Finding Arbitrary Shaped Clusters with Related Extents in Space and Time

Abstract

The paper deals with density-based clustering of events, i.e. objects positioned in space and time, such as occurrences of earthquakes, forest fires, mobile phone calls, or photos with geographical references. Finding concentrations of events in space and time can help to discover interesting places and time periods. The spatial and temporal properties of event clusters, in particular, their spatial and temporal extents and densities, can be related to each other. Therefore, we suggest a two-step clustering method that considers relations of the spatial and temporal dimension. We demonstrate the work of the method on several examples of real data.