Residence-Workplace Spatial Distribution Characteristics Analysis Based on Mobile Phone Data

The spatial distribution relationship between residence and workplace is essential to urban transportation planning. This paper analyzes residence-workplace spatial distribution in Nanjing by using mobile data. First, the raw data was grouped, positioned, and smoothed. Then, this paper identified residence and workplace locations by selecting possible stations, and calculating cumulative duration. Finally, the indexes including commute indicators, commute space distribution, and commute distance applied to analyze the commute features of three different districts: Xinjiekou, Daishan, and Ruanjiandadao. The results show 87.16% of residents work inside the district and that the commute distance of Xinjiekou residents is only 2.32 km. Up to 41.66% of residents work in the other districts and for Daishan residents the commute distance is 6.49 km. In Ruanjiandaao, 37.14% of workers come from the other districts and the commute distance of workers is 8.36 km.

• Record URL:
  https://doi.org/10.1061/9780784481523.038
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
• Supplemental Notes:
  • © 2018 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Du, Shu-ying
  • Ran, Bin
  • Zhang, Jian
  • Shi, Xiao-kai
  • Zhang, Xiao-li
  • Wang, Qing
• Conference:
  • 18th COTA International Conference of Transportation Professionals
  • Location: Beijing , China
  • Date: 2018-7-5 to 2018-7-8
• Publication Date: 2018-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 378-390
• Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility

Subject/Index Terms

• TRT Terms: Commuting; Residential location; Spatial analysis; Trip length; Workplaces
• Geographic Terms: Nanjing (China)
• Subject Areas: Highways; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01868931
• Record Type: Publication
• ISBN: 9780784481523
• Files: TRIS, ASCE
• Created Date: Dec 29 2022 1:08PM