In view of the large scale and normalized operation trend of unmanned aerial vehicle (UAV) in urban low altitude airspace, a evaluation method for the bearing capacity of urban low altitude airspace for UAVs is proposed. The geometric topological method is used to identify the reachable airspace. At the same time, a capacity-risk bi-level evaluation model is constructed by combining with the UAV safety risk factors. The bi-level optimization model is solved by the Method of Successive Averages (MSA) and the improved Particle Swarm Optimization (PSO) algorithm. To verify the effectiveness of the model and the algorithm, an airspace capacity evaluation scenario based on real world geographical information is constructed. The simulation results show that the low altitude airspace capacity evaluated by the proposed method is increased by 37.3% compared with the corridor-based method, and the number of UAV in high-risk areas is reduced significantly. The experimental results demonstrate that this method can be applied to the capacity evaluation of urban low altitude airspace and is effective.