IDEAS home Printed from https://ideas.repec.org/a/taf/cjutxx/v19y2012i4p3-21.html
   My bibliography  Save this article

Towards Estimating Urban Population Distributions from Mobile Call Data

Author

Listed:
  • Chaogui Kang
  • Yu Liu
  • Xiujun Ma
  • Lun Wu

Abstract

Today, large-volume mobile phone call datasets are widely applied to investigate the spatio-temporal characteristics of human urban activity. This paper discusses several fundamental issues in estimating population distributions based on mobile call data. By adopting an individual-based call activity dataset that consists of nearly two million mobile subscribers who made over one hundred million communications over seven consecutive days, we explore the relationships among the Erlang values, the number of calls, and the number of active mobile subscribers. Then, the LandScan population density dataset is introduced to evaluate the process of estimating the population. The empirical findings indicate that: (1) Temporal variation exists in the relation between the Erlang values and the number of calls; (2) The number of calls is linearly proportional to the number of active mobile subscribers; (3) The proportion between the mobile subscribers and the actual total population varies in different areas, thus failing to represent the underlying population. Hence, the call activity reflects "activity intensity" rather than population distribution. The Erlang is a defective indicator of population distribution, whereas the number of calls serves as a better measure. This research provides an explicit clarification with respect to using call activity data for estimating population distribution.

Suggested Citation

  • Chaogui Kang & Yu Liu & Xiujun Ma & Lun Wu, 2012. "Towards Estimating Urban Population Distributions from Mobile Call Data," Journal of Urban Technology, Taylor & Francis Journals, vol. 19(4), pages 3-21, October.
    • Handle: RePEc:taf:cjutxx:v:19:y:2012:i:4:p:3-21
    DOI: 10.1080/10630732.2012.715479
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10630732.2012.715479
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/10630732.2012.715479?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wenlai Wang & Tao Pei & Jie Chen & Ci Song & Xi Wang & Hua Shu & Ting Ma & Yunyan Du, 2019. "Population Distributions of Age Groups and Their Influencing Factors Based on Mobile Phone Location Data: A Case Study of Beijing, China," Sustainability, MDPI, vol. 11(24), pages 1-19, December.
    2. Yoon Ha Lee & Ji Soo Lee & Seung Chan Baek & Won Hwa Hong, 2020. "Spatial Equity with Census Population Data vs. Floating Population Data: The Distribution of Earthquake Evacuation Shelters in Daegu, South Korea," Sustainability, MDPI, vol. 12(19), pages 1-17, September.
    3. He, Qingsong & He, Weishan & Song, Yan & Wu, Jiayu & Yin, Chaohui & Mou, Yanchuan, 2018. "The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’," Land Use Policy, Elsevier, vol. 78(C), pages 726-738.
    4. Yisheng Peng & Jiahui Liu & Tianyao Zhang & Xiangyang Li, 2021. "The Relationship between Urban Population Density Distribution and Land Use in Guangzhou, China: A Spatial Spillover Perspective," IJERPH, MDPI, vol. 18(22), pages 1-19, November.
    5. Fang Wang & Zhao Liu & Shanshan Shang & Yuelei Qin & Bihu Wu, 2019. "Vitality continuation or over-commercialization? Spatial structure characteristics of commercial services and population agglomeration in historic and cultural areas," Tourism Economics, , vol. 25(8), pages 1302-1326, December.
    6. Jun Li & Yuan Zhang & Qiming Qin & Yueguan Yan, 2017. "Investigating the Impact of Human Activity on Land Use/Cover Change in China’s Lijiang River Basin from the Perspective of Flow and Type of Population," Sustainability, MDPI, vol. 9(3), pages 1-16, March.
    7. Guanghua Chi & Jean-Claude Thill & Daoqin Tong & Li Shi & Yu Liu, 2016. "Uncovering regional characteristics from mobile phone data: A network science approach," Papers in Regional Science, Wiley Blackwell, vol. 95(3), pages 613-631, August.
    8. Ling Yin & Jie Chen & Hao Zhang & Zhile Yang & Qiao Wan & Li Ning & Jinxing Hu & Qi Yu, 2020. "Improving emergency evacuation planning with mobile phone location data," Environment and Planning B, , vol. 47(6), pages 964-980, July.
    9. Chaogui Kang & Dongwan Fan & Hongzan Jiao, 2021. "Validating activity, time, and space diversity as essential components of urban vitality," Environment and Planning B, , vol. 48(5), pages 1180-1197, June.
    10. Liguo Zhang & Langping Leng & Yongming Zeng & Xi Lin & Su Chen, 2021. "Spatial distribution of rural population using mixed geographically weighted regression: Evidence from Jiangxi Province in China," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-15, April.
    11. Benyong Wei & Bin Hu & Wenhua Qi, 2023. "Fine–Scale Spatiotemporal Distribution Assessment of Indoor Population Based on Single Buildings: A Case in Dongcheng Subdistrict, Xichang, China," Sustainability, MDPI, vol. 15(9), pages 1-16, April.
    12. Xiping Yang & Zhiyuan Zhao & Shiwei Lu, 2016. "Exploring Spatial-Temporal Patterns of Urban Human Mobility Hotspots," Sustainability, MDPI, vol. 8(7), pages 1-18, July.
    13. Chen, Bi Yu & Cheng, Xue-Ping & Kwan, Mei-Po & Schwanen, Tim, 2020. "Evaluating spatial accessibility to healthcare services under travel time uncertainty: A reliability-based floating catchment area approach," Journal of Transport Geography, Elsevier, vol. 87(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:cjutxx:v:19:y:2012:i:4:p:3-21. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/cjut20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.