Search results for "TIM"

showing 10 items of 25123 documents

Quantifying and easing conflicting goals between interest groups in natural resource planning

2019

Management of natural resources at the regional level is a compromise between a variety of objectives and interests. At the local level, management of the forests depends upon the ownership structure, with forest owners using their forests as they see fit. A potential conflict occurs if the forest owners’ management decisions are counter to the interests of society in general or the industry that relies on the forest resource as their raw material. We explore the intensity of this conflict at the regional level in several large boreal forest production landscapes. To explore the conflict, we investigate three main interest groups: (i) economically oriented forest owners; (ii) industry grou…

010504 meteorology & atmospheric sciencesCompromisemedia_common.quotation_subjecttehokkuusconflict management010501 environmental sciences01 natural sciencesmultifunctionalityoptimointiboreal forestEnvironmental planningFinlandbiodiversity0105 earth and related environmental sciencesmedia_commonGlobal and Planetary ChangeEcologyforest planningforestryForestrykonfliktit15. Life on landluonnon monimuotoisuusmetsätNatural resourcebiodiversiteettiVariety (cybernetics)boreaalinen vyöhykeekosysteemipalvelutefficiencyBusinessmetsänhoitoecosystem servicesoptimizationCanadian Journal of Forest Research
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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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Anticipating the impact of pitfalls in kinetic biodegradation parameter estimation from substrate depletion curves of organic pollutants

2019

[EN] Accurate and reliable estimation of kinetic parameters of pollutant biodegradation processes is essential for environmental and health risk assessment. Common biodegradation models proposed in the literature, such as the nonlinear Monod equation and its simplified versions (e.g. Michaelis-Menten-like and first-order equations), are problematic in terms of accuracy of kinetic parameters due to the parameter correlation. However, a comparison between these models in terms of accuracy and reliability, related to data imprecision, has not been performed in the literature. This task is necessary, mainly because the model selection cannot be straightforward, as shown in this work. To facilit…

010504 meteorology & atmospheric sciencesComputer scienceHealth Toxicology and Mutagenesis010501 environmental sciencesToxicology01 natural sciencesRisk AssessmentModelling depletion curveMonod equationLimit (mathematics)Reliability (statistics)0105 earth and related environmental sciencesPollutantObservational errorEstimation theoryModel selectionReproducibility of ResultsModel comparisonGeneral MedicineModels TheoreticalPollutionNonlinear systemKineticsBiodegradation EnvironmentalParameter estimationsBiodegradationEnvironmental PollutantsBiochemical engineeringPitfallsAlgorithms
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Controlled time integration for the numerical simulation of meteor radar reflections

2016

We model meteoroids entering the Earth[U+05F3]s atmosphere as objects surrounded by non-magnetized plasma, and consider efficient numerical simulation of radar reflections from meteors in the time domain. Instead of the widely used finite difference time domain method (FDTD), we use more generalized finite differences by applying the discrete exterior calculus (DEC) and non-uniform leapfrog-style time discretization. The computational domain is presented by convex polyhedral elements. The convergence of the time integration is accelerated by the exact controllability method. The numerical experiments show that our code is efficiently parallelized. The DEC approach is compared to the volume …

010504 meteorology & atmospheric sciencesComputer scienceMETEORPLASMATIC OBJECTSRADAR REFLECTIONS01 natural sciencesplasmatic objectslaw.inventionINTEGRAL EQUATIONSlawRadar010303 astronomy & astrophysicsSpectroscopyEARTH ATMOSPHEREvolume integral equationRadiationPLASMANUMERICAL MODELSMathematical analysisFinite differenceNUMERICAL METHODMETEORSAtomic and Molecular Physics and OpticsCALCULATIONSControllabilityDISCRETE EXTERIOR CALCULUSAstrophysics::Earth and Planetary AstrophysicsMAGNETOPLASMADiscretizationRADAR REFLECTIONTIME DOMAIN ANALYSISVOLUME INTEGRAL EQUATIONdiscrete exterior calculusELECTROMAGNETIC SCATTERINGOpticsFINITE DIFFERENCE TIME DOMAIN METHOD0103 physical sciencesSCATTERINGTime domainmeteorsNUMERICAL METHODS0105 earth and related environmental sciencesta113ta114Computer simulationbusiness.industryta111Finite-difference time-domain methodRADARDiscrete exterior calculuselectromagnetic scatteringradar reflectionsELECTROMAGNETIC METHODmeteoritbusinessJournal of Quantitative Spectroscopy and Radiative Transfer
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Cloud detection on the Google Earth engine platform

2017

The vast amount of data acquired by current high resolution Earth observation satellites implies some technical challenges to be faced. Google Earth Engine (GEE) platform provides a framework for the development of algorithms and products built over this data in an easy and scalable manner. In this paper, we take advantage of the GEE platform capabilities to exploit the wealth of information in the temporal dimension by processing a long time series of satellite images. A cloud detection algorithm for Landsat-8, which uses previous images of the same location to detect clouds, is implemented and tested on the GEE platform.

010504 meteorology & atmospheric sciencesComputer scienceReal-time computingScalability0211 other engineering and technologiesCloud detectionSatellite02 engineering and technologyDimension (data warehouse)Earth observation satellite01 natural sciences021101 geological & geomatics engineering0105 earth and related environmental sciences2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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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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First Results of Hyperspectral Scene Generation in Preparation of the Chime Imaging Spectrometer Mission

2021

End-To-End mission performance simulators (E2Es) are software tools developed to support satellite mission preparatory activities. For passive remote sensing missions, E2Es generate synthetic scenes simulating the interaction of the solar radiation between the atmosphere and the surface; therefore allowing the estimation of the mission performance before its launch. In this paper, we present the CHIME Scene Generator Module (SGM) as part of CHIME E2Es, with state-of-the-art parallelization and optimization that give a performance allowing to obtain a whole year of daily worldwide Top-Of-Atmosphere radiance images in a matter of hours. The CHIME SGM generates 100x200km hyperspectral scenes w…

010504 meteorology & atmospheric sciencesComputer sciencebusiness.industryReal-time computing0211 other engineering and technologiesImaging spectrometerHyperspectral imaging02 engineering and technology01 natural sciencesConvolutionInstruction setSoftwareShadowRadianceSatellitebusiness021101 geological & geomatics engineering0105 earth and related environmental sciences2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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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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Supporting group decision makers to locate temporary relief distribution centres after sudden-onset disasters

2020

International audience; In the humanitarian response, multiple decision-makers (DMs) need to collaborate in various problems, such as locating temporary relief distribution centres (RDCs). Several studies have argued that maximising demand coverage, reducing logistics costs and minimising response time are among the critical objectives when locating RDCs after a sudden-onset disaster. However, these objectives are often conflicting and the trade-offs can considerably complicate the situation for finding a consensus.To address the challenge and support the DMs, we suggest investigating the stability of non-dominated alternatives derived from a multi-objective model based on Monte Carlo Simul…

010504 meteorology & atmospheric sciencesComputer sciencemedicine.medical_treatment0211 other engineering and technologiesStability (learning theory)Distribution (economics)02 engineering and technology01 natural sciencesHumanitarian responseNATURAL DISASTERSupport groupINFORMATION-MANAGEMENT[SPI]Engineering Sciences [physics]NETWORK DESIGNGroup decision-making2015 Nepal earthquakemedicineOPTIMIZATIONVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Monte Carlo simulation0105 earth and related environmental sciences021110 strategic defence & security studiesCOORDINATIONCOMPLEXDISTRIBUTION MODELbusiness.industrySTOCHASTIC-MODELHumanitarian responseGeologyGeotechnical Engineering and Engineering GeologyRisk analysis (engineering)Multiobjective facility locationPARETO SETbusinessSafety ResearchHUMANITARIAN LOGISTICSSudden onsetInternational Journal of Disaster Risk Reduction
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Stochastic Galerkin method for cloud simulation

2018

AbstractWe develop a stochastic Galerkin method for a coupled Navier-Stokes-cloud system that models dynamics of warm clouds. Our goal is to explicitly describe the evolution of uncertainties that arise due to unknown input data, such as model parameters and initial or boundary conditions. The developed stochastic Galerkin method combines the space-time approximation obtained by a suitable finite volume method with a spectral-type approximation based on the generalized polynomial chaos expansion in the stochastic space. The resulting numerical scheme yields a second-order accurate approximation in both space and time and exponential convergence in the stochastic space. Our numerical results…

010504 meteorology & atmospheric sciencesComputer scienceuncertainty quantificationQC1-999cloud dynamicsFOS: Physical sciencesCloud simulation65m15010103 numerical & computational mathematics01 natural sciencespattern formationMeteorology. ClimatologyFOS: MathematicsApplied mathematicsMathematics - Numerical Analysis0101 mathematicsStochastic galerkin0105 earth and related environmental sciencesnavier-stokes equationsPhysics65m2565l05Numerical Analysis (math.NA)65m06Computational Physics (physics.comp-ph)stochastic galerkin method35l4535l65finite volume schemesQC851-999Physics - Computational Physicsimex time discretization
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