Delineating and modeling activity space using geotagged social media data
Document Type
Article
Publication Date
5-3-2020
Abstract
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.
Identifier
85079421705 (Scopus)
Publication Title
Cartography and Geographic Information Science
External Full Text Location
https://doi.org/10.1080/15230406.2019.1705187
e-ISSN
15450465
ISSN
15230406
First Page
277
Last Page
288
Issue
3
Volume
47
Grant
1416509
Fund Ref
National Science Foundation
Recommended Citation
Hu, Lingqian; Li, Zhenlong; and Ye, Xinyue, "Delineating and modeling activity space using geotagged social media data" (2020). Faculty Publications. 5307.
https://digitalcommons.njit.edu/fac_pubs/5307
