Entropy of GPS-measured Earth tremor

Abstract

Modern GPS networks make it possible to study the tremors of the earth’s surface from the point of view of identifying anomalous areas. The use of the entropy of the distribution of wavelet coefficients provides a tool for highlighting the hidden and non-obvious properties of the earth’s surface tremors. The principal component method makes it possible to identify the most important general trends in the behavior of informative tremor statistics and determine areas of anomalous behavior. The application of these methods to the analysis of GPS data in California is presented. Particular attention is paid to time intervals and areas (clusters) with extreme entropy values. Periodicities in the occurrence of strong jumps in the average entropy of the entire region have been discovered, of which the period of 95 days is dominant. The trend of migration of areas of maximum entropy from the South to the North has been identified. As a result of the analysis, it was found that the area of minimum entropy values gravitates toward the San Andreas fault, and the vicinity of San Francisco has the selected properties of maximum information content and attracts low entropy trajectories.