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.