Please use this identifier to cite or link to this item:
Title: Visualizing interchange patterns in massive movement data
Authors: Zeng, Wei
Fu, Chi-Wing
Arisona, Stefan Müller
Qu, Huamin
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Computer graphics
Issue Date: 2013
Source: Zeng, W., Fu, C.-W., Arisona, S. M., & Qu, H. (2013). Visualizing interchange patterns in massive movement data. Computer graphics forum, 32(3pt3), 271-280.
Series/Report no.: Computer graphics forum
Abstract: Massive amount of movement data, such as daily trips made by millions of passengers in a city, are widely available nowadays. They are a highly valuable means not only for unveiling human mobility patterns, but also for assisting transportation planning, in particular for metropolises around the world. In this paper, we focus on a novel aspect of visualizing and analyzing massive movement data, i.e., the interchange pattern, aiming at revealing passenger redistribution in a traffic network. We first formulate a new model of circos figure, namely the interchange circos diagram, to present interchange patterns at a junction node in a bundled fashion, and optimize the color assignments to respect the connections within and between junction nodes. Based on this, we develop a family of visual analysis techniques to help users interactively study interchange patterns in a spatiotemporal manner: 1) multi-spatial scales: from network junctions such as train stations to people flow across and between larger spatial areas; and 2) temporal changes of patterns from different times of the day. Our techniques have been applied to real movement data consisting of hundred thousands of trips, and we present also two case studies on how transportation experts worked with our interface.
ISSN: 0167-7055
DOI: 10.1111/cgf.12114
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

Citations 5

Updated on Jan 24, 2023

Web of ScienceTM
Citations 5

Updated on Jan 30, 2023

Page view(s) 50

Updated on Jan 31, 2023

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.