Format du dépôt |
Fichier |
Type de dépôt |
Communication dans un congrès |
Résumé |
en
Presented work illustrates application of the GIS based processing of various geographic data: satellite images and CORINE (Coordination of Information on the Environment) layers at the lessons of geography in the high schools and universities. The research illustrates GIS application for understanding, visualizing and modeling landscapes of the Earth. Practically, the work aims to demonstrate students, how mapping land cover types can be done using GIS and combination of vector and raster geospatial data. Practical example of this work is application of IDRISI GIS and geospatial data towards a study region, located on the coasts of the Baltic Sea: Pärnu region. The GIS project was performed using Landsat TM satellite image and thematic CORINE layers showing land cover and vegetation types. The CORINE project was started in 1985 in the European Union (EU). This is a cartographic database common and standardized for the EU. The project consists of 44 land cover types in classes, presented as a series of maps at a scale of 1:100 000. This database is available for the most areas of Europe (EU) including Estonia. The image was classified according to the European system of CORINE Land Cover Project classification. The CORINE map was used for the interpretation of this classification. Following this methodology the "training areas" were created, i.e. key regions, typical for the landscape types. In totally, 14 land cover types were classified. Classification is based on the detection of land use types. The final result is thematic map of landscape types made using cartographic methods. The work demonstrated how the ecosystems can be studied using combination of CORINE, GIS and remote sensing by the students at the classes of geography at high schools.
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Titre |
en
Opportunities for Classes of Geography in the High School: the Use of ’CORINE’ Project Data, Satellite Images and IDRISI GIS for Geovisualization
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Auteur(s)
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1
OUC -
Ocean University of China
( 308546 )
- Qingdao City, Shandong Province
- Chine
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Actes |
Oui
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Audience |
Internationale
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Invité |
Oui
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Comité de lecture |
Oui
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Vulgarisation |
Oui
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Date de production/écriture |
2014-04-24
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Langue du document |
Anglais
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Licence |
CC0 - Transfert dans le Domaine Public
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Date de publication |
2014
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Page/Identifiant |
284–286
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Titre du congrès |
Perspectives for the Development of Higher Education
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Date début congrès |
2014-04-24
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Date fin congrès |
2014-04-25
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Ville |
Grodno
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Pays |
Biélorussie
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Domaine(s) |
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Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
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Informatique [cs]/Géométrie algorithmique [cs.CG]
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Informatique [cs]/Synthèse d'image et réalité virtuelle [cs.GR]
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Informatique [cs]/Algorithme et structure de données [cs.DS]
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Sciences de l'environnement/Ingénierie de l'environnement
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Sciences de l'Homme et Société/Géographie
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Éditeur scientifique |
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Organisateur du congrès |
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Grodno State Agrarian University GGAU
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Classification ACM 2012 |
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acm2012.ACM2012/Computing methodologies/Machine learning
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acm2012.ACM2012/Computing methodologies/Machine learning/Machine learning approaches
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acm2012.ACM2012/Computing methodologies/Artificial intelligence/Computer vision/Image and video acquisition
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acm2012.ACM2012/Computing methodologies/Artificial intelligence/Computer vision/Computer vision tasks
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acm2012.ACM2012/Computing methodologies/Artificial intelligence/Computer vision/Image and video acquisition/Computational photography
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acm2012.ACM2012/Computing methodologies/Machine learning/Machine learning approaches/Classification and regression trees
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acm2012.ACM2012/Computing methodologies/Computer graphics/Image manipulation
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acm2012.ACM2012/Computing methodologies/Computer graphics/Image manipulation/Image processing
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acm2012.ACM2012/Computing methodologies/Computer graphics/Image manipulation/Image-based rendering
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acm2012.ACM2012/Computing methodologies/Computer graphics/Image manipulation/Texturing
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acm2012.ACM2012/Applied computing/Computers in other domains
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acm2012.ACM2012/Applied computing/Computers in other domains/Cartography
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acm2012.ACM2012/Computing methodologies/Machine learning/Machine learning algorithms
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acm2012.ACM2012/Computing methodologies/Artificial intelligence
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acm2012.ACM2012/Computing methodologies/Artificial intelligence/Computer vision
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Classification ACM 1998 |
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I.: Computing Methodologies/I.3: COMPUTER GRAPHICS
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I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION
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I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.10: Image Representation
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I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis
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I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.1: Digitization and Image Capture
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I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.3: Picture/Image Generation
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I.: Computing Methodologies/I.5: PATTERN RECOGNITION
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I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE
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I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering
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I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models
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I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.2: Geometric
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I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation
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Mots-clés |
en
Land cover and land use changes, Land Cover Mapping, Environmental Assessment, Landscape analysis, Mapping, GIS & Spatial Analyses, Geoinformatics, Geoinformation, Estonia, CORINE LAND COVER, CORINE biotopes, CORINE land-use, Satellite image interpretation, Satellite image analysis
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DOI |
10.6084/m9.figshare.7211933 |