城市人日常出行数据中所含规律的可视分析 " /> 城市人日常出行数据中所含规律的可视分析 " /> A visual analytics design for studying rhythm patterns from human daily movement data " />
城市人日常出行数据中所含规律的可视分析
A visual analytics design for studying rhythm patterns from human daily movement data
WeiZenga,Chi-Wing Fub,Stefan Müller Arisonac,a, Simon Schubigerc,a, Remo Burkharda, Kwan-Liu Mad
背景:城市人的日常出行在时空上呈现出高度的规律性。了解他们的日常出行规律对城市规划者、交通分析师和商业策划者都有很大意义。
贡献:本文提出一种面向城市人出行跟踪数据的交互式可视分析设计方案,通过对这些数据进行空间和时间上的交互式分析和挖掘,可揭示和呈现众人日常出行的模式。
案例验证:以新加坡的大量城市公共交通数据和MIT的Reality Minning数据集为典型案例进行分析,证明了我们的系统具有有效性和可用性。
Human’s daily movements exhibit high regularity in a space–time context that typically forms circadian rhythms. Understanding the rhythms for human daily movements is of high interest to a variety of parties from urban planners, transportation analysts, to business strategists. In this paper, we present an interactive visual analytics design for understanding and utilizing data collected from tracking human’s movements. The resulting system identifies and visually presents frequent human movement rhythms to support interactive exploration and analysis of the data over space and time. Case studies using real-world human movement data, including massive urban public transportation data in Singapore and the MIT reality mining dataset, and interviews with transportation researches were conducted to demonstrate the effectiveness and usefulness of our system.
WeiZeng, Chi-Wing Fu, Stefan Müller Arisona, Simon Schubiger, Remo Burkhard, Kwan-Liu Ma.
A visual analytics design for studying rhythm patterns from human daily movement data . Vis Inf, 2017, 1(2): 132-142.
http://www.zjujournals.com/vi/CN/10.1016/j.visinf.2017.07.001 或 http://www.zjujournals.com/vi/CN/Y2017/V1/I2/132
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