To improve our understanding of the long-term behavior of low-frequency earthquakes (LFEs) along the tremor belt of the Nankai subduction zone, we applied a matched filter technique to continuous seismic data recorded by a dense and highly sensitive seismic network over an 11 year window, April 2004 to August 2015. We detected a total of ~510,000 LFEs, or ~23× the number of LFEs in the JMA catalog for the same period. During long-term slow slip events (SSEs) in the Bungo Channel, a series of migrating LFE bursts intermittently occurred along the fault-strike direction, with slow hypocenter propagation. Elastic energy released by long-term SSEs appears to control the extent of LFE activity. We identify slowly migrating fronts of LFEs during major episodic tremor and slip (ETS) events, which extend over distances of up to 100 km and follow diffusion-like patterns of spatial evolution with a diffusion coefficient of ~10 4 m 2 /s. This migration pattern closely matches the spatio-temporal evolution of tectonic tremors reported by previous studies. At shorter distances, up to 15 km, we discovered rapid diffusion-like migration of LFEs with a coefficient of ~10 5 m 2 /s. We also recognize that rapid migration of LFEs occurred intermittently in many streaks during major ETS episodes. These observations suggest that slow slip transients contain a multitude of smaller, temporally clustered fault slip events whose evolution is controlled by a diffusional process.

Enormous volumes of continuous seismic data have been acquired from seismograph networks over the past decade, with these data sets consisting of observations from multiple seismic stations. Dense seismograph networks, such as the Japanese Metropolitan Seismic Observation network (MeSO-net) and the Southern California Seismic Network, monitor real-time seismicity and provide continuous waveforms from their respective network stations. Efficient and thorough analyses of these data sets should be of great benefit to seismology. The main objective of the present work, which represents a novel approach to and advance in seismic data analysis, is the development of an improved earthquake detection technique for these massive seismic network data sets.In recent years, deep neural networks have been attracting increasing interest as tools for analyzing such complex big data in many applied fields such as image processing (

The 2019 {\text{M}}_{\text{j}} 6.7 Yamagata-Oki Earthquake occurred adjacent to the northeastern edge of the source region of the 1964 {\text{M}}_{\text{j}} 7.5 Niigata Earthquake, offshore of Yamagata Prefecture, Japan. Few aftershocks occurred in the source region of the Yamagata-Oki earthquake immediately following the Niigata earthquake, and the recent seismicity rate in this region is extremely low compared with that of the surrounding region. This spatial variation in seismicity may allow us to elucidate plausible physical processes that shape the spatiotemporal evolution of these shallow-crustal environments. Here, we investigate the spatial variations in seismicity characteristics by applying the HIerarchical Space–Time Epidemic Type Aftershock Sequence (HIST-ETAS) model to an earthquake catalog compiled by the Japan Meteorological Agency for events in and around the Yamagata-Oki earthquake rupture region. We compare spatial variations in the background seismicity rate and aftershock productivity estimated from the HIST-ETAS model with the geophysical features in the study region. The background seismicity rate is high along the eastern margin of the Sea of Japan and correlates well with a previously identified zone that possesses a high geodetic shear strain rate. The two major earthquakes occurred in and around an active shear zone, suggesting that the background seismicity rate may serve as a key parameter for evaluating seismic hazard across the Japanese Archipelago. Furthermore, the source region of the Yamagata-Oki earthquake has a higher aftershock productivity, lower b-value, and lower seismic-wave velocity than that of the Niigata earthquake. We interpret this low-velocity zone to be a well-developed damaged rock that resulted in both a reduction in the b-value and an increase in aftershock productivity based on previous laboratory experiments and numerical results; this damage makes the rock more ductile at the macroscopic scale. The higher ductility in the source region of the Yamagata-Oki earthquake may have worked as a soft barrier against the propagation of dynamic rupture that occurred during the Niigata earthquake.

The 2019 Mj 6.7 Yamagata-Oki earthquake occurred adjacent to the northeastern edge of the source region of the 1964 Mj 7.5 Niigata earthquake, offshore of Yamagata Prefecture, Japan. Few aftershocks occurred in the source region of the Yamagata-Oki earthquake immediately following the Niigata earthquake, and the recent seismicity rate in this region is low compared with the source region of the Niigata earthquake. This spatial variation in seismicity may allow us to elucidate plausible physical processes that shape the spatiotemporal evolution of these shallow-crustal environments. Here, we investigate the spatial variations in seismicity characteristics by applying the HIerarchical Space–Time Epidemic Type Aftershock Sequence (HIST-ETAS) model to an earthquake catalog compiled by the Japan Meteorological Agency for events in and around the Yamagata-Oki earthquake rupture region. We compare spatial variations in the background seismicity rate and aftershock productivity estimated from the HIST-ETAS model with the geophysical features in the study region. The background seismicity rate is high along the eastern margin of the Sea of Japan and correlates well with a previously identified zone that possesses a high geodetic E-W strain rate. The two major earthquakes occurred in and around a high E-W strain rate zone, suggesting that the background seismicity rate may serve as a key parameter for evaluating seismic hazard across the Japanese Archipelago. Furthermore, the source region of the Yamagata-Oki earthquake has a higher aftershock productivity and lower seismic-wave velocity than that of the Niigata earthquake. We interpret this low-velocity zone to be a well-developed damaged rock that resulted in an increase in aftershock productivity based on previous laboratory experiments and numerical results; this damage makes the rock more ductile at the macroscopic scale. The higher ductility in the source region of the Yamagata-Oki earthquake may have worked as a barrier against the propagation of dynamic rupture that occurred during the Niigata earthquake.

To improve our understanding of the long-term behavior of low-frequency earthquakes (LFEs) along the tremor belt of the Nankai subduction zone, we applied a matched filter technique to continuous seismic data recorded by a dense and highly sensitive seismic network over an 11year window, April 2004 to August 2015. We detected a total of ~510,000 LFEs, or ~23× the number of LFEs in the JMA catalog for the same period. During long-term slow slip events (SSEs) in the Bungo Channel, a series of migrating LFEbursts intermittently occurred along the fault-strike direction, with slow hypocenter propagation. Elastic energy released by long-term SSEs appears to control the extent of LFE activity. We identify slowlymigrating fronts of LFEs during major episodic tremor and slip (ETS)events, which extend over distances of up to 100 km and follow diffusion-like patterns of spatial evolution with a diffusion coefficient of ~104 m2/s. This migration pattern closely matches the spatio-temporal evolution of tectonictremors reported by previous studies. At shorter distances, up to 15 km, we discovered rapid diffusion-like migrationof LFEs with a coefficient of ~105 m2/s. We also recognize that rapid migration of LFEs occurred intermittently in many streaks during major ETS episodes. These observations suggest that slow slip transients contain a multitude of smaller, temporally clustered fault slip events whose evolution is controlled by a diffusional process.