Understanding Spatial and Temporal Change Patterns of Population in Urban Areas Using Mobile Phone Data

Tianwen Liang,Zheng Zhang,Huan Liu,T Coenye,H Huang

doi:10.1051/e3sconf/202014502007

Tianwen Liang, Zheng Zhang + Show 3 more

Open Access

https://doi.org/10.1051/e3sconf/202014502007

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Abstract

The wide application of information computing technology has allowed for the emergence of big data on tracing human activities. Therefore, it provides an opportunity to explore temporal profile of population changes in geographical area subdivisions. In this paper, we present a multi-step method to characterize and approximate temporal changes of population in a geographical area subdivision using eigen decomposition. Datasets in weekday and weekend are decomposed to obtain the principal temporal change profiles in Xiamen, China. The Principal Components are common patterns of temporal population changes shared by most geographical area subdivisions. Its corresponding elements in eigenvectors could be regard as a coefficient to principal components. Then, a measure, which is the similarity of each eigenvector to a basis vector, that could characterize the temporal population change is established. Based on this, the coupling interaction between population changes and land use characteristics is explored using this measure. It shows that it is restricted by land use characteristics and also is a reflection of population changes over time. These results provided an insight on understanding temporal population change patterns and it would help to improve urban planning and establish a job-housing balance.

Highlights

With the rapid development of China's economy and society, the frequency at which Chinese citizens travel for business activities, official activities, tourism and entertainment becomes higher
Human activity data being difficult to obtain directly, we can infer this information from the human mobility information because of human activities are coupled with land use characteristics
Attempt to explore the underlying patterns of population changes over time in a metropolitan area and characterize these change patterns in Traffic Analysis Zones (TAZs) using low dimensional structures

Summary

Introduction

With the rapid development of China's economy and society, the frequency at which Chinese citizens travel for business activities, official activities, tourism and entertainment becomes higher. The travel demand is becoming more personalized and diversified. Various travel demand considerably influences urban traffic conditions(Zhou, Murphy, & Long, 2014). Population changes are coupled with local built environment. Insights on population changes and interactions with built environment in a geographical area subdivision are essential for developing traffic management strategies for distinctive travel demand. It can provide efficient, safe, environment-friendly and equitable transportation services to the public

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