Combining human perception and street accessibility to provide information for better street construction: a case study of Chengdu City, China

Huang, Zhongshan; Lee, Sunjung

doi:10.1080/13467581.2024.2399682

Journal of Asian Architecture and Building Engineering

2024

DOI: 10.1080/13467581.2024.2399682

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Combining human perception and street accessibility to provide information for better street construction: a case study of Chengdu City, China

Zhongshan Huang,

Sunjung Lee

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Integrating Streetscape Images, Machine Learning, and Space Syntax to Enhance Walkability: A Case Study of Seongbuk District, Seoul

Huang,

Wang,

Luo

et al. 2024

Land

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As urbanization rapidly progresses, streets have transitioned from mere transportation corridors to crucial spaces for daily life and social interaction. While past research has examined the impact of physical street characteristics on walkability, there is still a lack of large-scale quantitative assessments. This study systematically evaluates street walkability in Seongbuk District, Seoul, through the integration of streetscape images, machine learning, and space syntax. The physical characteristics of streets were extracted and analyzed in conjunction with space syntax to assess street accessibility, leading to a combined analysis of walkability and accessibility. The results reveal that the central and western regions of Seongbuk District outperform the eastern regions in overall street performance. Additionally, the study identifies four distinct street types based on their spatial distribution: high accessibility–high overall score, high accessibility–low overall score, low accessibility–high overall score, and low accessibility–low overall score. The findings not only provide a scientific basis for street development in Seongbuk District but also offer valuable insights for assessing and enhancing walkability in cities globally.

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Integrating Streetscape Images, Machine Learning, and Space Syntax to Enhance Walkability: A Case Study of Seongbuk District, Seoul

Huang,

Wang,

Luo

et al. 2024

Land

View full text Add to dashboard Cite

show abstract

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Combining human perception and street accessibility to provide information for better street construction: a case study of Chengdu City, China

Cited by 1 publication

References 54 publications

Integrating Streetscape Images, Machine Learning, and Space Syntax to Enhance Walkability: A Case Study of Seongbuk District, Seoul

Integrating Streetscape Images, Machine Learning, and Space Syntax to Enhance Walkability: A Case Study of Seongbuk District, Seoul

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