Visual and emotional interaction between people and post-industrial riverscape based on the significance of “Original – New Placement”

心理学 地理 生态学 业务 生物
作者
Chuli Huang,Fang Wei,Qisheng Han,Jing Xu,Sijia Qiu,Xinyue Ban,Yingying Huang,Ting‐Yu Huang
出处
期刊:Ecological Indicators [Elsevier]
卷期号:163: 112135-112135
标识
DOI:10.1016/j.ecolind.2024.112135
摘要

Post-industrial regeneration, the conversion and integration of brown lands into green spaces, has become a prevalent process in contemporary urban sustainable development. Previous research on post-industrial landscapes has mostly focused on qualitative studies and paid little attention to the visual and physical attributes of these landscapes, providing little quantitative analyses of their physical qualities. We examined the relationship between landscape characteristics and individual perceptions and preferences of post-industrial landscapes. We used statistical modeling, including multivariate stepwise regression models, to involve the multidimensional integration of participants' physiological responses, eye-tracking responses, and mental activity data. We found: 1) The hypothesis that "coherence and legibility may not serve as mediating factors in the relationship between low-level image features and preference as well as positive perception" has been rejected. 2) The post-industrial landscape has unique aesthetic features of "Original – New Placement". In this study, participants preferred artificial to natural scenes. 3) The significant factors in enhancing participants' perceptions and preferences were the increase in the percentages of industrial remains, new construction, and ground-covering plants elements. 4) The type of artificial views in the post-industrial landscape has been positively influenced by the sense of industrial historical atmosphere and the sense of aesthetic appeal for industrial remains. 5) The percentage of water in post-industrial waterfront environments might reduce participants' initial attraction to industrial remains in their original location. In application, these findings could help improve public preference and satisfaction in the design of post-industrial landscapes.
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