Abstract

Abstract: Modeling human mobility is a critical task in fields such as urban planning, ecology, and epidemiology. Given the current use of mobile phones, there is an abundance of data that can be used to create models of high reliability. Existing techniques can reveal the macro-patterns of crowd movement, or analyze the trajectory of an individual object; however, they focus on geographical characteristics. In this paper, we propose a novel data representation, the mobility transition graph, to characterize spatio-temporal mobility transition of crowd from city-wide human mobility data. We describe the design, creation, and manipulation of the mobility transition graph and demonstrate the efficiency of our approach by a case study. Graphical abstract: [Figure not available: see fulltext.]

Original languageEnglish (US)
Pages (from-to)1-12
Number of pages12
JournalJournal of Visualization
DOIs
StateAccepted/In press - Jun 9 2016

Fingerprint

Epidemiology
Urban planning
Ecology
Mobile phones
Macros
Visualization
Trajectories
urban planning
epidemiology
ecology
manipulators
trajectories

Keywords

  • Mobility modeling
  • Multi-modal information visualization
  • Spatial–temporal visual analysis

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Electrical and Electronic Engineering

Cite this

Spatial–temporal visualization of city-wide crowd movement. / Wu, Feiran; Zhu, Minfeng; Wang, Qi; Zhao, Xin; Chen, Wei; Maciejewski, Ross.

In: Journal of Visualization, 09.06.2016, p. 1-12.

Research output: Contribution to journalArticle

Wu, Feiran ; Zhu, Minfeng ; Wang, Qi ; Zhao, Xin ; Chen, Wei ; Maciejewski, Ross. / Spatial–temporal visualization of city-wide crowd movement. In: Journal of Visualization. 2016 ; pp. 1-12.
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