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PDF(810 KB)
基于绿视率的城市公园空间满意度调查研究
A study on spatial satisfaction of urban parks based on visible green index
以城市公园动态图像采集和空间满意度评价为基础，探讨绿视率对空间满意度的影响与相互关系，为科学评价基于心理感知的城市绿色空间质量，促进城市绿色空间结构优化提供理论依据。
以城市公园为调查目的地，通过动态图像采集、图像绿视率分析、动态满意度与静态满意度评价，结合社会人口学背景分析绿视率与空间满意度的相互关系与影响因素。
城市公园动态空间满意度评价和静态空间满意度评价呈显著的线性相关；超过50%图片样本的绿视率集中在30%~60%区间，并且绿视率与空间满意度呈现显著的弱负相关性；静态空间满意度评价存在户籍和性别的组间显著性差异。
人类偏好30%~60%绿视率，植被元素对个人空间满意度评价影响更大，静态满意度评价由于缺少与真实环境的感官交互作用，更容易受到社会人口学背景的影响。
This paper discusses the influence and correlation of the visible green index on spatial satisfaction based on urban park dynamic image collection and evaluation of spatial satisfaction. It provides a theoretical basis for scientific evaluation of urban green space quality based on psychological perception, thereby promoting the optimization of the urban green space structure.
Using urban parks as the investigation destination, the correlation between the visible green index and spatial satisfaction and the factors influencing this correlation was analyzed through urban park dynamic image collection, the visible green index analysis of images, evaluation of dynamic and static spatial satisfaction, and the social demographic background.
There was a significant linear correlation between dynamic spatial satisfaction and static spatial satisfaction. The visible green index of more than 50% of the image samples was concentrated in the range of 30%-60%, and there was a significant weakly negative correlation between the visible green index and spatial satisfaction. Further, there were significant differences between household groups and gender in static spatial satisfaction.
Human beings prefer a 30%-60% visible green index, and vegetation elements have a greater impact on personal spatial satisfaction. Static satisfaction is more susceptible to the social demographic background due to the lack of sensory interaction in the real environment.
城市公园 / 感知 / 空间满意度 / 绿视率 / 植视率 / 水视率
urban park / perception / spatial satisfaction / visible green index / visible plant index / visible water index
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