Multi-agent coordination and planning techniques play a fundamental role in designing control systems for autonomous multi-UAV-based information collection. The most important categories of information collection are exploration, surveillance, search and tracking. We introduce each category of information collection and then focus on a specific problem – multi-UAV-based surveillance in complex environments where sensor occlusions can occur due to high buildings and other obstacles in the target area. We formalize the problem and propose a solution as a decomposition of the problem in two subproblems: the problem of single-area surveillance and the problem of allocating UAVs to multiple areas. We present and compare several algorithms for the subproblems and prove their optimality. Finally, we empirically evaluate the performance of all algorithms on a realistic simulation of aerial surveillance, built using the AGENTFLY framework, and compare it to theoretical estimates.