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

Wei Yan,Guiping Liu,Zirui Li,Xueze Wen,Changrong He

doi:10.1007/s42452-020-03886-6

Abstract

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.

Highlights

A big earthquake could kill thousands of people and trigger a tsunami
Li et al [14] systematically combed the seismic belts before 96 earthquakes by rescanning and showed that the ratio of belts before earthquakes of M5, M6 and M7 was 25%, 38% and 71%, respectively, which indicated that the belt image might be an important criterion for the occurrence of strong earthquakes of M7 or above to some extent
This paper presents a fast automatic identification method for seismic belts based on Delaunay triangulation

Summary

Introduction

A big earthquake could kill thousands of people (such as 2008 Wenchuan Mw7.9 Earthquake) and trigger a tsunami (such as 2011 East Japan Mw9.0 Earthquake). Since the 1950s, people have discovered some pre-earthquake anomalies that may be related to the occurrence of strong earthquakes such as seismic belt, seismic gap, seismic recurrence period, and so on [2,3,4,5,6,7,8,9,10,11,12,13,14]. Li et al [14] systematically combed the seismic belts before 96 earthquakes by rescanning and showed that the ratio of belts before earthquakes of M5, M6 and M7 was 25%, 38% and 71%, respectively, which indicated that the belt image might be an important criterion for the occurrence of strong earthquakes of M7 or above to some extent. Using the fastest computer at present to compute [16], it will take above 2.71 × 10276 years to complete This is the main reason that prevents seismic belts from being tested. This paper presents a fast automatic identification method for seismic belts based on Delaunay triangulation

The fast automatic identification method

Earthquake case

Conclusion and discussion

Findings

Compliance with ethical standards