Understanding Core Districts of City using Human Activity Data

Understanding Core Districts of City using Human Activity Data

Duan Hu Jie Yang Benxiong Huang

The Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, China

The Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, China

Communication software center, EIE dept, Huazhong University of Science and Technology, China

Corresponding Author Email: 
huduan@whut.edu.cn, jieyang@ whut. edu. cn
Page: 
224-238
|
DOI: 
https://doi.org/10.18280/ama_b.600114
Received: 
15 March 2017
|
Accepted: 
15 April 2017
|
Published: 
31 March 2017
| Citation

OPEN ACCESS

Abstract: 

For "polycentric" urban systems, the role of city centers and their human flows’s spatial influence on the surrounding area remain a challenging problem with many applications ranging from transportation planning to epidemiology. Firstly, we segmented urban area to different districts as the basic research unit and abstract latent activity contexts from large scale call logs in city using existing approaches. By proposing urban area as a inter-district network model of which edge is measured by temporal-spatial proximity among different districts stem from those latent activity contexts, we identified core districts of city by using a network-based method based on community detection and local centrality. We further analyzed the functional role of these core districts in city. It provides a feasible approach to uncover spatial structure of an urban system.

Keywords: 

City’s core districts, community detection, human activity

1. Introduction
2. Problem Definition and Methodology
3. Case Study
4. Related Work
5. Conclusion
Acknowledgments
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