Urban tree failures during extreme wind events pose escalating risks to public safety in dense built environments. This study operationalizes and validates a multi-disciplinary risk assessment framework through intensive application at Beijing Forestry University (46.4 ha, 3322 trees). The system integrates GPR defect characterization, FEA-derived stability factors ( \({f}_{\text{r}\text{o}\text{t}}\) , \({f}_{\text{o}\text{f}\text{f}\text{s}\text{e}\text{t}}\) ), and CFD-based microscale wind prediction with linear interpolation (R2 = 0.977–0.986, RMSE < 0.73 m/s), enabling rapid translation of meteorological forecasts into canopy-level mechanical loads. Across 135 selected trees in three high-risk zones, the framework identified 25 high/very-high risk individuals (18.5%) and revealed uprooting as the dominant failure mode—with local wind direction variability causing overestimation of tree resistance when neglected. Case-specific application to two Chinese pines (T75: hollow rot \(\alpha \) = 0.55; T83: 60% windward root loss) informed targeted rigid-support interventions, subsequently validated during extreme wind events ( \({v}_{10}\) > 25 m/s). The methodology demonstrates scalable potential for precision urban tree management, bridging biomechanical modeling with operational disaster preparedness.
