Discussion and Conclusions
While a general noise reduction was discovered in many cities by previous studies (Xiao et al., 2020; Poli et al., 2020; Lecocq et al., 2020; Dias et al., 2020; Yabe et al., 2020), our results reveal many new and detailed features of seismic noise caused by progressive COVID-19 measures.
First, we find the seismic noise reduction in broad frequency bands (0.01–100 Hz) caused by decreased human activities during the period of stay-at-home (March-April 2020). After Phase Yellow (May-June 2020), the seismic noise recovers slightly in high-frequency bands (10–100 Hz), while the noise in 1–10 Hz shows no recovery until late Phase Green. We interpret that after the relaxation of restrictions, residents voluntarily followed the stay-at-home guidelines (i.e., less pedestrian movement) while road traffic and industrial activities started to recover. These results show that the dense DAS array in urban areas could sense slight changes due to the gradual lifting of restrictions since the end of May. Noise changes caused by particular human activities (e.g. pedestrian movements and industrial activities) can also be identified in different frequency bands. The sensitivity of the DAS array indicates the possibility of using seismic noise variation from telecom DAS in the city-block scale to evaluate local response to social restrictions.
Second, seismic noise in the low frequency band (0.01–1 Hz, where anthropogenic noise is weaker) is also impacted by the COVID-19 measures, which was not reported in previous studies using seismic networks (Xiao et al., 2020; Lecoq et al., 2020; Poli et al., 2020). Lindsey et al. (2020) observed a reduction in the very-low-frequency seismic noise (0.01–1 Hz) using fiber sensors along a major road in Stanford, CA, during the COVID-19 pandemic. This reduction is likely to be the geodetic response of the roadbed to decreased vehicle loading (Lindsey et al., 2020; Jousset et al., 2018), providing an additional constraint to quantify the number of passing vehicles using dense seismic noise data.
Third, the meter scale human activity variation is hard to be obtained from either sparse seismic stations or mobility data due to incomplete data acquisition, location accuracy, and privacy issues. In contrast, DAS could provide a high spatial resolution map of seismic noise variation, which can distinguish different human activity variation patterns between the main campus and agricultural area, and further identify dominant noise sources on different streets within each area. For instance, the significant noise reduction, almost 90% in the frequency band 1-50 Hz, on the main campus is attributed to few local concentrated human activities (including footsteps and road traffic) due to the required stay-at-home order in State College PA. Seismic noise in less busy areas (AG areas) remains relatively stable. In the local noise reduction zone (main campus), we could distinguish footsteps, single passing vehicles, and high-frequency industrial noise associated with construction activities (Figure 3). The spatial noise variation provides detailed information on population mobility dynamic in urban areas, demonstrating that the lockdown measurements have a significant impact on certain populated areas (e.g., universities) during the COVID-19 pandemic.
Finally, a linear correlation between mobility change and seismic noise change implies that high-resolution DAS seismic noise data could further serve as an additional and innovative approach for evaluating the impact of the COVID-19 measures in populated areas related to industrial, educational, and other activities. DAS data contain non-personalized information and enable urban monitoring use patterns, which protects the privacy of individuals compared to cell phone location-tracking data (Lindsey and Martin, 2021). This suggests the benefits of using city infrastructure fiber-optic cables over the mobility data to monitor and quantify human activity in a city (e.g., estimation of people’s movement and the number of vehicles) with high spatiotemporal resolution.
In summary, our results show key connections between the progressive COVID-19 measures and spatiotemporal seismic noise changes using a dense fiber array at the city scale, which helps estimate whether and how communities respond to county-level policies. Our research shows that seismic noise recorded by infrastructure DAS fiber networks could potentially help policymakers to evaluate the compliance of the population following state-mandated mobility restrictions, which in-turn could optimize the restriction policies in the future pandemic. Looking forward, fiber-optic arrays using existing telecommunication fiber networks make seismic monitoring more cost-effective and practical than other types of seismic sensors in urban areas.