Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
How Vegetation Colorization Design Affects Urban Forest Aesthetic Preference and Visual Attention: An Eye-Tracking Study
The enhancement of the urban forest landscape through vegetation colorization has emerged as a continuous concern for urban managers in southern Chinese cities. However, the understanding of how designers can effectively select the appropriate form and intensity of colorization design to align with users’ aesthetic preferences remains limited. The process of visual perception is closely intertwined with eye movements. Employing visualization techniques, this research aims to investigate the impact of colorization design on aesthetic benefits and eye movements in urban forests, considering four intensities (slight, low, medium, and high) and three forms (aggregate, homogeneous, and random). A total of 183 participants (with an average age of 23.5 ± 2.5 years) were randomly assigned to three groups to assess the aesthetics score, while eye-tracking devices were utilized to record eye movement behaviors. The outcomes indicate that a homogeneous design form and a moderate intensity of landscaping yield higher scenic benefits for urban forests. In the case of canopy landscape, both the form and intensity of landscaping have a significant influence on urban forest aesthetics. The HCI with aggregate form showed the best marginal effect (1.313). In contrast, MCI showed the best marginal effect when the design form was random and homogeneous (1.438, 1.308). Furthermore, although the form and intensity of the colorization design significantly affect eye exploration, the perception of landscape aesthetics does not correlate with eye movements. These findings provide valuable insights for design policies aimed at promoting the urban forest landscape, while also contributing to the enrichment of research in landscape perception studies employing eye-tracking technology.
How Vegetation Colorization Design Affects Urban Forest Aesthetic Preference and Visual Attention: An Eye-Tracking Study
The enhancement of the urban forest landscape through vegetation colorization has emerged as a continuous concern for urban managers in southern Chinese cities. However, the understanding of how designers can effectively select the appropriate form and intensity of colorization design to align with users’ aesthetic preferences remains limited. The process of visual perception is closely intertwined with eye movements. Employing visualization techniques, this research aims to investigate the impact of colorization design on aesthetic benefits and eye movements in urban forests, considering four intensities (slight, low, medium, and high) and three forms (aggregate, homogeneous, and random). A total of 183 participants (with an average age of 23.5 ± 2.5 years) were randomly assigned to three groups to assess the aesthetics score, while eye-tracking devices were utilized to record eye movement behaviors. The outcomes indicate that a homogeneous design form and a moderate intensity of landscaping yield higher scenic benefits for urban forests. In the case of canopy landscape, both the form and intensity of landscaping have a significant influence on urban forest aesthetics. The HCI with aggregate form showed the best marginal effect (1.313). In contrast, MCI showed the best marginal effect when the design form was random and homogeneous (1.438, 1.308). Furthermore, although the form and intensity of the colorization design significantly affect eye exploration, the perception of landscape aesthetics does not correlate with eye movements. These findings provide valuable insights for design policies aimed at promoting the urban forest landscape, while also contributing to the enrichment of research in landscape perception studies employing eye-tracking technology.
How Vegetation Colorization Design Affects Urban Forest Aesthetic Preference and Visual Attention: An Eye-Tracking Study
Ziru Chen (Autor:in) / Yaling Huang (Autor:in) / Yuanping Shen (Autor:in) / Weicong Fu (Autor:in) / Xiong Yao (Autor:in) / Jingkai Huang (Autor:in) / Yuxiang Lan (Autor:in) / Zhipeng Zhu (Autor:in) / Jiaying Dong (Autor:in)
2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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