This article considers deploying a dual-functional unmanned aerial vehicle (UAV) as both an aerial data collector and aerial anchor node (AN) to assist the ground base stations in providing integrated localization and communication (ILAC) service in urban areas. A major challenge to the urban ILAC service quality lies in the severe blockage of ground-to-air links by densely located buildings. To improve the service quality, we leverage the recent advance in urban physical environment map (PEM), also known as the three-dimensional (3-D) city map, to aid in optimizing the 3-D deployment of UAV. This allows a UAV to avoid blockages and establish strong acrlong LoS links to all target ground users. We propose a PEM-aided ILAC service model and formulate a UAV 3-D deployment optimization problem. The aim is to maximize the sum communication rate of ground users while satisfying individual localization accuracy and communication rate constraints. The problem is very challenging to solve mainly because the localization accuracy and blockage-avoiding constraints are both nonconvex with respect to UAV position. To tackle the problem, we first adopt a new localization accuracy metric and subsequently derive a convex expression of the localization constraint. Then, we convert the blockage-avoiding constraints into an equivalent and analytically tractable form and propose an efficient iterative algorithm to solve the UAV deployment optimization problem. Simulation results show that the proposed method achieves close-to-optimal performance under dense urban blockage setups, while significantly reducing the computational complexity.