Evaluate Human Perception of the Built Environment in the Metro Station Area

北京 运输工程 公共交通 地理 土地利用 环路 感知 服务(商务) 中国 公交导向发展 城市规划 区域科学 土木工程 业务 工程类 营销 考古 神经科学 生物
作者
Wei Gao,Xiaoli Sun,Mei Zhao,Yong Gao,Haoran Ding
出处
期刊:Land [Multidisciplinary Digital Publishing Institute]
卷期号:13 (1): 90-90 被引量:5
标识
DOI:10.3390/land13010090
摘要

Transit-oriented development (TOD) has become a dominant form of spatial planning and land use in large cities internationally. As the intersections of urban space and rail transportation, metro station areas play a key public service function in the lives of city residents. Based on the “5D” index and Node-Place theory in the metro station area, current research on the built environment in metro station areas focuses on improving the economic and transportation efficiency while neglecting public perception of the construction of station space. Sentiments, as an important part of the individual’s perception, are closely related to the built environment. Therefore, this study takes 187 metro stations within the fifth ring road of Beijing, China, as an example and extracts public sentiment information from social media data using a wide range of natural language processing techniques to quantitatively analyze the distribution of the public’s sentiment characteristics (including intensity, polarity, and category) in the metro station area and deeply explores the spatial correlation with the distribution of the objective built environment elements. The study shows that influenced by the spatial design of the metro station, density, land use functions, etc., the sentiment intensity of the station area within the Fifth Ring Road of Beijing is “strong in the east and weak in the west, strong in the north and weak in the south”, and the sentiment polarity has the characteristic of gradually negative from inside to outside in a circular pattern. Synthesizing the sentiment perception in the metro station area, our study further divided the Beijing metro station area into four major categories and eight specific subtypes.
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