Depicting urban boundaries from a mobility network of spatial interactions: a case study of Great Britain with geo-located Twitter data

ABSTRACT

Existing urban boundaries are usually defined by government agencies for administrative, economic, and political purposes. However, it is not clear whether the boundaries truly reflect human interactions with urban space in intra- and interregional activities. Defining urban boundaries that consider socioeconomic relationships and citizen commute patterns is important for many aspects of urban and regional planning. In this paper, we describe a method to delineate urban boundaries based upon human interactions with physical space inferred from social media. Specifically, we depicted the urban boundaries of Great Britain using a mobility network of Twitter user spatial interactions, which was inferred from over 69 million geo-located tweets. We define the non-administrative anthropographic boundaries in a hierarchical fashion based on different physical movement ranges of users derived from the collective mobility patterns of Twitter users in Great Britain. The results of strongly connected urban regions in the form of communities in the network space yield geographically cohesive, nonoverlapping urban areas, which provide a clear delineation of the non-administrative anthropographic urban boundaries of Great Britain. The method was applied to both national (Great Britain) and municipal scales (the London metropolis). While our results corresponded well with the administrative boundaries, many unexpected and interesting boundaries were identified. Importantly, as the depicted urban boundaries exhibited a strong instance of spatial proximity, we employed a gravity model to understand the distance decay effects in shaping the delineated urban boundaries. The model explains how geographical distances found in the mobility patterns affect the interaction intensity among different non-administrative anthropographic urban areas, which provides new insights into human spatial interactions with urban space.

KEYWORDS:

• Mobility pattern
• urban boundary
• spatial interaction
• spatial network
• community structure

Acknowledgments

We would like to thank the three anonymous reviewers for their constructive comments that helped improve the paper. We are grateful for insightful inputs to the manuscript received from Austin Davis and Ben Liebersohn in the CyberInfrastructure and Geospatial Information Laboratory at the University of Illinois at Urbana-Champaign. This material is based in part upon work supported by the U.S. National Science Foundation (NSF) [grant numbers 1047916 and 1443080]. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF. The computational work used the ROGER supercomputer, which is supported by NSF [grant number 1429699].

Disclosure statement

No potential conflict of interest was reported by the authors.

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Additional information

Funding

This work was supported by the National Science Foundation [1047916,1429699,1443080].