针对城市内无人机起降场布局规划不合理的现象，首先利用最大覆盖模型进行选址求解，但因其需求点分布不均且需求覆盖判定标准过于单一，使得求解结果出现覆盖率不高、选址过于集中的情况。针对此问题，考虑需求在空间内的连续分布，结合无人机禁飞区、应用场景等限制因素，提出了一种基于空间连续需求的无人机起降场最大覆盖模型选址办法，利用规则网格确定需求对象、多边形交点集（polygon intersection point set, PIPS）方法确定起降场候选点。以天津市滨海新区城市内无人机起降场选址研究为例，验证了改进模型的可行性，在起降场建设数量均为14时，改进模型将实际服务面积覆盖率从62.03%提升至88.61%。其结果表明：该方法更符合无人机起降场选址的实际需求，使起降场选址布局均匀合理，能够显著提高无人机起降场服务覆盖率。

To address the issue of land and capital waste caused by suboptimal site selection and construction models for urban drone landing and takeoff sites, the maximum coverage model is initially used for site selection. However, due to the uneven distribution of demand points and overly simplistic coverage determination criteria, the results show low coverage rates and overly concentrated site selection. To solve this problem, a method based on spatially continuous demand for the maximum coverage model of drone landing and takeoff site selection was proposed, considering factors such as no-fly zones and application scenarios. Demand objects were determined using a regular grid, and candidate sites were identified using the PIPS(polygon intersection point set) method. The feasibility of the improved model was validated through a case study of site selection for urban drone landing and takeoff sites in Binhai New Area, Tianjin. When the number of landing and takeoff sites was fixed at 14, the improved model increased the actual service area coverage rate from 62.03% to 88.61%. The results indicate that this method better meets the practical requirements for drone landing and takeoff site selection, resulting in more evenly distributed and rational site layouts, and significantly enhancing the service coverage rate of the drone landing and takeoff sites.