Comprehending the spatial–temporal transformation of urban resilience (UR) is fundamental for promoting sustainable urban growth in the Chinese context. In this study, a multi-dimensional index framework is developed to cover economic, social, ecological, and infrastructural aspects of resilience, assessing urban resilience across 282 prefecture-level cities between 2005 and 2022. By integrating the Time-Varying Entropy Method (TEM) with the Two-Stage Nested Theil Index (TNTI), we quantify the intensity and origins of spatial disparities in UR. Furthermore, spatial econometric models are employed to examine β convergence across regional and temporal dimensions. Additionally, the research adopts an Optimal Parameter-based Geographical Detector (OPGD) approach to explore and quantify the major determinants affecting urban resilience. The results reveal that (1) UR has significantly improved nationwide, with higher levels concentrated in eastern and southern China; (2) intra-provincial disparities are the dominant source of spatial differences, and continue to expand; (3) UR shows robust β-convergence nationally and regionally, although σ-convergence is limited to specific periods; (4) savings deposits per capita, ratio of employees, per capita fiscal expenditure and market size are identified as the core factors driving UR. The findings offer new insights into urban spatial governance under multi-dimensional constraints and challenges and serve as empirical guidance for narrowing resilience gaps and promoting balanced regional development.

The coordinated development of urban renewal (UR) and ecological resilience (ER) is essential for regional sustainability and livable city construction. Based on data from 108 cities in the Yangtze River Economic Belt (YREB) during 2012–2023, this study constructs the UR indicator system from the dimensions of urban infrastructure construction, social function development, and cultural and leisure facility construction. ER is evaluated in terms of resistance, adaptability, and recoverability. The spatiotemporal evolution of their coupling coordination degree (CCD) is then examined. In addition, the XGBoost-SHAP model is employed to identify the threshold of digital technological innovation (DTI) on CCD and its interactions with different development conditions. The results show that (1) CCD remained relatively low but improved slowly during the study period. UR lagged behind ER in most cities, indicating that insufficient UR development capacity was the main constraint on coordination between the two systems. (2) CCD exhibited a pronounced core–periphery pattern, with high-value areas mainly concentrated in provincial capitals and centrally administered municipalities within the YREB. (3) DTI was positively associated with CCD and exhibited a nonlinear pattern with a model-derived turning point, while the strength and pattern of this association varied across different development contexts. These findings enrich the understanding of UR-ER coordination and offer policy implications for sustainable urban governance.