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Article: Visual 3D morphology of street-level urban trees and older adults’ emotional well-being: A nonlinear machine learning model incorporating temporal dynamics

TitleVisual 3D morphology of street-level urban trees and older adults’ emotional well-being: A nonlinear machine learning model incorporating temporal dynamics
Authors
KeywordsChina
Healthy city
Mental well-being
Older adults
Urban green spaces
Issue Date1-Oct-2025
PublisherElsevier
Citation
Building and Environment, 2025, v. 284 How to Cite?
Abstract

Aging-in-place has increased the need for green design to support community-dwelling older adults to live independently with mental well-being. The three-dimensional (3D) morphology of street-level urban trees thus becomes particularly significant, as these are urban elements that create unique visual and spatial experiences and interact passively with older adults daily, especially in high-density built environments where meso-and macro-scale greenery is often lacking. To clarify the effects of 3D morphology on older adult's emotional well-being, this study 1) measured visual 3D metrics—tree height, structural complexity, coherence and structural diversity—from street view images that approximate a human-eye view, to capture the morphological characteristics of visible trees in the case study of Fuzhou, China; 2) assessed perceived happiness (as outcomes of emotional well-being) through paired comparisons and the Microsoft Trueskill approach and 3) conducted a quasi-longitudinal study with a non-linear random forest model incorporating temporal dynamics through lagged and differenced variables to enhance predictive capacity. Generally, visual 3D metrics were more important determinants of perceived happiness than socioeconomic characteristics, with a relative importance of 22.67 % and 6.97 %, respectively. Among visual 3D metrics, tree height had the largest impact, followed by coherence, structural diversity, and structural complexity. All metrics were positively associated with perceived happiness, with tree height and structural diversity following power associations, while coherence and structural complexity exhibited polynomial associations. Positive interactions between visual 3D metrics were also observed. These findings provide critical insights into the profound, nonlinear and synergistic effects of urban trees’ 3D morphology on mental well-being, offering practical guidance for urban landscape design to promote healthier cities. These findings provide critical insights into the profound, nonlinear and synergistic effects of urban trees’ 3D morphology on mental well-being, offering practical guidance for urban landscape design to promote healthier cities.


Persistent Identifierhttp://hdl.handle.net/10722/359013
ISSN
2023 Impact Factor: 7.1
2023 SCImago Journal Rankings: 1.647

 

DC FieldValueLanguage
dc.contributor.authorGuo, Huagui-
dc.contributor.authorWan, Boyu-
dc.contributor.authorLi, Jiajun-
dc.contributor.authorLi, Weifeng-
dc.contributor.authorYin, Jie-
dc.contributor.authorHo, Hung Chak-
dc.date.accessioned2025-08-19T00:32:07Z-
dc.date.available2025-08-19T00:32:07Z-
dc.date.issued2025-10-01-
dc.identifier.citationBuilding and Environment, 2025, v. 284-
dc.identifier.issn0360-1323-
dc.identifier.urihttp://hdl.handle.net/10722/359013-
dc.description.abstract<p>Aging-in-place has increased the need for green design to support community-dwelling older adults to live independently with mental well-being. The three-dimensional (3D) morphology of street-level urban trees thus becomes particularly significant, as these are urban elements that create unique visual and spatial experiences and interact passively with older adults daily, especially in high-density built environments where meso-and macro-scale greenery is often lacking. To clarify the effects of 3D morphology on older adult's emotional well-being, this study 1) measured visual 3D metrics—tree height, structural complexity, coherence and structural diversity—from street view images that approximate a human-eye view, to capture the morphological characteristics of visible trees in the case study of Fuzhou, China; 2) assessed perceived happiness (as outcomes of emotional well-being) through paired comparisons and the Microsoft Trueskill approach and 3) conducted a quasi-longitudinal study with a non-linear random forest model incorporating temporal dynamics through lagged and differenced variables to enhance predictive capacity. Generally, visual 3D metrics were more important determinants of perceived happiness than socioeconomic characteristics, with a relative importance of 22.67 % and 6.97 %, respectively. Among visual 3D metrics, tree height had the largest impact, followed by coherence, structural diversity, and structural complexity. All metrics were positively associated with perceived happiness, with tree height and structural diversity following power associations, while coherence and structural complexity exhibited polynomial associations. Positive interactions between visual 3D metrics were also observed. These findings provide critical insights into the profound, nonlinear and synergistic effects of urban trees’ 3D morphology on mental well-being, offering practical guidance for urban landscape design to promote healthier cities. These findings provide critical insights into the profound, nonlinear and synergistic effects of urban trees’ 3D morphology on mental well-being, offering practical guidance for urban landscape design to promote healthier cities.</p>-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofBuilding and Environment-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectChina-
dc.subjectHealthy city-
dc.subjectMental well-being-
dc.subjectOlder adults-
dc.subjectUrban green spaces-
dc.titleVisual 3D morphology of street-level urban trees and older adults’ emotional well-being: A nonlinear machine learning model incorporating temporal dynamics-
dc.typeArticle-
dc.identifier.doi10.1016/j.buildenv.2025.113410-
dc.identifier.scopuseid_2-s2.0-105010965328-
dc.identifier.volume284-
dc.identifier.eissn1873-684X-
dc.identifier.issnl0360-1323-

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