Decoding waterfront spatial characteristics and public health correlation in historic cities: a case study of Suzhou, China

In high-density urban areas, waterfront spaces have garnered considerable attention as an essential medium for promoting public health. However, there remains a lack of empirical research on the comprehensive health effects of waterfront spaces within historic urban contexts. By taking the ancient city moat of Suzhou, China, as a case study, this paper examines the key attributes of waterfront spaces that influence both the physical and mental health of the public. The characteristic factors of waterfront spaces that affect health were identified based on a literature review. And then, non-invasive measurement techniques were employed to quantify the physical and mental health levels of users. Finally, a correlation analysis between the two sets of variables was conducted. Results indicate that the factor of blue exposure exhibits the most significant and positive correlation with both the physical and mental health of spatial users. Other influential factors, in descending order of impact, include color richness, shape indices, shoreline morphology, revetment types, cultural structures, enclosure degree, vegetation richness, hydrophilicity and the soft-hard landscape ratio. Beyond existing research, these findings demonstrate that optimizing the spatial proportion and layout of artificial elements in combination with natural elements can further enhance the health effects of waterfront spaces.

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Publication Details

Journal
Journal of Asian Architecture and Building Engineering
Published
2026-01-26
DOI
https://doi.org/10.1080/13467581.2026.2620902
Primary Topic
Coastal and Marine Management
Type
article
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article

Decoding waterfront spatial characteristics and public health correlation in historic cities: a case study of Suzhou, China

Hexiong Shi, Yue Chen, Li Wu, Wenjie Jiang
Journal of Asian Architecture and Building Engineering
Coastal and Marine Management
article

Decoding waterfront spatial characteristics and public health correlation in historic cities: a case study of Suzhou, China

Hexiong Shi, Yue Chen, Li Wu, Wenjie Jiang
article en

Abstract

In high-density urban areas, waterfront spaces have garnered considerable attention as an essential medium for promoting public health. However, there remains a lack of empirical research on the comprehensive health effects of waterfront spaces within historic urban contexts. By taking the ancient city moat of Suzhou, China, as a case study, this paper examines the key attributes of waterfront spaces that influence both the physical and mental health of the public. The characteristic factors of waterfront spaces that affect health were identified based on a literature review. And then, non-invasive measurement techniques were employed to quantify the physical and mental health levels of users. Finally, a correlation analysis between the two sets of variables was conducted. Results indicate that the factor of blue exposure exhibits the most significant and positive correlation with both the physical and mental health of spatial users. Other influential factors, in descending order of impact, include color richness, shape indices, shoreline morphology, revetment types, cultural structures, enclosure degree, vegetation richness, hydrophilicity and the soft-hard landscape ratio. Beyond existing research, these findings demonstrate that optimizing the spatial proportion and layout of artificial elements in combination with natural elements can further enhance the health effects of waterfront spaces.

Journal of Asian Architecture and Building Engineering
Chongqing Academy of Forestry (CN), State Forestry and Grassland Administration (CN), Wenzhou-Kean University (CN)
Sustainable cities and communities
Openalex Percentile: Top 82%
Coastal and Marine Management
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Decoding waterfront spatial characteristics and public health correlation in historic cities: a case study of Suzhou, China — Hexiong Shi, Yue Chen, et al. · Journal of Asian Architecture and Building Engineering (2026) | TGRS Research Map | TGRS