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Visual analytics of time-varying multivariate ionospheric scintillation data / Aurea Soriano-Vargas in Computers and graphics, vol 68 (November 2017)  

Public [article]  inComputers and graphics > vol 68 (November 2017) . - pp 96 - 107 Titre : Visual analytics of time-varying multivariate ionospheric scintillation data Type de document : Article/Communication Auteurs : Aurea Soriano-Vargas, Auteur ; Bruno C. Vani, Auteur ; Milton H. Shimabukuro, Auteur ; João F.G. Monico, Auteur Année de publication : 2017 Article en page(s) : pp 96 - 107 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle [Termes IGN] analyse multivariée [Termes IGN] données spatiotemporelles [Termes IGN] ionosphère [Termes IGN] scintillation [Termes IGN] visualisation de données [Vedettes matières IGN] Géovisualisation Résumé : (résumé) We present a clustering-based interactive approach to multivariate data analysis, motivated by the specific needs of scintillation data. Ionospheric scintillation is a rapid variation in the amplitude and/or phase of radio signals traveling through the ionosphere. This spatial and time-varying phenomenon is of great interest since it affects the reception quality of satellite signals. Specialized receivers at strategic regions can track multiple variables related to this phenomenon, generating a database of observations of regional ionospheric scintillation. We introduce a visual analytics solution to support analysis of such data, keeping in mind the general applicability of our approach to similar multivariate data analysis situations. Taking into account typical user questions, we combine visualization and data mining algorithms that satisfy these goals: (i) derive a representation of the variables monitored that conveys their behavior in detail, at multiple user-defined aggregation levels; (ii) provide overviews of multiple variables regarding their behavioral similarity over selected time periods; (iii) support users when identifying representative variables for characterizing scintillation behavior. We illustrate the capabilities of our proposed framework by presenting case studies driven directly by questions formulated by collaborating domain experts. Numéro de notice : A2017-452 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cag.2017.08.013 En ligne : https://doi.org/10.1016/j.cag.2017.08.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86363 [article]