The dynamic development of medical logistics utilizing Unmanned Aerial Vehicles (UAVs) in time-critical missions requires a careful balance between operational efficiency and stringent Ground Risk Class (GRC) safety requirements within dense urban environments. This study introduces and implements a multi-criteria optimization model for autonomous Beyond Visual Line of Sight (BVLOS) medical flight corridors based on spatial cost surface analysis. The proposed methodology integrates urban planning structures with the SORA risk assessment framework. Utilizing a dasymetric mapping technique, a spatial disaggregation of demographic data was performed, shifting from homogeneous administrative districts to a continuous population presence probability model based on urban capacity indicators derived from the draft General Plan of the City of Lublin. Using the Analytic Hierarchy Process (AHP), specific weights were assigned to five operational criteria, with human exposure defined as the overriding component of the model. The final spatial resistance map was generated through Multi-Criteria Evaluation (MCE), and the optimal trajectories were calculated using the Least-Cost Path (LCP) algorithm. To evaluate model robustness and address shifts in operational priorities, a scenario-based sensitivity analysis was conducted via weight permutation. Validation of the model across selected healthcare facilities in Lublin demonstrated that LCP corridors reduce the operational population exposure risk (Rop) by an average of 74.38% compared to geometric shortest paths. Despite the extended trajectories, these routes guarantee a 22–40% time advantage over ground Emergency Medical Services (EMS). Furthermore, network analysis revealed that spatial optimization does not significantly affect cellular handover dynamics, maintaining a comparable frequency of network switches across both routing strategies. The developed method serves as a robust decision support tool, enabling the safe operationalization of Urban Air Mobility (UAM) networks integrated with municipal spatial planning.