Estimating potential demand of bicycle trips from mobile phone data - An anchor-point based approach

Yang Xu, Shih Lung Shaw, Zhixiang Fang, Ling Yin

Research output: Journal article publicationJournal articleAcademic researchpeer-review

27 Citations (Scopus)


This study uses a large-scale mobile phone dataset to estimate potential demand of bicycle trips in a city. By identifying two important anchor points (night-time anchor point and day-time anchor point) from individual cellphone trajectories, this study proposes an anchor-point based trajectory segmentation method to partition cellphone trajectories into trip chain segments. By selecting trip chain segments that can potentially be served by bicycles, two indicators (inflow and outflow) are generated at the cellphone tower level to estimate the potential demand of incoming and outgoing bicycle trips at different places in the city and different times of a day. A maximum coverage location-allocation model is used to suggest locations of bike sharing stations based on the total demand generated at each cellphone tower. Two measures are introduced to further understand characteristics of the suggested bike station locations: (1) accessibility; and (2) dynamic relationships between incoming and outgoing trips. The accessibility measure quantifies how well the stations could serve bicycle users to reach other potential activity destinations. The dynamic relationships reflect the asymmetry of human travel patterns at different times of a day. The study indicates the value of mobile phone data to intelligent spatial decision support in public transportation planning.
Original languageEnglish
Article number131
JournalISPRS International Journal of Geo-Information
Issue number8
Publication statusPublished - 1 Aug 2016
Externally publishedYes


  • Anchor point
  • Bike sharing
  • Location-allocation
  • Mobile phone data
  • Trajectory segmentation
  • Travel demand
  • Trip chain

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Computers in Earth Sciences
  • Earth and Planetary Sciences (miscellaneous)


Dive into the research topics of 'Estimating potential demand of bicycle trips from mobile phone data - An anchor-point based approach'. Together they form a unique fingerprint.

Cite this