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Measuring segregation using patterns of daily travel behavior: A social interaction based model of exposure
Abstract Recent advances in transportation geography demonstrate the ability to compute a metropolitan scale metric of social interaction opportunities based on the time-geographic concept of joint accessibility. The method we put forward in this article decomposes the social interaction potential (SIP) metric into interactions within and between social groups, such as people of different race, income level, and occupation. This provides a novel metric of exposure, one of the fundamental spatial dimensions of segregation. In particular, the SIP metric is disaggregated into measures of inter-group and intra-group exposure. While activity spaces have been used to measure exposure in the geographic literature, these approaches do not adequately represent the dynamic nature of the target populations. We make the next step by representing both the source and target population groups by space–time prisms, thus more accurately representing spatial and temporal dynamics and constraints. Additionally, decomposition of the SIP metric means that each of the group-wise components of the SIP metric can be represented at zones of residence, workplace, and specific origin–destination pairs. Consequently, the spatial variation in segregation can be explored and hotspots of segregation and integration potential can be identified. The proposed approach is demonstrated for synthetic cities with different population distributions and daily commute flow characteristics, as well as for a case study of the Detroit–Warren–Livonia MSA.
Highlights Social Interaction Potential (SIP) is extended into a measure of exposure We quantify opportunities of within-group and between-group interactions The measure is sensitive to the spatial structure of a region, especially daily commuting patterns
Measuring segregation using patterns of daily travel behavior: A social interaction based model of exposure
Abstract Recent advances in transportation geography demonstrate the ability to compute a metropolitan scale metric of social interaction opportunities based on the time-geographic concept of joint accessibility. The method we put forward in this article decomposes the social interaction potential (SIP) metric into interactions within and between social groups, such as people of different race, income level, and occupation. This provides a novel metric of exposure, one of the fundamental spatial dimensions of segregation. In particular, the SIP metric is disaggregated into measures of inter-group and intra-group exposure. While activity spaces have been used to measure exposure in the geographic literature, these approaches do not adequately represent the dynamic nature of the target populations. We make the next step by representing both the source and target population groups by space–time prisms, thus more accurately representing spatial and temporal dynamics and constraints. Additionally, decomposition of the SIP metric means that each of the group-wise components of the SIP metric can be represented at zones of residence, workplace, and specific origin–destination pairs. Consequently, the spatial variation in segregation can be explored and hotspots of segregation and integration potential can be identified. The proposed approach is demonstrated for synthetic cities with different population distributions and daily commute flow characteristics, as well as for a case study of the Detroit–Warren–Livonia MSA.
Highlights Social Interaction Potential (SIP) is extended into a measure of exposure We quantify opportunities of within-group and between-group interactions The measure is sensitive to the spatial structure of a region, especially daily commuting patterns
Measuring segregation using patterns of daily travel behavior: A social interaction based model of exposure
Farber, Steven (Autor:in) / O'Kelly, Morton (Autor:in) / Miller, Harvey J. (Autor:in) / Neutens, Tijs (Autor:in)
Journal of Transport Geography ; 49 ; 26-38
19.10.2015
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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