This study addresses the growing need for effective low-altitude airspace management driven by the rise of unmanned aerial vehicles (UAVs) and urban air mobility (UAM), including e-VTOL aircraft serving the expected UAM concept. The research develops a comprehensive airspace efficiency evaluation system based on ADS-B data, which offers real-time flight information. A TOPSIS-based evaluation model is proposed, incorporating seven core indicators: flight density, total flight time, capacity, traffic flow, specific aircraft flight counts, traffic composition, and altitude utilization. The model is applied to assess 28 airspaces over the period from January 1 to April 30, 2023. The findings demonstrate the model’s potential utility, with TOPSIS scores ranging from 0.263 to 0.699. The airspace “ZG-YC” showed the highest efficiency (score of 0.699), while “SN-N-L” had the lowest (0.263). The weighted indicators, derived from entropy-based methods, ensure a balanced consideration of horizontal, vertical, and temporal aspects of airspace usage. The evaluation results provide valuable insights for low-altitude airspace planning and management, particularly in optimizing capacity and safety in high-traffic regions. This method can also be used for real-time airspace monitoring and dynamic management, aiding in adaptive strategies for airspace allocation, reconfiguration, and resource optimization. The research contributes to the digitalization of airspace management and offers a practical framework for improving the efficiency and safety of low-altitude operations.
