Search results for "1902 Atmospheric Science"

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Traitement de données RGB et Lidar à extrêmement haute résolution: retombées de la compétition de fusion de données 2015 de l'IEEE GRSS - Partie A / …

2016

International audience; In this paper, we discuss the scientific outcomes of the 2015 data fusion contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource studies. The 2015 edition of the contest proposed a multiresolution and multisensorial challenge involving extremely high-resolution RGB images and a three-dimensional (3-D) LiDAR point cloud. The competition was framed in two parallel tracks, considering 2-D and 3-D products, respectively. In this paper, we discuss the sci…

Atmospheric Science010504 meteorology & atmospheric sciencesComputer scienceMULTIMODAL-DATA FUSIONGeophysics. Cosmic physics0211 other engineering and technologies02 engineering and technologyCONTESTcomputer.software_genre01 natural sciencesOutcome (game theory)LIDARTraitement des imagesIMAGE ANALYSIS AND DATA FUSION (IADF)DEEP NEURAL NETWORKSDeep neural networksTraitement du signal et de l'imageMULTIRESOLUTION910 Geography & travelMultiresolutionGround truthLANDCOVER CLASSIFICATIONIMAGE AERIENNE1903 Computers in Earth SciencesBenchmarkingVision par ordinateur et reconnaissance de formesOcean engineering10122 Institute of GeographyLidarDeep neural networksData miningExtremely high spatial resolutionMultimodal-data fusionLiDARComputers in Earth Sciences; Atmospheric ScienceImage analysis and data fusion (IADF)EXTREMELY HIGH SPATIAL RESOLUTIONCLASSIFICATIONTRAITEMENT IMAGE1902 Atmospheric ScienceAPPRENTISSAGE STATISTIQUEComputers in Earth SciencesTELEDETECTIONSynthèse d'image et réalité virtuelleTC1501-1800021101 geological & geomatics engineering0105 earth and related environmental sciencesLandcover classificationmultiresolution-[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]QC801-809Intelligence artificielleMULTISOURCESensor fusionRGB color modelcomputerMultisource
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Trends in phenological parameters and relationship between land surface phenology and climate data in the Hyrcanian forests of Iran

2017

Vegetation activity may be changed in response to climate variability by affecting seasonality and phenological events. Monitoring of land surface phenological changes play a key role in understanding feedback of ecosystem dynamics. This study focuses on the analysis of trends in land surface phenology derived parameters using normalized difference vegetation index time series based on Global Inventory Monitoring and Mapping Studies data in the Hyrcanian forests of Iran covering the period 1981–2012. First, we applied interpolation for data reconstruction in order to remove outliers and cloud contamination in time series. Phenological parameters were retrieved by using the midpoint approach…

Atmospheric Science010504 meteorology & atmospheric sciencesPhenology0211 other engineering and technologies1903 Computers in Earth Sciences02 engineering and technologyVegetationSeasonalitymedicine.disease01 natural sciencesNormalized Difference Vegetation IndexTrend analysis10122 Institute of GeographyClimatologyLinear regression1902 Atmospheric SciencemedicineEnvironmental sciencePrecipitationTime series910 Geography & travelComputers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciences
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