Analyzing the distribution of human activity space from mobile phone usage: an individual and urban-oriented study

ABSTRACT

Travel activities are embodied as people’s needs to be physically present at certain locations. The development of Information and Communication Technologies (ICTs, such as mobile phones) has introduced new data sources for modeling human activities. Based on the scattered spatiotemporal points provided in mobile phone datasets, it is feasible to study the patterns (e.g., the scale, shape, and regularity) of human activities. In this paper, we propose methods for analyzing the distribution of human activity space from both individual and urban perspectives based on mobile phone data. The Weibull distribution is utilized to model three predefined measurements of activity space (radius, shape index, and entropy). The correlation between demographic factors (age and gender) and the usage of urban space is also tested to reveal underlying patterns. The results of this research will enhance the understanding of human activities in different urban systems and demographic groups, as well as providing novel methods to expand the important and widely applicable area of geographic knowledge discovery in the age of instant access.

KEYWORDS:

• Activity space
• human mobility
• mobile phones
• Weibull distribution
• data mining
• Big (geo)data

Acknowledgements

We thank Dr Yu Liu and Geosoft Lab at Peking University for providing the data. Gwen Raubal helped improving the grammar and style of this work. The reviewers provided excellent feedback, which helped us improving the content and clarity of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. When opening a new phone line, users can choose to provide or not provide their citizen ID which includes both the gender information and the date of birth. Detailed data are listed in Table 1.

2. China Statistical Yearbook, National Bureau of Statistics of China, 2008.

3. This conclusion was derived based on the landmarks on Google™ Map. Based on the request of data provider we are not able to provide the identifiable base maps from Google™ Map.

Additional information

Funding

This research was supported by the Swiss National Science Foundation [project # 205121_141284].