Publication Type

Journal Article

Version

publishedVersion

Publication Date

1-2026

Abstract

Urban environments are increasingly recognised for their potential to support psychological restoration, yet most studies assess green and grey spaces in isolation and rely on static, lab-based measures. This study introduces a multi-layered analytical framework that integrates experimental walking, momentary perception tracking, and machine learning to investigate how multisensory urban features shape restoration. Conducted on a university campus, the experiment exposed 20 participants to sequential grey–green–grey walking routes. Restoration was measured through pre/post psychometric surveys, heart rate variability (HRV), and minute-level micro-surveys during walking. Results reveal three key insights: (1) green exposure induces a short-term “inoculation effect”, with restorative benefits persisting even after re-entering grey environments; (2) visual features emerged as the most influential predictors of restoration, followed by noise and microclimate; and (3) solar irradiance — when balanced with moderate temperature and humidity — positively contributing to relaxation and stress reduction. Beyond experiments, we simulated design interventions on low-restoration scenarios using a large language model to enhance visual attributes, followed by predictive evaluation via machine learning. These simulations showed measurable improvements in predicted restoration, validating a data-driven approach for environmental optimisation. This research contributes to neurourbanism by bridging spatial sensing, physiological feedback, and AI-driven interpretation. It offers practical guidance for creating psychologically supportive urban environments — such as prioritising early green exposure and mitigating noise pollution — and introduces a replicable pipeline for evaluating restorative potential in future urban design.

Keywords

Built environment, Environmental psychology, Multisensory perceptions, Neurourbanism, Mental well-being, Microclimate

Discipline

Urban Studies and Planning

Research Areas

Integrative Research Areas

Publication

Building and Environment

Volume

287

First Page

1

Last Page

17

ISSN

0360-1323

Identifier

10.1016/j.buildenv.2025.113748

Publisher

Elsevier

Additional URL

https://doi.org/10.1016/j.buildenv.2025.113748

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