For missions in Safety, Security, and Rescue Robotics (SSRR) maps are often a core deliverable. Hence it is of high interest to assess the quality of maps in a simple and efficient way. Since SSRR is mostly taking place in unstructured environments, 3D mapping has become more and more important. Here a method to evaluate the quality of 3D maps is presented that extends the previously developed 2D Fiducial approach to the third dimension. The artificial features are identified and located in 2D cross-sections of the map as well as in the 3D maps. It is then attempted to proof this concept using a ground truth map and robot generated maps from the RoboCup Rescue competition 2013 in Eindhoven.