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dc.contributor.authorIurgel, Ido-
dc.contributor.authorSantos, Maribel Yasmina-
dc.description.abstractMaps are used in many application areas to support the visualization and analysis of geo-referenced data. The geometry used in those maps is usually associated with the administrative subdivisions of the regions, disregarding the purpose of the analysis. Another common drawback is that traditional classification methods for data analysis, used for example in Geographic Information Systems, divide the data in a pre-defined number of classes. This can lead to a situation where a class integrates values that are very different from each other and that do not allow the identification of the main differences that can exist between regions. This paper presents a different approach for geo-referenced data analysis that is based on clustering analysis. Through a clustering process it is possible to analyse a specific data set with a map, employing a Space Model, which suits the purposes of such an analysis. Space Models are new geometries of the space that are created to emphasize particularities of the analysed data.por
dc.subjectData miningpor
dc.subjectEnvironmental indicatorspor
dc.subjectSpace modelspor
dc.titleAdvanced clustering analysis for environmental indicatorspor
degois.publication.titleGeoSpatial Visual Analytics : Geographical Information Processing and Visual Analytics for Environmental Securitypor
dc.subject.wosScience & Technologypor
sdum.journalNato Science for Peace and Security Series C-Environmental Securitypor
sdum.conferencePublicationGEOSPATIAL VISUAL ANALYTICSpor
sdum.bookTitleGeoSpatial Visual Analytics : Geographical Information Processing and Visual Analytics for Environmental Securitypor
Appears in Collections:DSI - Engenharia da Programação e dos Sistemas Informáticos

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