为应对新型飞行器快速发展带来的低空空域运行复杂化问题，提出了一种面向多维指标的低空空域容量综合评价方法。首先从安全性、效率性、有序性、资源承载性与环境适应性等5个维度出发，构建了层次化的低空空域容量评价指标体系。在缺乏实测数据的条件下，采用参数化建模与拉丁超立方采样（LHS）方法生成具有代表性的运行样本；随后结合熵权法与CRITIC法确定指标权重，再以TOPSIS模型为核心进行综合评价，实现了不同运行场景下低空空域容量的定量比较与等级划分。结果表明，气象适航率、最小时间头距和吞吐量是影响容量水平的关键指标，低空空域容量受“安全约束-效率主导-环境调节”机制共同作用。与传统依赖专家经验或仿真的方法相比，本文提出的这一模型具备客观性强、通用性好、可复现性高等优点。研究成果可为低空空域规划、运行管理及政策制定提供量化依据，并为后续动态容量预测与智能调度研究奠定方法基础。

To address the increasing operational complexity of low-altitude airspace caused by the rapid development of emerging aerial vehicles, this study proposed a comprehensive evaluation method for low-altitude airspace capacity based on multi-dimensional indicators. Firstly, the method constructed a hierarchical evaluation framework from five aspects—safety, efficiency, orderliness, resource support, and environmental adaptability. In the absence of measured data, a parameterized modeling approach and LHS (Latin Hypercube Sampling) were employed to generate representative operational samples. Then, indicator weights were objectively determined through a combined entropy weight method and CRITIC method, while the TOPSIS model was utilized for integrated evaluation and capacity ranking under various operational scenarios. Results indicate that meteorological suitability, minimum time headway, and throughput are the key factors influencing airspace capacity, which is jointly governed by the mechanism of "safety constraints, efficiency dominance, environmental regulation". Compared with traditional simulation or expert-based methods, the proposed model demonstrates strong objectivity, reproducibility and general applicability. The findings provide a quantitative foundation for low-altitude airspace planning, capacity management, and policy formulation, as well as methodological support for future dynamic capacity prediction and intelligent scheduling research.