Measuring Street Quality: A Human-Centered Exploration Based on Multi-Sourced Data and Classical Urban Design Theories DOI Creative Commons
Renxi Wang,

Chengcheng Huang,

Yu Ye

и другие.

Buildings, Год журнала: 2024, Номер 14(11), С. 3332 - 3332

Опубликована: Окт. 22, 2024

Advancements in analytical tools have facilitated numerous studies on perceived street quality. However, most focused limited aspects of quality, failing to capture a comprehensive perception. This study introduces quantitative approach holistically measure quality by integrating three key dimensions: visual perception, network accessibility, and functional diversity. Using Beijing Shanghai as case studies, we employed artificial neural networks analyze view images quantify the characteristics streets. Additionally, accessibility was assessed through spatial design analysis, diversity evaluated using entropy points interest (POIs) data. The evaluation results were combined analytic hierarchy process. reliability accuracy this method validated further testing. Our offers human-centered, large-scale measurement framework, providing valuable insights for urban renewal design.

Язык: Английский

Measuring Street Quality: A Human-Centered Exploration Based on Multi-Sourced Data and Classical Urban Design Theories DOI Creative Commons
Renxi Wang,

Chengcheng Huang,

Yu Ye

и другие.

Buildings, Год журнала: 2024, Номер 14(11), С. 3332 - 3332

Опубликована: Окт. 22, 2024

Advancements in analytical tools have facilitated numerous studies on perceived street quality. However, most focused limited aspects of quality, failing to capture a comprehensive perception. This study introduces quantitative approach holistically measure quality by integrating three key dimensions: visual perception, network accessibility, and functional diversity. Using Beijing Shanghai as case studies, we employed artificial neural networks analyze view images quantify the characteristics streets. Additionally, accessibility was assessed through spatial design analysis, diversity evaluated using entropy points interest (POIs) data. The evaluation results were combined analytic hierarchy process. reliability accuracy this method validated further testing. Our offers human-centered, large-scale measurement framework, providing valuable insights for urban renewal design.

Язык: Английский

Процитировано

3