dc.contributor.author | Kamw, Farah | en_US |
dc.contributor.author | AL-Dohuki, Shamal | en_US |
dc.contributor.author | Zhao, Ye | en_US |
dc.contributor.author | Yang, Jing | en_US |
dc.contributor.author | Ye, Xinyue | en_US |
dc.contributor.author | Chen, Wei | en_US |
dc.contributor.editor | Landesberger, Tatiana von and Turkay, Cagatay | en_US |
dc.date.accessioned | 2019-06-02T18:19:22Z | |
dc.date.available | 2019-06-02T18:19:22Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 978-3-03868-087-1 | |
dc.identifier.uri | https://doi.org/10.2312/eurova.20191123 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/eurova20191123 | |
dc.description.abstract | Accessibility 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.publisher | The Eurographics Association | en_US |
dc.title | Visually Analyzing Latent Accessibility Clusters of Urban POIs | en_US |
dc.description.seriesinformation | EuroVis Workshop on Visual Analytics (EuroVA) | |
dc.description.sectionheaders | Analyzing Movement and Events | |
dc.identifier.doi | 10.2312/eurova.20191123 | |
dc.identifier.pages | 43-47 | |