A fast automatic identification method for seismic belts based on Delaunay triangulation

Earthquake prediction practice and a large number of earthquake cases show that there may be abnormal images of small earthquake belts near the epicenter before strong earthquakes occur. For a static small earthquakes spatial distribution, due to the complexity of exhaustive algorithm, the fast automatic identification method of seismic belts has not yet been realized. Visual identification is still the main method of seismic belt discrimination. Based on the Delaunay triangulation, this paper presents a fast automatic identification method of seismic belts. The effectiveness of this method is proved by a 1000 random points test and an actual example of the 4-magnitude belts before the 2005 Jiujiang M5.7 Earthquake. The results show that: (1) Using Delaunay triangulation method, we can fast get the spatial relationship between two neighboring points; (2) using the two neighboring relationships, it can automatically extend to cluster, which carries the key information of seismic belt; (3) using the technology of minimum enclosing rectangle (MER) for the identified cluster, we can get the shape and structural information of the MER, which can be called the “suspect seismic belt”; (4) after using the other restrictions to sort and filter the suspect seismic belt, we complete the identification of seismic belt; (5) the random and actual earthquakes trial calculation shows that the Delaunay triangulation method can realize a fast automatic identification of seismic belts; and (6) this automatic identification method may provide a research basis for earthquake prediction.