A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data
Joint Authors
Li, Weifeng
Cheng, Xiaoyun
Duan, Zhengyu
Yang, Dongyuan
Guo, Gaohua
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-11-04
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning.
This study aimed to analyze the spatial interaction based on the large-scale mobile phone data.
The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics.
A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement.
The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association.
A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application.
The spatial interaction patterns and the representative features proved the rationality of the proposed framework.
American Psychological Association (APA)
Li, Weifeng& Cheng, Xiaoyun& Duan, Zhengyu& Yang, Dongyuan& Guo, Gaohua. 2014. A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1016723
Modern Language Association (MLA)
Li, Weifeng…[et al.]. A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1016723
American Medical Association (AMA)
Li, Weifeng& Cheng, Xiaoyun& Duan, Zhengyu& Yang, Dongyuan& Guo, Gaohua. A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1016723
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1016723