main variables driving t…

010504 meteorology & atmospheric sciences0211 other engineering and technologiesmodeling02 engineering and technologyLand coverVegetation[INFO.INFO-IA]Computer Science [cs]/Computer Aided EngineeringSnow01 natural sciencesPhysics::GeophysicsBrightness temperatureglobal scaleSoil waterRadiative transferGeneral Earth and Planetary SciencesEnvironmental scienceRadiometryL-band radiometryElectrical and Electronic Engineeringsoil moistureWater content[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Generation of global vegetation products from EUMETSAT AVHRR/METOP satellites

2020

We describe the methodology applied for the retrieval of global LAI, FAPAR and FVC from Advanced Very High Resolution Radiometer (AVHRR) onboard the Meteorological-Operational (MetOp) polar orbiting satellites also known as EUMETSAT Polar System (EPS). A novel approach has been developed for the joint retrieval of three parameters (LAI, FVC, and FAPAR) instead of training one model per parameter. The method relies on multi-output Gaussian Processes Regression (GPR) trained over PROSAIL EPS simulations. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. We describe the ma…

010504 meteorology & atmospheric sciencesAdvanced very-high-resolution radiometerComputer scienceImage and Video Processing (eess.IV)0211 other engineering and technologiesPolar orbit02 engineering and technologyVegetationAtmospheric modelElectrical Engineering and Systems Science - Image and Video Processing01 natural sciencesGround-penetrating radarFOS: Electrical engineering electronic engineering information engineeringSatelliteSensitivity (control systems)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Derivation of global vegetation biophysical parameters from EUMETSAT Polar System

2020

Abstract This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological–Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key par…

010504 meteorology & atmospheric sciencesAdvanced very-high-resolution radiometerImage and Video Processing (eess.IV)0211 other engineering and technologies02 engineering and technologyVegetationElectrical Engineering and Systems Science - Image and Video Processing01 natural sciencesAtomic and Molecular Physics and OpticsComputer Science Applications13. Climate actionKrigingFOS: Electrical engineering electronic engineering information engineeringRadiative transferRange (statistics)Environmental scienceSatelliteSensitivity (control systems)Computers in Earth SciencesLeaf area indexEngineering (miscellaneous)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingISPRS Journal of Photogrammetry and Remote Sensing
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Edge-Based Missing Data Imputation in Large-Scale Environments

2021

Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis

010504 meteorology & atmospheric sciencesComputer scienceDistributed computingUrban sensingMobile sensingContext (language use)Information technology02 engineering and technology01 natural sciences[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Smart cityEdge intelligence11. Sustainability0202 electrical engineering electronic engineering information engineeringLeverage (statistics)Edge computingVoronoi tessellation0105 earth and related environmental sciencesSmart cityOut-of-order executionSettore INF/01 - InformaticaMulti-agent systemMissing data imputation020206 networking & telecommunicationsT58.5-58.64Variety (cybernetics)Multi-agent system[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Mobile deviceInformation Systems
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Multioutput Automatic Emulator for Radiative Transfer Models

2018

This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…

010504 meteorology & atmospheric sciencesComputer scienceFlatness (systems theory)Bayesian optimizationSampling (statistics)02 engineering and technologyFunction (mathematics)Atmospheric model01 natural sciencessymbols.namesakeSampling (signal processing)0202 electrical engineering electronic engineering information engineeringsymbolsRadiative transfer020201 artificial intelligence & image processingGaussian process emulatorGaussian processAlgorithm0105 earth and related environmental sciencesInterpolationIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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A Lightweight Prototype of a Magnetometric System for Unmanned Aerial Vehicles

2021

Detection of the Earth’s magnetic field anomalies is the basis of many types of studies in the field of earth sciences and archaeology. These surveys require different ways to carry out the measures but they have in common that they can be very tiring or expensive. There are now several lightweight commercially available magnetic sensors that allow light-UAVs to be equipped to perform airborne measurements for a wide range of scenarios. In this work, the realization and functioning of an airborne magnetometer prototype were presented and discussed. Tests and measures for the validation of the experimental setup for some applications were reported. The flight sessions, appropriately programm…

010504 meteorology & atmospheric sciencesComputer scienceMagnetometerUAVcontrolling unitTP1-1185010502 geochemistry & geophysics01 natural sciencesBiochemistryField (computer science)ArticleAnalytical Chemistrylaw.inventionmagnetometryairborne magnetometerlawSettore GEO/11 - Geofisica ApplicataRange (aeronautics)Electrical and Electronic EngineeringInstrumentation0105 earth and related environmental sciencesChemical technologySystem of measurementarchaeologyAtomic and Molecular Physics and OpticsSystems engineeringSensors
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Automotive Radar in a UAV to Assess Earth Surface Processes and Land Responses

2020

The use of unmanned aerial vehicles (UAVs) in earth science research has drastically increased during the last decade. The reason being innumerable advantages to detecting and monitoring various environmental processes before and after certain events such as rain, wind, flood, etc. or to assess the current status of specific landforms such as gullies, rills, or ravines. The UAV equipped sensors are a key part to success. Besides commonly used sensors such as cameras, radar sensors are another possibility. They are less known for this application, but already well established in research. A vast number of research projects use professional radars, but they are expensive and difficult to hand…

010504 meteorology & atmospheric sciencesComputer scienceUAVReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION0211 other engineering and technologiesComputerApplications_COMPUTERSINOTHERSYSTEMS77 GHz02 engineering and technologylcsh:Chemical technology01 natural sciencesBiochemistryArticleAnalytical Chemistrylaw.inventionARS-408lawlcsh:TP1-1185ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMSElectrical and Electronic EngineeringRadarInstrumentationARS-404021101 geological & geomatics engineering0105 earth and related environmental sciencesRadarAtomic and Molecular Physics and OpticsEarth surfaceAutomotive radarKey (cryptography)Sensors
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Estimating Missing Information by Cluster Analysis and Normalized Convolution

2018

International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.

010504 meteorology & atmospheric sciencesComputer sciencemedia_common.quotation_subjectReal-time computingEnergy Engineering and Power Technology02 engineering and technologyIterative reconstructionsmart city dealsCluster (spacecraft)01 natural sciencesIndustrial and Manufacturing Engineeringnormalized convolutionstandard clustering technique[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]ConvolutionArtificial IntelligenceSmart city11. Sustainability0202 electrical engineering electronic engineering information engineeringLimit (mathematics)SimplicityCluster analysisInstrumentationad-hoc sensors0105 earth and related environmental sciencesmedia_commonSettore INF/01 - InformaticaRenewable Energy Sustainability and the EnvironmentComputer Science Applications1707 Computer Vision and Pattern Recognitionenvironmental informationmissing informationComputer Networks and CommunicationKernel (image processing)020201 artificial intelligence & image processingcluster analysis2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)
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SAR Image Classification Combining Structural and Statistical Methods

2011

The main objective of this paper is to develop a new technique of SAR image classification. This technique combines structural parameters, including the Sill, the slope, the fractal dimension and the range, with statistical methods in a supervised image classification. Thanks to the range parameter, we define the suitable size of the image window used in the proposed approach of supervised image classification. This approach is based on a new way of characterising different classes identified on the image. The first step consists in determining relevant area of interest. The second step consists in characterising each area identified, by a matrix. The last step consists in automating the pr…

010504 meteorology & atmospheric sciencesContextual image classificationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)Pattern recognition02 engineering and technology01 natural sciencesFractal dimensionImage (mathematics)Range (mathematics)Matrix (mathematics)Fractal[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceVariogrambusinessComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesMathematics
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Exploring Effective Ecosystems in Disaster Management: Case studies of Japan and Nepal

2017

010504 meteorology & atmospheric sciencesEmergency managementbusiness.industryEnvironmental resource management0202 electrical engineering electronic engineering information engineering020206 networking & telecommunicationsEcosystem02 engineering and technologySociologyInformation ecologybusiness01 natural sciences0105 earth and related environmental sciencesProceedings of the 50th Hawaii International Conference on System Sciences (2017)
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