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BinSq : visualizing geographic dot density patterns with gridded maps / Alvin Chua in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)  

Public [article]  inCartography and Geographic Information Science > Vol 44 n° 5 (September 2017) . - pp 390 - 409 Titre : BinSq : visualizing geographic dot density patterns with gridded maps Type de document : Article/Communication Auteurs : Alvin Chua, Auteur ; Andrew Vande Moere, Auteur Année de publication : 2017 Article en page(s) : pp 390 - 409 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] carte de répartition par points [Termes descripteurs IGN] déplacement d'objet géographique [Termes descripteurs IGN] données localisées [Termes descripteurs IGN] généralisation cartographique [Termes descripteurs IGN] grille [Termes descripteurs IGN] visualisation de données [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Dot maps have become a popular way to visualize discrete geographic data. Yet, beyond showing how the data are spatially distributed, dot maps are often visually cluttered in terms of consistency, overlap, and representativeness. Existing clutter reduction techniques like jittering, refinement, distortion, and aggregation also address this issue, but do so by arbitrarily displacing dots from their exact location, removing dots from the map, changing the spatial reference of the map, or reducing its level of detail, respectively. We present BinSq, a novel visualization technique to compare variations in dot density patterns without visual clutter. Based on a careful synthesis of existing clutter reduction techniques, BinSq reduces the wide variety of dot density variations on the map to a representative subset of density intervals that are more distinguishable. The subset is derived from a nested binning operation that introduces order and regularity to the map. Thereafter, a dot prioritization operation improves the representativeness of the map by equalizing visible data values to correspond with the actual data. In this paper, we describe the algorithmic implementation of BinSq, explore its parametric design space, and discuss its capabilities in comparison to six existing clutter reduction techniques for dot maps. Numéro de notice : A2017-448 Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2016.1174623 En ligne : http://dx.doi.org/10.1080/15230406.2016.1174623 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86357 [article]

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