Work

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

Year: 2024

Type: article

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. • A novel concept of exercisality is proposed and critically justified. • Metrics and methods for quantifying exercisality on urban trails are proposed. • The exercisality framework has been empirically validated using exercise trajectory data and network-constrained analysis. • The robustness of exercisality pattern to temporal scale is tested. • Policy supporting for trails exercisality landscape is suggested to promote its city-wide demonstration effect.

Source: Social Science & Medicine

DOI: 10.1016/j.socscimed.2024.117361

Authors: Cailin Qiu, Jianquan Cheng, Yi Lu, Tianjie Zhang

Institutions: Tianjin University, Manchester Metropolitan University, City University of Hong Kong, City University of Hong Kong, Shenzhen Research Institute

Language: English

Topic: Urban Green Space and Health

Subfield: Health, Toxicology and Mutagenesis

Field: Environmental Science

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,390