We present an agent-based coordination and planning method for aerial surveillance of multiple urban areas using a group of fixed-wing unmanned aerial vehicles (UAVs). The method differs from the existing work by explicit consideration of sensor occlusions that can occur due to high buildings and other obstacles in the target area. The solution employs a decomposition of the problem in two subproblems: the problem of single-area surveillance and the problem of allocating UAVs to multiple areas. Three occlusion-aware methods for single-area surveillance are presented and compared. An algorithm for UAV allocation is presented and its optimality proved. The performance of all algorithms is evaluated empirically on a realistic simulation of aerial surveillance, built using the AgentFly framework, and is compared to theoretical estimates. Categories and Subject Descriptors I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence--Coherence and coordination, multiagent systems ...