UrbanFACET: Visually Profiling Cities from Mobile Device Recorded Movement Data of Millions of City Residents

TL;DR

UrbanFACET is a visual analytics system that uses mobile device movement data and information-theory metrics to profile and compare the dynamic urban functions of multiple cities.

Contribution

It introduces a novel set of information-theory based metrics and a visualization system for analyzing city mobility patterns and urban functions at large scales.

Findings

Effective visualization of city profiles and resident behaviors.

Identification of hidden urban functions through new metrics.

Successful case studies on major cities demonstrating system utility.

Abstract

Cities are living systems where urban infrastructures and their functions are defined and evolved due to population behaviors. Profiling the cities and functional regions has been an important topic in urban design and planning. This paper studies a unique big data set which includes daily movement data of tens of millions of city residents, and develop a visual analytics system, namely UrbanFACET, to discover and visualize the dynamical profiles of multiple cities and their residents. This big user movement data set, acquired from mobile users' agnostic check-ins at thousands of phone APPs, is well utilized in an integrative study and visualization together with urban structure (e.g., road network) and POI (Point of Interest) distributions. In particular, we novelly develop a set of information-theory based metrics to characterize the mobility patterns of city areas and groups of residents. These multifaceted metrics including Fluidity, vibrAncy, Commutation, divErsity, and densiTy (FACET) which categorize and manifest hidden urban functions and behaviors. UrbanFACET system further allows users to visually analyze and compare the metrics over different areas and cities in metropolitan scales. The system is evaluated through both case studies on several big and heavily populated cities, and user studies involving real-world users.