How does green technological innovation shape urban resilience? Revealing nonlinear relationships via explainable machine learning

Green technological innovation (GTEC) drives economic growth, environmental protection, and social progress. Its contributions to urban resilience (UR) – enabling cities to adapt to climate risks, resource constraints, and socio-economic shocks – remain underexplored. To address this, our study first constructs a multidimensional UR framework for 108 Yangtze River Economic Belt (YREB) cities (2010–2022) and analyzes the spatiotemporal evolution of UR, then explores the nonlinear relationships of GTEC using explainable machine learning. Results indicate that the UR in YREB has improved by 42%, with an agglomeration effect. GTEC contributes 59% to UR, proving to be a key contributor with a threshold effect. GTEC’s positive contribution threshold to UR is 0.4. The study emphasizes that cities with higher GTEC should focus on high-tech manufacturing and services to promote the optimization and upgrading of industrial structures, enhancing their economic resilience and radiation effects. Meanwhile, cities with weaker GTEC should increase infrastructure investment and foster cooperation with central cities. In the YREB, the upper reaches should prioritize ecological development, the middle regions should focus on the long-term development of the service sector and leverage the bonding role, while the lower areas should strengthen green regulation to drive GTEC and corporate green transformation. The study reveals the complex nonlinear relationships between GTEC and UR, highlighting the need to develop GTEC-driven UR improvement strategies tailored to each city’s specific conditions, social context, and development patterns, rather than blindly pursuing GTEC.