A place-based model of local activity spaces: individual place exposure and characteristics

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Abstract

Researchers for long have hypothesized relationships between mobility, urban context, and health. Despite the ample amount of discussions, the empirical findings corroborating such associations remain to be marginal in the literature. It is growingly believed that the weakness of the observed associations can be largely explained by the common misspecification of the geographical context. Researchers coming from different fields have developed a wide range of methods for estimating the extents of these geographical contexts. In this article, we argue that no single approach yet has sufficiently been capable of capturing the complexity of human mobility patterns. Subsequently, we discuss that reaching a better understanding of individual activity spaces can be possible through a spatially sensitive estimation of place exposure. Following this discussion, we take an integrative person and place-based approach to create an individualized residential exposure model (IREM) to estimate the local activity spaces (LAS) of the individuals. This model is created using data collected through public participation GIS. Following a brief comparison of IREM with other commonly used LAS models, the article continues by presenting an empirical study of aging citizens in Helsinki area to demonstrate the usability of the proposed framework. In this study, we identify the main dimensions of LASs and seek their associations with socio-demographic characteristics of individuals and their location in the region. The promising results from comparisons and the interesting findings from the empirical part suggest both a methodological and conceptual improvement in capturing the complexity of local activity spaces.

Details

Original languageEnglish
Pages (from-to)227-252
Number of pages26
JournalJOURNAL OF GEOGRAPHICAL SYSTEMS
Volume20
Issue number3
Early online date5 Jan 2018
Publication statusPublished - Jul 2018
MoE publication typeA1 Journal article-refereed

    Research areas

  • Activity space, Local activity space, PPGIS, Modeling, Neighborhood, Mobility pattern

ID: 16981557