Exploring the Spatiotemporal Influence of Community Regeneration on Urban Vitality: Unraveling Spatial Nonstationarity with Difference-in-Differences and Nonlinear Effect with Gradient Boosting Decision Tree Regression DOI Open Access

Hong Ni,

Haoran Li, Pengcheng Li

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3509 - 3509

Published: April 14, 2025

Community regeneration plays a pivotal role in creating human-centered spaces by transforming spatial configurations, enhancing multifunctional uses, and optimizing designs that promote sustainability vibrancy. However, the influence of such on vitality—particularly its heterogeneity nonlinear effects—remains insufficiently explored. This study presents comprehensive framework combines Difference-in-Differences (DID) method with multiple socio-spatial correlated factors, including place agglomeration, individual social perception, offering systematic assessment urban vitality evaluating impact interventions. By leveraging street-level imagery to capture environmental changes pre- post-regeneration, this research applies Gradient Boosting Decision Tree Regression (GBDT) uncover built environment dynamics affecting vitality. Empirical analysis from six districts Suzhou reveals following: (1) A pronounced increase is seen core areas, while peripheral exhibit more moderate improvements, highlighting spatially uneven outcomes. (2) In historically significant areas as Wuzhong, limited gains underscore complex interplay among historical preservation, development trajectories. (3) Furthermore, transformations, variations sky visibility, nonprivate vehicles, architectural elements, introduction glass-wall structures, impacts distinct threshold effects. advances discourse sustainable proposing context-sensitive, data-driven tools reconcile heritage conservation contemporary goals. It underscores need for integrated, adaptive strategies align local conditions, contexts, trajectories, informing policies green, inclusive, digitally transformed cities.

Language: Английский

Exploring the Spatiotemporal Influence of Community Regeneration on Urban Vitality: Unraveling Spatial Nonstationarity with Difference-in-Differences and Nonlinear Effect with Gradient Boosting Decision Tree Regression DOI Open Access

Hong Ni,

Haoran Li, Pengcheng Li

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3509 - 3509

Published: April 14, 2025

Community regeneration plays a pivotal role in creating human-centered spaces by transforming spatial configurations, enhancing multifunctional uses, and optimizing designs that promote sustainability vibrancy. However, the influence of such on vitality—particularly its heterogeneity nonlinear effects—remains insufficiently explored. This study presents comprehensive framework combines Difference-in-Differences (DID) method with multiple socio-spatial correlated factors, including place agglomeration, individual social perception, offering systematic assessment urban vitality evaluating impact interventions. By leveraging street-level imagery to capture environmental changes pre- post-regeneration, this research applies Gradient Boosting Decision Tree Regression (GBDT) uncover built environment dynamics affecting vitality. Empirical analysis from six districts Suzhou reveals following: (1) A pronounced increase is seen core areas, while peripheral exhibit more moderate improvements, highlighting spatially uneven outcomes. (2) In historically significant areas as Wuzhong, limited gains underscore complex interplay among historical preservation, development trajectories. (3) Furthermore, transformations, variations sky visibility, nonprivate vehicles, architectural elements, introduction glass-wall structures, impacts distinct threshold effects. advances discourse sustainable proposing context-sensitive, data-driven tools reconcile heritage conservation contemporary goals. It underscores need for integrated, adaptive strategies align local conditions, contexts, trajectories, informing policies green, inclusive, digitally transformed cities.

Language: Английский

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