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Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China

ZHANG Shanqi,  YANG Yu,  ZHEN Feng,  LOBSANG Tashi

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文章导航 > Chinese Geographical Science  > 2020 >  30(4): 695-709
ZHANG Shanqi, YANG Yu, ZHEN Feng, LOBSANG Tashi. Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China[J]. 中国地理科学, 2020, 30(4): 695-709. doi: 10.1007/s11769-020-1130-3
引用本文: ZHANG Shanqi, YANG Yu, ZHEN Feng, LOBSANG Tashi. Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China[J]. 中国地理科学, 2020, 30(4): 695-709. doi: 10.1007/s11769-020-1130-3
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ZHANG Shanqi, YANG Yu, ZHEN Feng, LOBSANG Tashi. Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China[J]. Chinese Geographical Science, 2020, 30(4): 695-709. doi: 10.1007/s11769-020-1130-3
Citation: ZHANG Shanqi, YANG Yu, ZHEN Feng, LOBSANG Tashi. Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China[J]. Chinese Geographical Science, 2020, 30(4): 695-709. doi: 10.1007/s11769-020-1130-3
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Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China

doi: 10.1007/s11769-020-1130-3

  • 1. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China;

  • 2. Provincial Engineering Laboratory of Smart City Design Simulation&Visualization, Nanjing 210046, China;

  • 3. Pancar Technology Co. Ltd. Nanjing 210049, China

基金项目: 

Under the auspices of the National Natural Science Foundation of China (No. 41571146), China Postdoctoral Science Foundation (No. 2019M651784)

详细信息
    通讯作者:

    ZHEN Feng. E-mail:zhenfeng@nju.edu.cn

Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China

  • 1. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China;

  • 2. Provincial Engineering Laboratory of Smart City Design Simulation&Visualization, Nanjing 210046, China;

  • 3. Pancar Technology Co. Ltd. Nanjing 210049, China

Funds: 

Under the auspices of the National Natural Science Foundation of China (No. 41571146), China Postdoctoral Science Foundation (No. 2019M651784)

  • 摘要: The increasing availability of data in the urban context (e.g., mobile phone, smart card and social media data) allows us to study urban dynamics at much finer temporal resolutions (e.g., diurnal urban dynamics). Mobile phone data, for instance, are found to be a useful data source for extracting diurnal human mobility patterns and for understanding urban dynamics. While previous studies often use call detail record (CDR) data, this study deploys aggregated network-driven mobile phone data that may reveal human mobility patterns more comprehensively and can mitigate some of the privacy concerns raised by mobile phone data usage. We first propose an analytical framework for characterizing and classifying urban areas based on their temporal activity patterns extracted from mobile phone data. Specifically, urban areas’ diurnal spatiotemporal signatures of human mobility patterns are obtained through longitudinal mobile phone data. Urban areas are then classified based on the obtained signatures. The classification provides insights into city planning and development. Using the proposed framework, a case study was implemented in the city of Wuhu, China to understand its urban dynamics. The empirical study suggests that human activities in the city of Wuhu are highly concentrated at the Traffic Analysis Zone (TAZ) level. This large portion of local activities suggests that development and planning strategies that are different from those used by metropolitan Chinese cities should be applied in the city of Wuhu. This article concludes with discussions on several common challenges associated with using network-driven mobile phone data, which should be addressed in future studies.
    Abstract: The increasing availability of data in the urban context (e.g., mobile phone, smart card and social media data) allows us to study urban dynamics at much finer temporal resolutions (e.g., diurnal urban dynamics). Mobile phone data, for instance, are found to be a useful data source for extracting diurnal human mobility patterns and for understanding urban dynamics. While previous studies often use call detail record (CDR) data, this study deploys aggregated network-driven mobile phone data that may reveal human mobility patterns more comprehensively and can mitigate some of the privacy concerns raised by mobile phone data usage. We first propose an analytical framework for characterizing and classifying urban areas based on their temporal activity patterns extracted from mobile phone data. Specifically, urban areas’ diurnal spatiotemporal signatures of human mobility patterns are obtained through longitudinal mobile phone data. Urban areas are then classified based on the obtained signatures. The classification provides insights into city planning and development. Using the proposed framework, a case study was implemented in the city of Wuhu, China to understand its urban dynamics. The empirical study suggests that human activities in the city of Wuhu are highly concentrated at the Traffic Analysis Zone (TAZ) level. This large portion of local activities suggests that development and planning strategies that are different from those used by metropolitan Chinese cities should be applied in the city of Wuhu. This article concludes with discussions on several common challenges associated with using network-driven mobile phone data, which should be addressed in future studies.
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  • 收稿日期:  2019-04-02

Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China

doi: 10.1007/s11769-020-1130-3
  • 1. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China;
  • 2. Provincial Engineering Laboratory of Smart City Design Simulation&Visualization, Nanjing 210046, China;
  • 3. Pancar Technology Co. Ltd. Nanjing 210049, China
    • 基金项目:

    Under the auspices of the National Natural Science Foundation of China (No. 41571146), China Postdoctoral Science Foundation (No. 2019M651784)

    通讯作者: ZHEN Feng. E-mail:zhenfeng@nju.edu.cn
  • 收稿日期: 2019-04-02

摘要: The increasing availability of data in the urban context (e.g., mobile phone, smart card and social media data) allows us to study urban dynamics at much finer temporal resolutions (e.g., diurnal urban dynamics). Mobile phone data, for instance, are found to be a useful data source for extracting diurnal human mobility patterns and for understanding urban dynamics. While previous studies often use call detail record (CDR) data, this study deploys aggregated network-driven mobile phone data that may reveal human mobility patterns more comprehensively and can mitigate some of the privacy concerns raised by mobile phone data usage. We first propose an analytical framework for characterizing and classifying urban areas based on their temporal activity patterns extracted from mobile phone data. Specifically, urban areas’ diurnal spatiotemporal signatures of human mobility patterns are obtained through longitudinal mobile phone data. Urban areas are then classified based on the obtained signatures. The classification provides insights into city planning and development. Using the proposed framework, a case study was implemented in the city of Wuhu, China to understand its urban dynamics. The empirical study suggests that human activities in the city of Wuhu are highly concentrated at the Traffic Analysis Zone (TAZ) level. This large portion of local activities suggests that development and planning strategies that are different from those used by metropolitan Chinese cities should be applied in the city of Wuhu. This article concludes with discussions on several common challenges associated with using network-driven mobile phone data, which should be addressed in future studies.

English Abstract

ZHANG Shanqi, YANG Yu, ZHEN Feng, LOBSANG Tashi. Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China[J]. 中国地理科学, 2020, 30(4): 695-709. doi: 10.1007/s11769-020-1130-3
引用本文: ZHANG Shanqi, YANG Yu, ZHEN Feng, LOBSANG Tashi. Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China[J]. 中国地理科学, 2020, 30(4): 695-709. doi: 10.1007/s11769-020-1130-3
shu
ZHANG Shanqi, YANG Yu, ZHEN Feng, LOBSANG Tashi. Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China[J]. Chinese Geographical Science, 2020, 30(4): 695-709. doi: 10.1007/s11769-020-1130-3
Citation: ZHANG Shanqi, YANG Yu, ZHEN Feng, LOBSANG Tashi. Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China[J]. Chinese Geographical Science, 2020, 30(4): 695-709. doi: 10.1007/s11769-020-1130-3
shu

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