Search results for "méthode"

showing 10 items of 189 documents

Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory

2018

International audience; Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability ('p-theory'), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types.…

0106 biological sciencesCanopyEarth observationPhoton010504 meteorology & atmospheric sciencesF40 - Écologie végétalehttp://aims.fao.org/aos/agrovoc/c_1920Soil Science01 natural sciencesMeasure (mathematics)http://aims.fao.org/aos/agrovoc/c_7701Multi-angle remote sensingProbability theoryhttp://aims.fao.org/aos/agrovoc/c_718Foliage clumping indexRange (statistics)http://aims.fao.org/aos/agrovoc/c_3081[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyComputers in Earth SciencesLeaf area indexhttp://aims.fao.org/aos/agrovoc/c_4039http://aims.fao.org/aos/agrovoc/c_4116Photon recollision probabilityhttp://aims.fao.org/aos/agrovoc/c_10672http://aims.fao.org/aos/agrovoc/c_32450105 earth and related environmental sciencesMathematicsRemote sensinghttp://aims.fao.org/aos/agrovoc/c_8114GeologyVegetationhttp://aims.fao.org/aos/agrovoc/c_5234http://aims.fao.org/aos/agrovoc/c_7558Leaf area indexhttp://aims.fao.org/aos/agrovoc/c_7273http://aims.fao.org/aos/agrovoc/c_1236http://aims.fao.org/aos/agrovoc/c_1556U30 - Méthodes de recherchehttp://aims.fao.org/aos/agrovoc/c_4026010606 plant biology & botanyhttp://aims.fao.org/aos/agrovoc/c_6124
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Accounting for preferential sampling in species distribution models

2019

D. C., A. L. Q. and F. M. would like to thank the Ministerio de Educación y Ciencia (Spain) for financial support (jointly financed by the European Regional Development Fund) via Research Grants MTM2013‐42323‐P and MTM2016‐77501‐P, and ACOMP/2015/202 from Generalitat Valenciana (Spain). Species distribution models (SDMs) are now being widely used in ecology for management and conservation purposes across terrestrial, freshwater, and marine realms. The increasing interest in SDMs has drawn the attention of ecologists to spatial models and, in particular, to geostatistical models, which are used to associate observations of species occurrence or abundance with environmental covariates in a fi…

0106 biological sciencesComputer scienceQH301 BiologySpecies distributionPoint processesStochastic partial differential equation01 natural scienceshttp://aims.fao.org/aos/agrovoc/c_6774EspèceAbundance (ecology)StatisticsPesqueríasQAOriginal Researchhttp://aims.fao.org/aos/agrovoc/c_241990303 health sciencesEcologyU10 - Informatique mathématiques et statistiquesSampling (statistics)Integrated nested Laplace approximationstochastic partial differential equationVariable (computer science)symbolsÉchantillonnageSpecies Distribution Models (SDMs)Modèle mathématiqueBayesian probabilityNDASDistribution des populations010603 evolutionary biologyQH30103 medical and health sciencessymbols.namesakeCovariateQA MathematicsSDG 14 - Life Below WaterCentro Oceanográfico de Murciaspecies distribution modelsRelative species abundanceEcology Evolution Behavior and Systematicspoint processes030304 developmental biologyNature and Landscape Conservationhttp://aims.fao.org/aos/agrovoc/c_6113http://aims.fao.org/aos/agrovoc/c_7280Markov chain Monte Carlointegrated nested Laplace approximationU30 - Méthodes de rechercheBayesian modelling
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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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la prospection systématique d’un fond de rivière : l’exemple du Doubs

2020

La présentation des méthodes mises en œuvre et des résultats obtenus à l’occasion d’une opération de prospection subaquatique systématique menée sur la rivière Doubs, en amont de Verdun-sur-le-Doubs (Saône-et-Loire), illustre en grandeur réelle l’intérêt de la démarche adoptée, fondée sur des principes simples, dans la perspective d’un inventaire systématique du patrimoine fluvial immergé. La diversité des vestiges découverts et leur répartition sur la longue durée en soulignent la pertinence mais également, s’il en était encore besoin, la réalité du formidable potentiel archéologique que recèlent les cours d’eau. The presentation of the methods used and results obtained during a systematic…

0106 biological scienceslacHDarchéologie fluviale[SHS.ARCHEO]Humanities and Social Sciences/Archaeology and Prehistorycrossing pointlange ZeitFurt01 natural sciencesrömische Brückemoulin sur bateauxSchiffsmühleArchéologielong timeSOC003000ComputingMilieux_MISCELLANEOUSméthodes de prospection subaquatiqueunderwater prospection methodsFlussarchäologie[SHS.ARCHEO] Humanities and Social Sciences/Archaeology and Prehistorypont romainMethoden der UnterwasserprospektionmontagneRoman bridge010604 marine biology & hydrobiologyriver archaeologyarchéologie subaquatiquelac savoyardtemps longfloating millenvironnementArchaeology[ SHS.ARCHEO ] Humanities and Social Sciences/Archaeology and Prehistoryguérivière
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Les étudiants de la génération Y en formation

2013

National audience; La génération Y suscite débats et questionnements au niveau pédagogique. C'est actuellement celle qui constitue la majorité des étudiants en formation paramédicale. Peu désireuse d'un enseignement dispensant uniquement des savoirs, cette génération demande que le formateur s'adapte aux étudiants pour susciter leur intérêt et donc leur engagement dans la formation. Cela passe par certaines caractéristiques générationnelles, à commencer par la relation entre le formateur et les étudiants mais aussi par le travail en groupe, l'apprentissage par essais-erreurs, ou encore l'utilisation de nouvelles technologies. Ce texte propose un éclairage sur ces différents points pour ques…

030506 rehabilitationÉcole paramédicaleHealth Policy[SHS.EDU]Humanities and Social Sciences/Education05 social sciences[SHS.EDU] Humanities and Social Sciences/Education050301 educationÉtudiant[ SHS.EDU ] Humanities and Social Sciences/EducationEffet de générationProcessus d'apprentissageEnseignement supérieur03 medical and health sciencesMéthode pédagogiqueRelation éducativeRelation pédagogiqueFrance0305 other medical science0503 educationGeneral Nursing
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Le prix des paysages périurbains

2007

L'évaluation économique du prix des paysages périurbains utilise des analyses géographiques (occupation des sols, composition paysagère, distance à des biens paysagers, paysages vus : champ de vision, objets, formes). L'article fait le point sur la littérature en matière de méthode et de résultats et présente l'estimation du prix d'attributs paysagers dans la ceinture périurbaine de Dijon.

AMENITEamenityhedonic price[SHS.GEO] Humanities and Social Sciences/Geographymodèle[ SHS.GEO ] Humanities and Social Sciences/GeographypériurbainEconomies et financesaménité0502 economics and businesszone périurbainePRIX HEDONISTE050207 economicspaysageprix hédonisteliving environmentestimation05 social sciencesattribut paysagerperiurban[SHS.GEO]Humanities and Social Sciences/Geography15. Life on landPRIX HEDONISTE;CADRE DE VIE;AMENITE;LANDSCAPE;PERIURBAN;HEDONIC PRICE;LIVING ENVIRONMENT;AMENITYlandscape[SHS.ECO]Humanities and Social Sciences/Economics and FinanceEconomies and financesméthode050202 agricultural economics & policycadre de viePRIX HEDONISTE CADRE DE VIE AMENITE LANDSCAPE PERIURBAN HEDONIC PRICE LIVING ENVIRONMENT AMENITY paysage zone périurbaineattribut paysagerestimation modèleméthode
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Accélération de la convergence et algorithme proximal

1995

Nous faisons une première étude de la question de savoir s'il est possible d'accélérer des suites issues de l'algorithme proximal ou de la méthode de l'inverse partiel par des méthodes d'extrapolation.

Accélération de la convergenceInverse partielMéthodes d'extrapolation[ MATH.MATH-NA ] Mathematics [math]/Numerical Analysis [math.NA][MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA][MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]Algorithme proximalApplication pseudo-contractante
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Risque phytosanitaire (ARP) portant sur Fusarium oxysporum f. sp. cubense (agent pathogène responsable de la maladie de Panama) pour les départements…

2018

Risque phytosanitaire (ARP) portant sur [i]Fusarium oxysporum[/i] f. sp.[u] cubense[/u] (agent pathogène responsable de la maladie de Panama) pour les départements d'Outre-mer

Analyse de risque phytosanitaire[SDV.SA]Life Sciences [q-bio]/Agricultural sciences[SDV.SA] Life Sciences [q-bio]/Agricultural sciencesoutre mer françaisétat de l'artrisque économiqueregulationweed control methodsrace tropicale 4champignon phytopathogèneexpertise scientifiquephytopathogenic fungusbananedétection[SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacyFoc TR4méthode de luttemaladie de PanamaFusarium oxysporum f. sp. cubenseréglementationpathologie végétale[SDV.BV.PEP] Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacyéconomie des filières
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Démarche statistique pour la sélection des indicateurs par Random Forests pour la surveillance de la qualité des sols

2013

The volume of data, and the large number of biological variables to be tested (one hundred), require analytical techniques, such asRandom Forests, which can overcome the problem of multi-colinearity for the selection of indicators, sensitive to various factors.Random Forests methodology is appropriate for the selection of the most discriminant variables. So, we searched for the best wayto select them, by bringing together all biological variables, representing the Microflora and Fauna. This approach focuses on impactindicators from the Bio2 program, indicators of flora and indicators of accumulation (snails) were not included.This work has been implemented on the three factors of discrimina…

Analyse discriminanteRandom Forestscontaminantes orgánicosindicateurs pédologiquesland use.organic pollutantspolluants organiques[ SHS.ENVIR ] Humanities and Social Sciences/Environmental studies[ SHS.GEO ] Humanities and Social Sciences/Geography[SHS]Humanities and Social Sciencesbioindicateurs[ SHS ] Humanities and Social Sciencesoccupation des sols.sélectionméthodes statiquesbioindicadoresRandom Forets[ SHS.STAT ] Humanities and Social Sciences/Methods and statisticsComputingMilieux_MISCELLANEOUS[SHS.STAT]Humanities and Social Sciences/Methods and statisticspédologieuso del sueloDiscriminant Analysis[SHS.GEO]Humanities and Social Sciences/Geographysols[SDE.ES]Environmental Sciences/Environmental and Societymetal contaminationETMselección[SHS.ENVIR]Humanities and Social Sciences/Environmental studiesbioindicatorsanálisis discriminante[SDE.ES] Environmental Sciences/Environmental and Society[ SDE.ES ] Environmental Sciences/Environmental and Societyqualité des sols
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Bias correction of dynamically downscaled precipitation to compute soil water deficit for explaining year-to-year variation of tree growth over north…

2017

This paper documents the accuracy of a post-correction method applied to precipitation regionalized by the Weather Research and Forecasting (WRF) Regional Climate Model (RCM) for improving simulated rainfall and feeding impact studies. The WRF simulation covers Burgundy (northeastern France) at a 8-km resolution and over a 20-year long period (1989–2008). Previous results show a strong deficiency of the WRF model for simulating precipitation, especially when convective processes are involved. In order to reduce such biases, a Quantile Mapping (QM) method is applied to WRF-simulated precipitation using the mesoscale atmospheric analyses system SAFRAN («Système d'Analyse Fournissant des Rense…

Atmospheric Science010504 meteorology & atmospheric sciences0208 environmental biotechnologyméthode de correction02 engineering and technologybourgogneCOMMON BEECH01 natural sciencesCiencias de la Tierra y relacionadas con el Medio AmbienteWater balanceREGIONAL CLIMATE MODELLINGGlobal and Planetary Changedéficit hydriqueForestry[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/ClimatologyClimatologyWATER BALANCECommon beechSOIL WATER DEFICITFrance[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/ClimatologyCIENCIAS NATURALES Y EXACTASforêt tempéréeWRFMesoscale meteorology[ SDV.SA.SDS ] Life Sciences [q-bio]/Agricultural sciences/Soil study[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studySpatial distributionDOUGLAS-FIRmedicineREGIONAL CLIMATE-CHANGE; ERA-INTERIM REANALYSIS; POTENTIAL IMPACT; TEMPERATE FOREST; FAGUS-SYLVATICA; SEVERE DROUGHT; MODEL; RESPONSES; SYSTEM; PROJECTIONSPrecipitationmodèle climatique[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrologyclimatologie régionaleWater balanceSoil water deficit0105 earth and related environmental sciencesQuantile mappingclimatprécipitationDouglas-firQUANTILE MAPPINGnord est de la France15. Life on landSeasonalitymedicine.disease020801 environmental engineering13. Climate actionWeather Research and Forecasting ModelSoil waterEnvironmental scienceClimate modelMeteorología y Ciencias Atmosféricas[ SDU.STU.HY ] Sciences of the Universe [physics]/Earth Sciences/HydrologyAgronomy and Crop ScienceRegional climate modelling
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