Understanding Metropolitan Crowd Mobility via Mobile Cellular Accessing Data
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Published:2019-08-26
Issue:2
Volume:5
Page:1-18
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ISSN:2374-0353
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Container-title:ACM Transactions on Spatial Algorithms and Systems
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language:en
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Short-container-title:ACM Trans. Spatial Algorithms Syst.
Author:
Cao Hancheng1,
Sankaranarayanan Jagan2,
Feng Jie1,
Li Yong1,
Samet Hanan2
Affiliation:
1. Beijing National Research Center for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing, China
2. University of Maryland, College Park, MD
Abstract
Understanding crowd mobility in a metropolitan area is extremely valuable for city planners and decision makers. However, crowd mobility is a relatively new area of research and has significant technical challenges: lack of large-scale fine-grained data, difficulties in large-scale trajectory processing, and issues with spatial resolution. In this article, we propose a novel approach for analyzing crowd mobility on a “city block” level. We first propose algorithms to detect homes, working places, and stay regions for individual user trajectories. Next, we propose a method for analyzing commute patterns and spatial correlation at a city block level. Using mobile cellular accessing trace data collected from users in Shanghai, we discover commute patterns, spatial correlation rules, as well as a hidden structure of the city based on crowd mobility analysis. Therefore, our proposed methods contribute to our understanding of human mobility in a large metropolitan area.
Funder
National Science Foundation
the National Nature Science Foundation of China
Beijing National Research Center for Information Science and Technology
the National Key Research and Development Program of China
research fund of Tsinghua University - Tencent Joint Laboratory for Internet Innovation Technology
Publisher
Association for Computing Machinery (ACM)
Subject
Discrete Mathematics and Combinatorics,Geometry and Topology,Computer Science Applications,Modelling and Simulation,Information Systems,Signal Processing
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