This paper considers using unmanned aerial vehicles (UAVs) to survey remote sites across a city. Suppose that a UAV can take public transportation vehicles (PTVs) like a passenger. Then, it may reach a site that is unreachable by flying only. Based on this UAV-PTV scheme, we investigate a task-UAV assignment problem. We formulate a mixed-integer linear programming (MILP) problem that minimizes the overall energy consumption of UAVs, subject to that every site is surveyed by a certain number of UAVs during a given time window. This problem is NP-hard, and we present a sub-optimal solution. It orders the surveillance tasks according to the time windows. Then, starting from the earliest task, it assigns the tasks one by one to UAVs. The comparison with the brute force method shows that the proposed solution can achieve competitive performance in a reasonable time.