Exploring Heterogeneous and Non-Linear Effects of the Built Environment on Street Quality: A Computational Approach Towards Precise Regeneration

Jiayu Xu, Yuxuan Liu, Jingfen Wu, Xuan Wang and Yu Ye ()
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Jiayu Xu: The College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Yuxuan Liu: The College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Jingfen Wu: The College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Xuan Wang: China Academy of Urban Planning and Design, Beijing 100044, China
Yu Ye: The College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China

Sustainability, 2025, vol. 17, issue 19, 1-24

Abstract: As a key strategy for broader sustainability, effective street regeneration requires a precise understanding of the built environment’s influence mechanisms. However, existing approaches often overlook the functional heterogeneity of streets and the non-linearity of their influence mechanisms. Addressing this gap, we developed an approach to analyze these mechanisms of the built environment, differentiated by street function. Integrating multi-source urban data, street quality was measured across three dimensions (visual quality, vibrancy, and functionality), and specialized weights for streets were determined according to their dominant functions. Applying this approach in Shanghai, we explained the non-linear effects of the built environment for each street function type through separate GBDT models and SHAP analysis. The results reveal that the influence mechanisms of built environment factors vary significantly across dominant street functions. Specifically, the heterogeneity of critical activation thresholds and saturation points provides direct evidence for more targeted regeneration strategies. Key findings highlight that a strong sense of enclosure is a priority for the quality of residential street, as measured by a low Sky View Factor. In contrast, vertical development intensity is a priority for commercial streets, as Floor Area Ratio requires a high activation threshold to exert a positive influence. In short, this research provides a computational approach that enables precise and data-driven interventions, which contribute to sustainable urban development.

Keywords: urban design; street quality; urban regeneration; built environment; non-linear effect (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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