Visualizing the Impact of Geographical Variations on Multivariate Clustering

dc.contributor.authorZhang, Yifanen_US
dc.contributor.authorLuo, Weien_US
dc.contributor.authorMack, Elizabeth A.en_US
dc.contributor.authorMaciejewski, Rossen_US
dc.contributor.editorKwan-Liu Ma and Giuseppe Santucci and Jarke van Wijken_US
dc.date.accessioned2016-06-09T09:32:37Z
dc.date.available2016-06-09T09:32:37Z
dc.date.issued2016en_US
dc.description.abstractTraditional multivariate clustering approaches are common in many geovisualization applications. These algorithms are used to define geodemographic profiles, ecosystems and various other land use patterns that are based on multivariate measures. Cluster labels are then projected onto a choropleth map to enable analysts to explore spatial dependencies and heterogeneity within the multivariate attributes. However, local variations in the data and choices of clustering parameters can greatly impact the resultant visualization. In this work, we develop a visual analytics framework for exploring and comparing the impact of geographical variations for multivariate clustering. Our framework employs a variety of graphical configurations and summary statistics to explore the spatial extents of clustering. It also allows users to discover patterns that can be concealed by traditional global clustering via several interactive visualization techniques including a novel drag & drop clustering difference view. We demonstrate the applicability of our framework over a demographics dataset containing quick facts about counties in the continental United States and demonstrate the need for analytical tools that can enable users to explore and compare clustering results over varying geographical features and scales.en_US
dc.description.number3en_US
dc.description.sectionheadersStructures, Clusters, and Patternsen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume35en_US
dc.identifier.doi10.1111/cgf.12886en_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages101-110en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12886en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.3 [Computer Graphics]en_US
dc.subjectApplicationsen_US
dc.titleVisualizing the Impact of Geographical Variations on Multivariate Clusteringen_US
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