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Density equalizing distortion of large geographic point sets / P. Bak in Cartography and Geographic Information Science, vol 36 n° 3 (July 2009)  

Public [article]  inCartography and Geographic Information Science > vol 36 n° 3 (July 2009) . - pp 237 - 250 Titre : Density equalizing distortion of large geographic point sets Type de document : Article/Communication Auteurs : P. Bak, Auteur ; M. Schaefer, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 237 - 250 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse de données [Termes IGN] cartogramme [Termes IGN] cartographie statistique [Termes IGN] densité des points [Termes IGN] traitement de données localisées [Termes IGN] visualisation de données Résumé : (Auteur) Visualizing large geo-demographical datasets using pixel-based techniques involves mapping the geospatial dimensions of a data point to screen coordinates and appropriately encoding its statistical value by color. The analysis of such data presents a great challenge. General tasks involve clustering, categorization, and searching for patterns of interest for sociological or economic research. Available visual encodings and screen space limitations lead to over-plotting and hiding of patterns and clusters in densely populated areas, while sparsely populated areas waste space and draw the attention away from the areas of interest. In this paper, two new approaches (RadialScale and AngularScale) are introduced to create density-equalized maps, while preserving recognizable features and neighborhoods in the visualization. These approaches build the core of a multi-scaling technique based on local features of the data described as local minima and maxima of point density. Scaling is conducted several times around these features, which leads to more homogeneous distortions. Results are illustrated using several real-world datasets. Our evaluation shows that the proposed techniques outperform traditional techniques as regard the homogeneity of the resulting data distributions and therefore build a more appropriate basis for analytic purposes. Copyright CaGISociet Numéro de notice : A2009-268 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1559/152304009788988288 En ligne : https://doi.org/10.1559/152304009788988288 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29898 [article]

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