Assessing Emotional Responses to the Spatial Quality of Urban Green Spaces through Self-Report and Face Recognition Measures

Lin Qiao, Jingwei Zhuang, Xuan Zhang, Yang Su and Yiping Xia
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Lin Qiao: Institute of Landscape Architecture, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
Jingwei Zhuang: Institute of Landscape Architecture, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
Xuan Zhang: Institute of Landscape Architecture, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
Yang Su: The Architectural Design & Research Institute of Zhejiang University Co, Ltd., Hangzhou 310030, China
Yiping Xia: Institute of Landscape Architecture, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China

IJERPH, 2021, vol. 18, issue 16, 1-22

Abstract: Although creating a high-quality urban green space (UGS) is of considerable importance in public health, few studies have used individuals’ emotions to evaluate the UGS quality. This study aims to conduct a multidimensional emotional assessment method of UGS from the perspective of spatial quality. Panoramic videos of 15 scenes in the West Lake Scenic Area were displayed to 34 participants. For each scene, 12 attributes regarding spatial quality were quantified, including perceived plant attributes, spatial structure attributes, and experiences of UGS. Then, the Self-Assessment-Manikin (SAM) scale and face recognition model were used to measure people’s valence-arousal emotion values. Among all the predictors, the percentages of water and plants were the most predictive indicators of emotional responses measured by SAM scale, while the interpretation rate of the model measured by face recognition was insufficiently high. Concerning gender differences, women experienced a significantly higher valence than men. Higher percentages of water and plants, larger sizes, approximate shape index, and lower canopy densities were often related to positive emotions. Hence, designers must consider all structural attributes of green spaces, as well as enrich visual perception and provide various activities while creating a UGS. In addition, we suggest combining both physiological and psychological methods to assess emotional responses in future studies. Because the face recognition model can provide objective measurement of emotional responses, and the self-report questionnaire is much easier to administer and can be used as a supplement.

Keywords: urban green space; spatial quality; emotional responses; structural attributes; face recognition (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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