Impact of Streetscape Built Environment Characteristics on Human Perceptions Using Street View Imagery and Deep Learning: A Case Study of Changbai Island, Shenyang

Since the reform and opening-up policy, the accelerated urbanization rate has triggered extensive construction of new towns, leading to architectural homogenization and environmental quality degradation. As urban development transitions toward a “quality improvement” paradigm, there is an urgent need to synergistically enhance the health performance of human settlements through the optimization of public space environments. The purpose of this study is to explore the impact of the built environment of urban streets on residents’ perceptions. In particular, in the context of rapid urbanization, how to improve the mental health and quality of life of residents by improving the street environment. Changbai Island Street in the Heping District of Shenyang City was selected for the study. Baidu Street View images combined with machine learning were employed to quantify physical characterizations like street plants and buildings. The ‘Place Pulse 2.0’ dataset was utilized to obtain data on residents’ perceptions of streets as beautiful, safe, boring, and lively. Correlation and regression analyses were used to reveal the relationship between physical characteristics such as green visual index, openness, and pedestrians. It was discovered that the green visual index had a positive effect on perceptions of it being beautiful and safe, while openness and building enclosure factors influenced perceptions of it being lively or boring. This study provides empirical data support for urban planning, emphasizing the need to focus on integrating environmental greenery, a sense of spatial enclosure, and traffic mobility in street design. Optimization strategies such as increasing green coverage, controlling building density, optimizing pedestrian space, and enhancing the sense of street enclosure were proposed. The results of the study not only help to understand the relationship between the built environment of streets and residents’ perceptions but also provide a theoretical basis and practical guidance for urban space design.

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Publication Details

Journal
Buildings
Published
2025-05-01
DOI
https://doi.org/10.3390/buildings15091524
Citations
13
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
15.60

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article

Impact of Streetscape Built Environment Characteristics on Human Perceptions Using Street View Imagery and Deep Learning: A Case Study of Changbai Island, Shenyang

Lu Xu, Dong Sun, Yumeng Meng, Xiang Ji et al.
13 citations
Buildings
Urban Green Space and Health
15.60
article

Impact of Streetscape Built Environment Characteristics on Human Perceptions Using Street View Imagery and Deep Learning: A Case Study of Changbai Island, Shenyang

Lu Xu, Dong Sun, Yumeng Meng, Xiang Ji, Mei Lyu, Qingyu Li, Yiqing Yu
article en
13 citations

Abstract

Since the reform and opening-up policy, the accelerated urbanization rate has triggered extensive construction of new towns, leading to architectural homogenization and environmental quality degradation. As urban development transitions toward a “quality improvement” paradigm, there is an urgent need to synergistically enhance the health performance of human settlements through the optimization of public space environments. The purpose of this study is to explore the impact of the built environment of urban streets on residents’ perceptions. In particular, in the context of rapid urbanization, how to improve the mental health and quality of life of residents by improving the street environment. Changbai Island Street in the Heping District of Shenyang City was selected for the study. Baidu Street View images combined with machine learning were employed to quantify physical characterizations like street plants and buildings. The ‘Place Pulse 2.0’ dataset was utilized to obtain data on residents’ perceptions of streets as beautiful, safe, boring, and lively. Correlation and regression analyses were used to reveal the relationship between physical characteristics such as green visual index, openness, and pedestrians. It was discovered that the green visual index had a positive effect on perceptions of it being beautiful and safe, while openness and building enclosure factors influenced perceptions of it being lively or boring. This study provides empirical data support for urban planning, emphasizing the need to focus on integrating environmental greenery, a sense of spatial enclosure, and traffic mobility in street design. Optimization strategies such as increasing green coverage, controlling building density, optimizing pedestrian space, and enhancing the sense of street enclosure were proposed. The results of the study not only help to understand the relationship between the built environment of streets and residents’ perceptions but also provide a theoretical basis and practical guidance for urban space design.

BuildingsVol. 15(9)
The University of Kitakyushu (JP), Shenyang Jianzhu University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 1%
Urban Green Space and Health
15.60
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