On radio aporee, we're researching the possibility to create non-geographical topographic maps out of the sounds and their meta data. Since it is impossible to create an exact 2-D image of n-dimensional data, we rather try to find tendencies, proximity and clusters of similarity. Distance implies difference, but nearness does not necessarily imply resemblance. Lines and structures between areas indicate divergence, like rivers and mountains separate nearby areas in real landscapes. How meaningful these maps can be depends on the pattern we choose for comparision. Data analysis is based on Peter Kleiweg's implementation of Teuvo Kohonen's algorithm.