To address the issues of large collision detection scale and low collision detection efficiency in complex urban obstacle environments, which result in slow solving speeds for traditional visibility methods, a hierarchical convex hull visibility method is proposed. By pre-screening polygons in the environment using the principal convex hull, it narrows the scope of obstacles involved in visibility detection, reducing detection time. Simultaneously, a local convex hull visibility detection method is introduced. It performs polygon pair traversal to construct local convex hulls and employs bridge points for regional segmentation. This approach avoids invalid detections inherent in traditional global pair traversal, substantially improving detection efficiency. Urban environments of varying scales are constructed using real city data. Simulation comparisons are conducted against baseline path planning algorithms, related improved algorithms and existing visibility methods in the literature. Results demonstrate that the hierarchical convex hull visibility graph method rapidly generates high-quality paths, reducing planning time by 99.66%, 94.38% and 94.06% compared to traditional visibility graph methods, bidirectional rapidly-exploring random trees （Bi-RRT*） and Informed-RRT*, respectively. The proposed method effectively addresses the computational efficiency challenge for UAV path planning in complex urban environments.