Mining Spatial-temporal Clusters from Geo-databases

In order to mine spatial-temporal clusters from geo-databases, two clustering methods with close relationships are proposed, which are both based on neighborhood searching strategy, and rely on the sorted k-dist graph to automatically specify their respective algorithm arguments. We declare the most distinguishing advantage of our clustering methods is they avoid calculating the spatial-temporal distance between patterns which is a tough job. Our methods are validated with the successful extraction of seismic sequence from seismic databases, which is a typical example of spatial–temporal clusters.