A Generalized Model of Activity Space
Seth E. Spielman; Alex D. Singleton (2022). Annals of the American Association of Geographers, 112(8), 2212-2229. DOI: 10.1080/24694452.2022.2077165
Abstract
This article introduces the concept of a generalized activity space to bridge area-based and activity-based representations of geographic context. We argue that microscale space–time paths fail to account for contextual determinants of behavior, because they emphasize “contacts” over “contexts,” a problem that could be solved, in part, by using a broader “generalized” representation of geographic context. This article develops the idea of a generalized activity space and empirically tests the viability of the concept. Support for the viability of the idea is identified through analysis of 34,500 trips by 7,550 individuals in Atlanta. We find that demographic characteristics and residential location jointly shape a person’s geographic context. Through a series of hypothesis tests, we find evidence that these location–demographic groupings are generalizable; that is, people with similar socioeconomic backgrounds and residential locations exhibit similar generalized activity spaces. Residential location, by itself, however, is not an effective descriptor of the configuration of a person’s context. We argue that generalized activity spaces have potential to inform study of how the environment influences behavior by allowing a more robust consideration of interplay between socioeconomic characteristics and the use of space.
Extended Summary
This research develops the concept of ‘generalised activity spaces’ to better understand how demographic characteristics and residential location combine to shape people’s geographic behaviour patterns. The paper addresses a fundamental tension in geographic research between individual-focused movement tracking and area-based neighbourhood analysis, arguing that both approaches have limitations when used in isolation. Using travel survey data from Atlanta covering 34,582 trips by 7,552 individuals, the study applies lifestyle segmentation through latent class analysis to identify four distinct groups: professional families, part-time non-professional families, professional singles, and older non-full-time workers. To enable comparison across different locations, the research standardises activity spaces using polar coordinate systems centred on each person’s home address. The methodology employs directional statistics and hypothesis testing to examine whether people with similar lifestyles and residential locations exhibit comparable spatial behaviour patterns. Key findings demonstrate that lifestyle groups show statistically significant differences in their directional travel patterns and distances travelled. Professional workers with families tend to have distinctive ‘dog bone’ shaped activity spaces, with concentrated activity around home and work locations connected by commuting routes. However, the research reveals that residential location alone is not sufficient to predict spatial behaviour - demographic characteristics play a crucial role in shaping how people use space. The study finds that people with similar lifestyles exhibit similar variance in travel direction regardless of where they live, supporting the concept of generalised activity spaces. This challenges traditional approaches that rely solely on residential neighbourhood characteristics to understand environmental exposures and social contexts. The research has important implications for urban planning, public health research, and transportation policy. By combining demographic profiling with spatial behaviour analysis, generalised activity spaces offer a more nuanced framework for understanding how different population groups interact with urban environments. This approach could improve environmental exposure assessments, inform targeted interventions, and enhance understanding of how social and spatial inequalities manifest in daily mobility patterns. The concept provides a bridge between individual-level GPS tracking studies and broader neighbourhood effects research, offering potential for more precise policy interventions that account for both who people are and where they live.
Key Findings
- People with similar lifestyles show statistically significant differences in directional travel patterns and distances travelled across urban areas.
- Residential location alone inadequately predicts spatial behaviour patterns - demographic characteristics crucially shape how people use geographic space.
- Professional workers exhibit distinctive ‘dog bone’ activity spaces with concentrated activity around home and work locations connected by commuting routes.
- Lifestyle groups demonstrate similar variance in travel direction regardless of residential location, supporting the generalised activity space concept.
- The research provides a methodological framework combining demographic profiling with spatial analysis to better understand environmental exposures and social contexts.
Citation
@article{spielman2022generalized,
author = {Seth E. Spielman; Alex D. Singleton},
title = {A Generalized Model of Activity Space},
journal = {Annals of the American Association of Geographers},
year = {2022},
volume = {112(8)},
pages = {2212-2229},
doi = {10.1080/24694452.2022.2077165}
}