Estimating exercisality on urban trails using physical exercise trajectory data and network-constrained approach

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

  • Cailin Qiu
  • Jianquan Cheng
  • Yi Lu
  • Tianjie Zhang

Detail(s)

Original languageEnglish
Article number117361
Journal / PublicationSocial Science and Medicine
Volume361
Online published21 Sept 2024
Publication statusPublished - Nov 2024

Link(s)

Abstract

Green exercise is a key aspect of urban vitality, supporting the hypothesis that increased physical exercise boosts urban vitality. Although research on urban vitality considers green space a crucial aspect, existing studies have concentrated on external functioning from the perspective of special systems, often overlooking the unique internal functioning associated with exercisers. This study proposed an original conceptual framework of exercisality, which is composed of four dimensions: density, diversity, time continuity and energy expenditure. Considering urban trails are publicly accessible and linear-type green infrastructure for residents to conduct and maintain regular and habitual green exercise, we have developed an innovative quantitative approach to estimate and validate exercisality on urban trails (EUT), by utilizing physical exercise trajectory data from the Keep APP across central Beijing in 2022. The hot spots of EUT were identified through the innovative method of local indicators of network-constrained clusters. It is argued that this new index of EUT which is scale independence when applied to exercise trajectory big data, generates data driven evidence to support human well-being. © 2024 The Authors

Research Area(s)

  • APP trajectory data, Exercisality, Green exercise, Network-constrained approach, Urban trails

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