Delineating and modeling activity space using geotagged social media data

Lingqian Hu, Zhenlong Li, Xinyue Ye

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


It has become increasingly important in spatial equity studies to understand activity spaces–where people conduct regular out-of-home activities. Big data can advance the identification of activity spaces and the understanding of spatial equity. Using the Los Angeles metropolitan area for the case study, this paper employs geotagged Twitter data to delineate activity spaces with two spatial measures: first, the average distance between users’ home location and activity locations; and second, the area covered between home and activity locations. The paper also finds significant relationship between the spatial measures of activity spaces and neighborhood spatial and socioeconomic characteristics. This research enriches the literature that aims to address spatial equity in activity spaces and demonstrates the applicability of big data in urban socio-spatial research.

Original languageEnglish (US)
Pages (from-to)277-288
Number of pages12
JournalCartography and Geographic Information Science
Issue number3
StatePublished - May 3 2020

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Management of Technology and Innovation

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