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The impact of landscape complexity on preference ratings and eye fixation of various urban green space settings

固定(群体遗传学) 城市绿地 偏爱 空格(标点符号) 地理 生物 计算机科学 数学 统计 生物化学 基因 操作系统
作者
Qunyue Liu,Zhipeng Zhu,Xianjun Zeng,Zhixiong Zhuo,Baojian Ye,Fang Lei,Qitang Huang,Pengcheng Lai
出处
期刊:Urban Forestry & Urban Greening [Elsevier]
卷期号:66: 127411-127411 被引量:37
标识
DOI:10.1016/j.ufug.2021.127411
摘要

People’s perceptions on landscapes are important in the design process, and are closely associated with viewing behavior. However, little is known about the perceived landscape complexity of different urban green space settings in relation to people’s preference and eye movements. This study, therefore, investigated the influence of landscape complexity on preference ratings and eye fixation of lawn, path, plaza, and waterfront settings of urban green spaces. Six images for each type of setting were selected as stimuli and further classified into three categories based on the participants’ mean ratings of landscape complexity. Forty valid responses were obtained. The results indicated that participants’ ratings of landscape complexity and preference were positively correlated in all types of settings. There were significant differences in fixation count and average fixation duration between images with different levels of landscape complexity in lawn and waterscape settings. Fixation count was positively correlated with landscape complexity level in all lawn, plaza and waterscape setting images. Moreover, average fixation duration was negatively correlated with landscape complexity level in all lawn and waterscape setting images. Preference ratings had no definite relationships with fixation counts and average fixation duration. The findings of this study will help designers and urban park managers to effectively incorporate public perceptions in design and decision-making process. In addition, it provides new insights into the relationship between eye movements and landscape complexity and sheds some light on the application of eye tracking technology in landscape perception studies.
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