Open‐source tools for the measurement of socio‐spatial segregation in activity spaces

Abstract

AbstractOver the last decade, socio‐spatial segregation of different population groups in activity spaces has attracted considerable attention from geographers and sociologists. A careful examination of such activity‐space segregation can provide a more comprehensive description of dynamic intergroup relations in society than conventional residential segregation, as its measurement is not limited to a particular place. However, the evaluation of activity‐space segregation is a challenging task because it requires the manipulation of large spatiotemporal data sets. The lack of software tools that can assist researchers in exploring and analyzing individuals’ travel trajectories is one of the significant impediments to empirical studies. To address this practical limitation, this article proposes a combined use of two R packages, namely, slice and seg: the former provides tools for storing and manipulating activity‐space data, and the latter implements several existing measures of segregation that can be applied to various social places. The proposed approach is applied to the measurement of activity‐space segregation between high‐ and low‐income groups in Seoul to illustrate the key features of the packages. The results demonstrate that the use of these packages would make it more convenient to conduct activity‐space segregation research and enhance our understanding of the complex socio‐spatial phenomenon.