Cross-national comparison of the restorative potential of urban forests in different seasons
Year: 2025
Type: article
Abstract: Understanding how people perceive environmental features is important for designing restorative and inclusive landscapes. While landscape perception is known to affect psychological responses, how this varies with cultural background and seasonal change is less well known. This study investigated whether and how culture affects the restorative potential of urban forests in different seasons via an online experiment using 360-degree videos recorded in summer and fall. Environmental characteristics were extracted from visible vegetation of images, acoustic metrics were computed based on sound recordings, and landscape spatial features were analyzed through viewshed analysis with LiDAR-derived digital models. Restorative potential was elicited from 104 participants in 12 randomly selected sites within forest, field, and water site types. Results from linear mixed-effects models show restorative potential depends upon cross-national differences in response to seasonal change and landscape attributes of greenness, foreground depth, and horizontal area, highlighting the need to consider the cultural contexts of present and future users in planning, designing, and managing urban forests for restorativeness. Restorative potential was lower in fall scenes with larger horizontal area for Chinese participants compared to Americans, whereas it increased more steeply with greenness for Chinese participants. Addressing the need for restoration in urban forests, we discuss considerations for balancing vegetation and landscape spatial attributes based on the cultural characteristics of multiple visitor groups.
Source: Landscape and Urban Planning
Institutions: University of Michigan, South China Agricultural University
Language: English
Topic: Urban Green Space and Health
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,120
OpenAlex ID: W4414399154