Noise classification for the unified earthquake catalog using ensemble learning: the enhanced image of seismic activity along the Japan Trench by the S-net seafloor network

Earth, Planets and Space

Fuyuki Hirose¹  Koji Tamaribuchi¹  Akemi Noda¹  Yuriko Iwasaki²  Hiroshi Ueno³  Kazuhiro Iwakiri³ 

[1] Meteorological Research Institute, 1-1 Nagamine, 305-0052, Tsukuba, Ibaraki, Japan;Osaka Regional Headquarters, Japan Meteorological Agency, 4-1-76, Otemae, Chuo-ku, 540-0008, Osaka, Japan;Seismology and Volcanology Department, Japan Meteorological Agency, 3-6-9 Toranomon, Minato-ku, 105-8431, Tokyo, Japan;

关键词: Automatic hypocenter determination;    Completeness magnitude;    JMA unified seismic catalog;    Machine learning;    Japan Trench;   

DOI  :  10.1186/s40623-021-01411-6

来源: Springer

【 摘 要 】

Homogeneous and accurate hypocenter distribution along the Japan Trench is important to better understand the process of plate subduction and the occurrence mode of large earthquakes. The seafloor seismic network (S-net) deployed recently along the Japan Trench has revealed new seismic activity including shallow slow earthquakes. However, conventional microseismic observations, such as those reported in the Japan Meteorological Agency (JMA) unified earthquake catalog, have been limited to land-based stations. Thus, steady seismic activity occurring at the shallow plate boundary, which is far from land is not always recorded. In the present study, we construct an automatic earthquake catalog using the nationwide observation network, including S-net. Because false detections caused by noise account for about 5% of automatically determined hypocenters, we attempted to reduce false detections using ensemble learning methods such as random forest and AdaBoost. First, we created a training dataset of earthquakes and noise by visual inspection based on the data recorded in the automatically determined catalog over a 2-month period, and we trained the dataset using the hypocenter and phase data as input. As a result of the training, AdaBoost was able to reduce the noise to about one-fifth of the total false detections, which is equivalent to 1%, while keeping the number of hypocenters above 99%. This method will contribute to significantly improving the efficiency of seismic activity monitoring and cataloging. In addition, the automatic denoised catalog data revealed that from January to August 2020, the completeness magnitude was M 1.6 along the Japan Trench. These microearthquakes were concentrated at depths of 20–50 km around the upper surface of the subducting Pacific Plate and are complementary to the slow earthquakes occurring at 10–20-km depths. Exceptionally, microearthquakes were observed off Iwate and Ibaraki prefectures, which correspond in location to areas of clustered foreshock activity. This spatial heterogeneity in microseismic activity is similar to the spatial complementary between the coseismic slip and afterslip of the 2011 Tohoku earthquake, which may be related to differences in interplate frictional properties and stress changes in the surrounding crust.

【 授权许可】

CC BY