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Exploring mass variations in the Earth system / Mike Sips in Cartography and Geographic Information Science, Vol 43 n° 1 (January 2016)  

Public [article]  inCartography and Geographic Information Science > Vol 43 n° 1 (January 2016) . - pp 3 - 15 Titre : Exploring mass variations in the Earth system Type de document : Article/Communication Auteurs : Mike Sips, Auteur ; Andrea Unger, Auteur ; Tobias Rawald, Auteur ; Ingo Sagsen, Auteur Année de publication : 2016 Article en page(s) : pp 3 - 15 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] analyse visuelle [Termes IGN] champ de pesanteur terrestre [Termes IGN] données GRACE [Termes IGN] exploration de données [Termes IGN] géophysique interne [Termes IGN] masse de la Terre Résumé : (Auteur) Geophysical processes cause a redistribution of masses within system Earth called mass transport. This mass transport induces variations in the observed gravity field of the Earth. A common scientific approach to draw conclusions about geophysical processes is to determine the imprint of individual geophysical processes in observed gravity field variations. For this purpose, modelers follow a sequence of specialized steps. From this sequence, we identified in close collaboration with Earth system modelers at the German Research Center for GeoSciences (GFZ) steps that can significantly benefit from Visual Analytics: (a) finding an applicable release of observed gravity field variations that exhibit the geophysical process of interest (b) separating individual geophysical processes in observed gravity field variations and (c) confirming the reduction of observed gravity field variations to the geophysical process of interest. We identified important analytical requirements for our Visual Analytics approach based on a user- and task-centered design. By providing tailored support for the identified requirements, our Visual Analytics approach provides a valuable expansion of the modeler’s toolbox. Numéro de notice : A2016-109 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/15230406.2015.1031702 En ligne : https://doi.org/10.1080/15230406.2015.1031702 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79927 [article]

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Highlighting space-time patterns: effective visual encoding for interactive decision-making / Mike Sips in International journal of geographical information science IJGIS, vol 21 n° 8 (september 2007)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 21 n° 8 (september 2007) . - pp 879 - 893 Titre : Highlighting space-time patterns: effective visual encoding for interactive decision-making Type de document : Article/Communication Auteurs : Mike Sips, Auteur ; J. Schneidewind, Auteur ; Daniel A. Keim, Auteur Année de publication : 2007 Article en page(s) : pp 879 - 893 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] analyse visuelle [Termes IGN] automatisation [Termes IGN] découverte de connaissances [Termes IGN] détection de changement [Termes IGN] données localisées [Termes IGN] données multisources [Termes IGN] entrepôt de données localisées [Termes IGN] visualisation Résumé : (Auteur) The research reported in this paper focuses on integrating analytical and visual methods in order to explore complex patterns in geo-related multivariate data sets and to understand the changes in patterns over time. The goal is to provide techniques that are able to analyse real-world Data Warehouses, a typical architecture to manage such geo-related multidimensional data sets, in order to support the analyst's decision-making process. Challenges arise because real-world applications usually have to deal with millions of records, with dozens of dimensions, and spatio-temporal context. Therefore, a tight integration of automated analysis and interactive visualizations is needed (as proposed in the context of Visual Analytics). Our approach uses the well-studied capabilities provided by Data Warehouses supporting knowledge discovery and decision-making to analyse spatio-temporal behaviour of pattern in high-dimensional spaces. The topic of the paper is to show possible interplays between automated analysis and geo-spatial visualization. Copyright Taylor & Francis Numéro de notice : A2007-322 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810701362147 En ligne : https://doi.org/10.1080/13658810701362147 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28685 [article]

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