Search results for "KRIGING"

showing 10 items of 93 documents

Spatio-temporal pattern of Pentastiridius leporinus migration in an ephemeral cropping system

2010

International audience; * 1 Cixiid planthoppers (Hemiptera: Fulgoromorpha: Cixiidae) are considered to be important economic pests because of their ability to transmit phloem-restricted prokaryotes causing emerging plant diseases worldwide. However, little information is available on the biology and ecology of such species. This is the case for Pentastiridius leporinus (Linnaeus), a cixiid planthopper reported to live on common reed across Countries of Central and Northern Europe. However, in the east of France, the same planthopper species appears to complete its life cycle in the sugar beet-wheat cropping system and has been repeatedly shown to transmit prokaryotic plant pathogens that ar…

0106 biological sciences[SDV]Life Sciences [q-bio]WHEATCIXIIDAEPLANTHOPPERPENTASTIRUDIUS LEPORINUS01 natural sciencesCropPlanthopperCropping systemNymphSugarSYNDROME "BASSES RICHESSES"2. Zero hungerbiologyEcologyfungifood and beveragesForestry15. Life on landbiology.organism_classificationCixiidaeKRIGINGHemiptera010602 entomologyInsect ScienceEMERGING DISEASESugar beetGEOSTATISTICSAgronomy and Crop ScienceGEOGRAPHIC INFORMATION SYSTEM (GIS)SUGAR BEET010606 plant biology & botany
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Evaluating field-scale sampling methods for the estimation of mean plant densities of weeds

2000

The weed flora (comprising seven species) of a field continuously grown with soyabean was simulated for 4 years, using semivariograms established from previous field observations. Various sampling methods were applied and compared for accurately estimating mean plant densities, for differing weed species and years. The tested methods were based on (a) random selection wherein samples were chosen either entirely randomly, randomly with at least 10 or 20 m between samples, or randomly after stratifying the field; (b) systematic selection where samples were placed along diagonals or along zig-zagged lines across the field; (c) predicted Setaria viridis (L.) P. Beaux seedling maps which were us…

0106 biological sciencesbiologyEcologySetaria viridisField experimentSampling (statistics)Sample (statistics)04 agricultural and veterinary sciencesPlant Sciencebiology.organism_classification01 natural sciencesKrigingStatistics040103 agronomy & agriculture0401 agriculture forestry and fisheries[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal BiologyWeedVariogramAgronomy and Crop ScienceEcology Evolution Behavior and SystematicsSelection (genetic algorithm)ComputingMilieux_MISCELLANEOUS010606 plant biology & botanyMathematics
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Communication cost of channel estimation interpolation for group-based vehicular communications in cellular networks

2020

Las comunicaciones inalámbricas para aplicaciones vehiculares en sistemas celulares de quinta generación (5G) deben ser de baja latencia y alta fiabilidad. Entre otros factores, la cantidad de información de control que debe intercambiarse entre cada vehículo y la estación base puede penalizar la latencia de la comunicación. Varios casos de uso vehicular 5G implican comunicaciones dentro de grupos de vehículos, por ejemplo el pelotón de vehículos. Este trabajo se centra en explotar la estructura y características de este servicio vehicular particular basado en grupos para disminuir el intercambio de información de control relacionado con la etapa de estimación del canal necesaria para las c…

020203 distributed computing:CIENCIAS TECNOLÓGICAS [UNESCO]business.industryComputer scienceintelligent transportation systemschannel estimation02 engineering and technologyUNESCO::CIENCIAS TECNOLÓGICASNetwork topologyCellular communicationBase stationVehicular communicationsKriging0202 electrical engineering electronic engineering information engineeringCellular networkWireless020201 artificial intelligence & image processingspatial interpolationLatency (engineering)businessIntelligent transportation system5GCommunication channelComputer network
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An Interactive Framework for Offline Data-Driven Multiobjective Optimization

2020

We propose a framework for solving offline data-driven multiobjective optimization problems in an interactive manner. No new data becomes available when solving offline problems. We fit surrogate models to the data to enable optimization, which introduces uncertainty. The framework incorporates preference information from a decision maker in two aspects to direct the solution process. Firstly, the decision maker can guide the optimization by providing preferences for objectives. Secondly, the framework features a novel technique for the decision maker to also express preferences related to maximum acceptable uncertainty in the solutions as preferred ranges of uncertainty. In this way, the d…

050101 languages & linguisticsDecision support systemMathematical optimizationOptimization problemdecision supportComputer scienceEvolutionary algorithmGaussian processespäätöksentukijärjestelmät02 engineering and technologyMulti-objective optimizationdecision makingData-driven0202 electrical engineering electronic engineering information engineeringmetamodelling0501 psychology and cognitive sciencessurrogateInteractive visualization05 social sciencesgaussiset prosessitmonitavoiteoptimointiMetamodelingKriging020201 artificial intelligence & image processingdecomposition-based MOEAkriging-menetelmäCognitive load
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Probabilistic cross-validation estimators for Gaussian process regression

2018

Gaussian Processes (GPs) are state-of-the-art tools for regression. Inference of GP hyperparameters is typically done by maximizing the marginal log-likelihood (ML). If the data truly follows the GP model, using the ML approach is optimal and computationally efficient. Unfortunately very often this is not case and suboptimal results are obtained in terms of prediction error. Alternative procedures such as cross-validation (CV) schemes are often employed instead, but they usually incur in high computational costs. We propose a probabilistic version of CV (PCV) based on two different model pieces in order to reduce the dependence on a specific model choice. PCV presents the benefits from both…

050502 lawHyperparameterMinimum mean square error05 social sciencesProbabilistic logicEstimator01 natural sciencesCross-validation010104 statistics & probabilitysymbols.namesakeKrigingStatisticssymbolsMaximum a posteriori estimation0101 mathematicsGaussian processAlgorithm0505 lawMathematics2017 25th European Signal Processing Conference (EUSIPCO)
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Towards Quantifying Non-Photosynthetic Vegetation for Agriculture Using Spaceborne Imaging Spectroscopy

2021

Non-photosynthetic vegetation (NPV) has been identified as priority variable in the context of new spaceborne imaging spectroscopy missions. In this study we provide a first attempt to quantify NPV biomass from these unprecedented data streams to be provided by multiple recently launched or planned instruments. A hybrid workflow is proposed including Gaussian process regression (GPR) trained over radiative transfer model (RTM) simulations and applying active learning strategies. A soybean field data set including two dates with NPV measurements on yellow and senescent (brown) plant organs was used for model validation, resulting in relative errors of 13.4%. This prototype retrieval model wa…

2. Zero hunger010504 meteorology & atmospheric sciencesData stream mining0211 other engineering and technologiesEnMAPHyperspectral imagingContext (language use)PRISMA02 engineering and technologyVegetationVegetation functional trait01 natural sciencesLigninImaging spectroscopyAtmospheric radiative transfer codesWorkflowHybrid approacheCHIMEKrigingEnvironmental scienceCelluloseGaussian process regression021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Multitemporal and multiresolution leaf area index retrieval for operational local rice crop monitoring

2016

Abstract This paper presents an operational chain for high-resolution leaf area index (LAI) retrieval from multiresolution satellite data specifically developed for Mediterranean rice areas. The proposed methodology is based on the inversion of the PROSAIL radiative transfer model through the state-of-the-art nonlinear Gaussian process regression (GPR) method. Landsat and SPOT5 data were used for multitemporal LAI retrievals at high-resolution. LAI estimates were validated using time series of in situ LAI measurements collected during the rice season in Spain and Italy. Ground LAI data were collected with smartphones using PocketLAI, a specific phone application for LAI estimation. Temporal…

2. Zero hunger010504 meteorology & atmospheric sciencesMean squared error0211 other engineering and technologiesSoil ScienceGeologyInversion (meteorology)02 engineering and technologyCrop monitoring; Rice; Leaf area index (LAI) retrieval; PROSAIL; Smartphone; Gaussian process regression (GPR); Landsat; SPOT5 Take501 natural sciencesAtmospheric radiative transfer codesKrigingSatellite dataGround-penetrating radarEnvironmental scienceComputers in Earth SciencesLeaf area indexRice crop021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Crop Phenology Retrieval Through Gaussian Process Regression

2021

Monitoring crop phenology significantly assists agricultural managing practices and plays an important role in crop yield predictions. Multi-temporal satellite-based observations allow analyzing vegetation seasonal dynamics over large areas by using vegetation indices or deriving biophysical variables. This study presents a framework for automatic corn phenology characterization based on high spatial and temporal resolution time series. By using the Difference Vegetation Index (DVI) estimated from Sentinel-2 data over Iowa (US), independent phenological models were optimized using Gaussian Processes regression. Their respective performances were assessed based on simulated phenological indi…

2. Zero hunger010504 meteorology & atmospheric sciencesMean squared errorPhenology0211 other engineering and technologies02 engineering and technologyVegetation15. Life on land01 natural sciencesRegressionsymbols.namesakeKrigingTemporal resolutionStatisticssymbolsTime seriesGaussian process021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematics2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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Radio environment map estimation based on communication cost modeling for heterogeneous networks

2017

Los mapas del entorno radioeléctrico pueden ser una poderosa herramienta para lograr una asignación de recursos eficiente y consciente del contexto en las redes heterogéneas 5G. En este trabajo, consideramos una red heterogénea formada por una red celular tradicional y una red de sensores inalámbricos. El papel de la red de sensores inalámbricos es estimar el mapa del entorno radioeléctrico de la célula utilizando una técnica de interpolación geoestadística denominada Kriging. En un trabajo anterior se propuso un algoritmo de agrupación distribuida de sensores para reducir la complejidad de la estimación. En nuestra contribución, el proceso de formación de clústeres se modifica para incluir…

:CIENCIAS TECNOLÓGICAS [UNESCO]Computer scienceReal-time computing020302 automobile design & engineering020206 networking & telecommunications02 engineering and technologyUNESCO::CIENCIAS TECNOLÓGICASradio environment maps0203 mechanical engineeringMetric (mathematics)0202 electrical engineering electronic engineering information engineeringCellular networkResource allocationcommunication costkrigingCluster analysiswireless sensor networksWireless sensor networkHeterogeneous network5GInterpolation
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Distributed Clustering Algorithm for Spatial Field Reconstruction in Wireless Sensor Networks

2015

En este trabajo, consideramos el problema de la estimación espacial distribuida para la reconstrucción del campo radio en redes de sensores inalámbricos. Para estimar el campo, se utiliza una técnica geoestadística llamada kriging. La estimación espacial centralizada con un gran número de sensores conllevan un elevado coste computacional y gasto de energía. Presentamos un novedoso algoritmo de clustering distribuido para estimar mapas de interferencia espacial, que son esenciales para las operaciones y la gestión de las futuras redes inalámbricas. En este algoritmo, los clústeres de sensores se forman de forma adaptativa mediante la minimización de la varianza de kriging. El cálculo del sem…

:CIENCIAS TECNOLÓGICAS [UNESCO]Computer scienceWireless networkComputationUNESCO::CIENCIAS TECNOLÓGICAScomputer.software_genreField (geography)Krigingspatial field reconstructionkrigingData miningwireless sensor networksCluster analysisVariogramWireless sensor networkcomputerEnergy (signal processing)clustering2015 IEEE 81st Vehicular Technology Conference (VTC Spring)
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