How Blue–Green Integration Shapes Urban Emotional Behavior: Evidence from Facial Expressions in Social Media Photos
Urban mental health is increasingly influenced by daily environmental exposures, yet limited empirical evidence exists regarding how the spatial configuration of blue–green environments, rather than their mere quantity, relates to emotional behavior in high-density cities. Guided by restoration theories and a perception-based perspective on landscape integration, this study analyzes the urban core of Shanghai by linking blue–green configurations to emotional states inferred from 20,907 geotagged social media facial photographs. Facial expressions serve to derive indices for emotional valence and arousal. The results demonstrate significant spatial clustering of emotional behavior, where hotspots are concentrated in higher-quality and more open settings, while coldspots cluster in dense areas with sparse vegetation. Emotional behavior also exhibits demographic heterogeneity, as females display higher valence and arousal than males. Furthermore, happiness tends to increase with age across both genders, whereas arousal declines specifically among male age groups. Crucially, emotional outcomes align more consistently with landscape integration and configuration than with isolated blue or green areas. Factors such as high connectivity, superior vegetation condition, and configurations featuring water embedded within green space are associated with favorable emotional responses. Conversely, extensive edge-dominated interfaces and high traffic exposure correlate with less favorable outcomes. These findings suggest a shift in blue–green planning from increasing total area toward optimizing spatial composition. Specifically, priority should be given to embedded and cohesive designs alongside the reduction of ambient stressors to foster emotionally supportive environments in dense urban cores. Methodologically, image-derived behavioral traces provide a scalable and ecologically grounded approach for investigating place-based affect at a city scale.
Authors
- Ziyi Li (ORCID: https://orcid.org/0009-0008-3306-7048)
- Jian Wu (ORCID: https://orcid.org/0000-0002-3394-1507)
- Xiaolu Wu
- Huihui Liu
Institutions
- Wuhan University (CN)
- China Railway Major Bridge Reconnaissance & Design Institute (China) (CN)
- Beijing Urban Construction Design & Development Group (China) (CN)
Publication Details
- Journal
- Land
- Published
- 2026-03-27
- DOI
- https://doi.org/10.3390/land15040553
- Primary Topic
- Urban Green Space and Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00