Fine-grained prediction of urban population using mobile phone location data-Reference-Cited by-同舟云学术

Fine-grained prediction of urban population using mobile phone location data

Published:2018-04-26 Issue:9 Volume:32 Page:1770-1786
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Chen Jie¹,Pei Tao¹²³,Shaw Shih-Lung⁴⁵,Lu Feng¹,Li Mingxiao¹²,Cheng Shifen¹²,Liu Xiliang¹,Zhang Hengcai¹

Affiliation:

1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

2. University of Chinese Academy of Sciences, Beijing, China

3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China

4. Department of Geography, University of Tennessee, Knoxville, TN, USA

5. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2018.1460753

Reference23 articles.

1. Daily rhythms of suburban commuters’ movements in the Tallinn metropolitan area: Case study with mobile positioning data

2. Understanding individual mobility patterns from urban sensing data: A mobile phone trace example

3. Fundamentals of Demographic Analysis: Concepts, Measures and Methods

4. Dynamic population mapping using mobile phone data

5. Inferring individual daily activities from mobile phone traces: A Boston example

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