Urban green space systems (UGSS) play a crucial role in enhancing citizens’ well-being and promoting sustainable urban development through their ecosystem service values (ESV). However, understanding the spatiotemporal changes, driving factors, and influencing mechanisms of ESV remains a critical challenge for advancing urban green theories and formulating effective policies. This study focuses on Suzhou, China’s third-largest prefecture-level city by economic volume and ecological core city of the Taihu watershed, to evaluate the ESV of its UGSS from 2010 to 2020, identify key driving factors, and analyze their influencing mechanisms. Using the InVEST model combined with the entropy weight method (EWM), we assessed the ESV changes over the study period. To examine the influencing mechanisms, we employed an innovative XGBoost-GWR approach, where XGBoost was used to screen globally significant factors from 37 potential drivers, and geographically weighted regression (GWR) was applied to model local spatial heterogeneity, providing a research perspective that balances global nonlinear relationships with local spatial heterogeneity. The results revealed three key findings: First, while Suzhou’s UGSS ESV increased by 9.92% from 2010 to 2020, the Global Moran’s I index rose from 0.325 to 0.489, indicating that its spatial distribution became more uneven, highlighting the increased ecological risks. Second, climate, topography, landscape pattern, and vegetation emerged as the most significant driving factors, with topographic factors showing the greatest variation (the negatively impacted area increased by 455.60 km²) and climate having the largest overall impact but least variation. Third, the influencing mechanisms were primarily driven by land use changes resulting from urbanization and industrialization, leading to increased ecological risks such as soil erosion, pollution, landscape fragmentation, and habitat degradation, particularly in the Kunshan, Wujiang, and Zhangjiagang Districts, where agricultural land has been extensively converted to constructed land. This study not only elucidates the mechanisms influencing UGSS’s ESV driving factors but also expands the theoretical understanding of urbanization’s ecological impacts, providing valuable insights for optimizing UGSS layout and informing sustainable urban planning policies.

The green space system in metropolitan areas is crucial for maintaining environmental health and stability by regulating and supporting ecosystem service values (ESVs). The Suzhou–Wuxi–Changzhou metropolitan area is located in the core of the Yangtze River Delta, and its green space exemplifies this importance, despite facing challenges from rapid urbanization in past decades. Studying the categories of ESVs and their driving factors can facilitate the comprehension of ESVs’ dynamics, thereby promoting regional sustainable development. In this article, we used the inVEST module to calculate six ESV indicators (soil retention, annual water yield, habitat quality, carbon storage, nitrogen, and phosphorus absorption) of the Suzhou–Wuxi–Changzhou metropolitan area’s green space system from 2015 to 2020 and combined it with the entropy weight method (EWM) to allocate weights for these indicators and evaluate the total value of the ESVs. To address the weakness of the inVEST model in calculating the total value of multiple ESVs, the Xgboost algorithm was combined with PCA methods to screen its main driving factors from numerous measures. Finally, the GWR method was used to reveal the spatial and temporal change in the main driving factors’ impacts on ESVs in the study area over five years. The result shows (1) the spatial distribution of the total value of regulating and supporting ESVs in the Suzhou–Wuxi–Changzhou metropolitan area has become more uneven in 2020 compared with 2015; (2) the most important driving factors include landscape diversity, topographic gradient, economic activity intensity, humidity, and surface temperature; and (3) based on the analysis of GWR results, the study area has an overall increase in regional soil erosion due to the expansion of impervious areas. And some mountainous areas have habitat fragmentation because of incorrect economic activity. This study provides a new perspective for evaluating the sum of multiple types of ESVs and exploring their driving factors, as well as revealing the ecosystem problems of the Suzhou–Wuxi–Changzhou metropolitan area in recent years. It also provides a reference for policymakers to maintain local ecological stability and security.

Coordinating the synergistic development of ecological protection and recreational utilization is a core issue for the high-quality development of green spaces in metropolitan areas. Using the coupling coordination degree model (CCDM) and Moran’s I Outlier Clustering, this study spatially assesses the coupling coordination degree (CCD) between the ecological quality and recreation service intensity of the green spaces in the Suzhou-Wuxi-Changzhou region. It further employs the Geodetector model to identify the influencing factors affecting the CCD. The results show the following: (1) The overall regional coordination is low, with 83.96% of green spaces being in moderate-to-severe imbalance and only 16.04% reaching primary-to-intermediate coordination, highlighting a prominent supply–demand imbalance. (2) The spatial pattern exhibits a structure whereby values are “high in the center, low in the east and west”, showing significant spatial differentiation. (3) Among the influencing factors, socio-economic elements such as cultural attractiveness (q = 0.433) and economic development (q = 0.148) play a dominant role, indicating that imbalance is mainly driven by socio-economic factors. Accordingly, this study proposes spatial optimization strategies based on zonal management, balanced layout, and multi-dimensional drivers to promote balanced recreational supply, facilitate the synergy between ecological protection and recreational utilization, and achieve the sustainable development of regional green spaces.