北京
开放的体验
地理
公制(单位)
城市景观
感知
空格(标点符号)
城市规划
中国
自然景观
相关性
地图学
计算机科学
心理学
环境规划
自然(考古学)
社会心理学
生态学
数学
营销
业务
考古
操作系统
几何学
生物
神经科学
作者
Wenning Li,Ranhao Sun,Hongbin He,Liding Chen
出处
期刊:Cities
[Elsevier]
日期:2023-10-17
卷期号:143: 104619-104619
被引量:3
标识
DOI:10.1016/j.cities.2023.104619
摘要
The impact of urban street landscapes on residents' sentiments is a critical concern. However, the current representation of street landscapes through landscape pattern two-dimensional metrics (LP2DM) derived from remote sensing images neglects the perceptibility of residents' visible environments at the eye level. To address this gap, we developed a novel landscape pattern three-dimensional metric (LP3DM) to quantitatively represent landscape perceptibility based on four individual perception dimensions: green space, gray space, openness, and crowding. We then investigated the relationships between LP3DM and residents' sentiments using Baidu street view images and Weibo social media textual big data in Beijing, China. Our results demonstrate that LP3DM is more significant correlated with residents' sentiments than LP2DM (average contribution, ACLP2DM=0.025, ACLP3DM=0.054). Notably, the greenness metric exhibited the highest contribution (AC=0.12), with the greenness three-dimensional metric showing a positive correlation (r = 0.15, p < 0.01) with residents' sentiments, while grayness exhibited a slightly negative correlation (r = −0.087, p < 0.1). Our study highlights the importance of considering the perceptibility of natural landscape elements in addition to their quantity during urban construction to enhance residents' sentimental well-being. Overall, our LP3DM framework offers a promising approach to capture residents' landscape perceptibility and inform urban planning and design decisions.
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