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dc.contributor.authorKamw, Farahen_US
dc.contributor.authorAL-Dohuki, Shamalen_US
dc.contributor.authorZhao, Yeen_US
dc.contributor.authorYang, Jingen_US
dc.contributor.authorYe, Xinyueen_US
dc.contributor.authorChen, Weien_US
dc.contributor.editorLandesberger, Tatiana von and Turkay, Cagatayen_US
dc.date.accessioned2019-06-02T18:19:22Z
dc.date.available2019-06-02T18:19:22Z
dc.date.issued2019
dc.identifier.isbn978-3-03868-087-1
dc.identifier.urihttps://doi.org/10.2312/eurova.20191123
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurova20191123
dc.description.abstractAccessibility of urban POIs (Points of Interest) is a key topic in a variety of urban sciences and applications as it reflects inherent city design, transportation, and population flow features. Isochrone maps and other techniques have been used to identify and display reachable regions from given POIs. In addition, domain experts further want to study the distribution effects of accessibility in the urban space such as finding spatial regions that have different accessibility patterns. Such patterns can be manifested by clustering POIs based on their accessibility of different time periods under different traffic conditions. In this paper, we present a visualization system that helps users to find and visualize Latent Accessibility Clusters (LACs) of POIs. The LACs discover temporally changing urban sub-regions (including nearby POIs) with disparate accessibilities at different times. LACs are computed by a POIGraph which connects POIs into a graph structure by extending the dual road network of the corresponding city. The LAC computation is facilitated by graph traversal over the POIGraph. By visualizing the LAC regions on the map, users can visually study the hidden patterns of spatial accessibility. It can contribute to urban transportation, planning, business, and related social sciences.en_US
dc.publisherThe Eurographics Associationen_US
dc.titleVisually Analyzing Latent Accessibility Clusters of Urban POIsen_US
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.description.sectionheadersAnalyzing Movement and Events
dc.identifier.doi10.2312/eurova.20191123
dc.identifier.pages43-47


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