Revealing urban–rural sustainability dynamics based on multi-source data and machine learning: spatio-temporal hotspots, driving mechanisms, and non-linear thresholds in Suzhou, China

Rapid urban expansion has transformed rural land use, generating multiple sustainability challenges, including environmental pollution, habitat degradation, and crises of community identity. However, existing studies lack a quantitative framework that captures the multidimensional coupling among economic vitality, ecological integrity, and social wellbeing during urban–rural transitions, limiting guidance for integrating urban and rural landscapes. To respond to this issue, this study introduces an integrated Urban-Rural Sustainability Index (URSI) that encompasses economic, ecological, and social dimensions. Additionally, it develops a methodological framework that combines a Random Effects Model (REM), an Extreme Gradient Boosting (XGBoost) model, and Shapley Additive Explanations (SHAP) to identify both linear and non-linear relationships, interaction effects, and threshold conditions, while ensuring predictive accuracy and interpretability. Using geospatial data from Suzhou, China, this study systematically examines the spatial-temporal dynamics of urban-rural integration and associated sustainable outcomes between 2012 and 2024. Three key findings were revealed: (1) Urban-Rural Sustainability Index (URSI)-based conflict exhibits significant spatial clustering, evolving from a monocentric hotspot into a polycentric, multi-nodal pattern as urban expansion proceeds; (2) REM results reveal heterogeneous effects across land use types: built-up area is positively associated with conflict, whereas farmland, water, and forest are negatively associated, indicating a buffering role of ecological and agricultural stocks; (3) XGBoost–SHAP analysis enhances these findings by identifying segmented effects and indicative operating ranges, including an inflection around a built-up area about 60%, diminishing marginal mitigation from water coverage around 15%, and conflict alleviation when contiguous farmland is maintained near 20%. Building upon these empirical insights, this study proposes targeted strategies to enhance urban-rural sustainability, including spatially differentiated land-use management, prioritising blue-green infrastructure in urban planning and balancing sustainability pressures within urban areas. The proposed framework and analytical methodology provide a transferable foundation for future research and practical urban-rural sustainability planning across diverse geographical contexts.