Potential for crustal deformation monitoring using a dense cell phone carrier Global Navigation Satellite System network

Monitoring of crustal deformation provides essential information for seismology and volcanology. For such earth science fields and other purposes, various Global Navigation Satellite System (GNSS) networks have been constructed at the national and regional levels. In Japan, the continuous nationwide GNSS network, the GNSS Earth Observation Network System (GEONET), is operated by the Geospatial Information Authority ofJapan. Although GEONET has made a substantial contribution to earth science research, the large spacing of GEONET sites makes it difficult to accurately understand crustal deformation phenomena in some cases. However, cell phone carriers in Japan have constructed independent GNSS networks to improve their positioning services in recent years. In this study, we examine the performance of a GNSS network operated by SoftBank Corp. for crustal deformation monitoring. The network has more than 3300 sites throughout Japan, which is approximately 2.5 times the number of the GEONET sites. To assess the quality of SoftBank's GNSS data, we first analyzed data from Miyagi Prefecture and evaluated the stability of the coordinate time series for nine consecutive days during a quiet (interseismic) period. The calculated standard deviations were approximately the same for both networks. Furthermore, we calculated the displacement between September 2020 and March 2021. The results reveal that almost all SoftBank sites showed a consistent displacement with their surrounding GEONET sites. Next, we analyzed the coseismic deformation associated with the off-Fukushima earthquake (MJMA 7.3) on February 13, 2021, in both static and kinematic modes. We obtained a westward coherent displacement along the coastline in both networks, although several outliers were observed for the SoftBank sites. Based on these initial assessments, we conclude that these private sector GNSS sites are useful for crustal deformation monitoring with appropriate data quality control