In this paper we propose distributed algorithms that solve the coverage problem in 3D space. In particular, we use a swarm of unmanned aerial vehicles (UAVs) in order to explore a possibly unknown area. Actual use cases include the automated acquisition of sensory data in operations that try to gain extensive knowledge about an area. First, we try to efficiently cover a predefined 3D space with multiple UAVs. Second, we target to maintain intra-swarm connectivity during the whole operation. Consequently, we develop and enhance metrics for benchmarking the resulting system with respect to coverage and communication capabilities. The algorithms were optimized towards getting a quick overview that is iteratively refined by getting more accurate data. This principle is similar to mip-mapping in computer graphics.