Identification of noise sources associated with human
activities
Predominant anthropogenic noise sources vary in different city sectors,
among workplaces (Ch 1240–1440), main roads (Ch 850–1110), a
residential area (Ch 690–830) and a less populated area (Ch 110–300)
(Figure 1b and 2). Characterizing seismic noise from particular sources
can help us understand local social interactions with city lockdown
measures. Our 5-km-long dense DAS array at 2 m spacing covers plenty of
public infrastructures. Hence, we chose specific subarrays and
identified noise sources – footstep signals, passing vehicles and
industrial noise, by comparing seismic noise variations before and after
the COVID-19 restrictions.
To analyze the impact of lockdown measures on footsteps, we selected
1-hour data (local time 10 am–11 am) from a subarray beneath a
pedestrian-only path on the main campus for similar days (March 5, April
16, and June 4) (Figure 3). Intuitively, walking footstep signals showed
up in the data as linear streaks with a slow moveout (1–2 m/s). On
March 5, during the regular semester, the DAS array picked up many
walking signals (plenty of data streaks in Figure 3a). Contrarily on
April 16, after the stay-at-home order was issued, only a few signals
are detected on this path (Figure 3b). In Phase Green (June 4), the
footstep signals are almost not recovered despite the easing of some
restriction measures. This invariability is confirmed by the average
spectrum plot in Figure 3d, showing the absence of peaks at 2 Hz and 4
Hz in both April 16 and June 4 curves, which are considered as the
footstep signals (Zhu et al., 2021).
We next analyzed traffic noise recordings (Figures 3e-h) from a subarray
beneath Curtin Road, the main road on campus. There is a significant
decrease in passing vehicles when comparing data between March 5 and
April 16. This is due to the shutdown of the university preventing
people from traveling to campus. The bus service was also reduced. On
June 4, more linear signals indicate more passing vehicles. The
decrease-increase traffic noise pattern is obviously different from the
loss-to-flat pattern of pedestrian movement. This trend is also
confirmed in the frequency spectrum (Figure 3h): a significant drop of
the power spectra between 10 and 50 Hz about 20 dB, then an increase by
5 dB. We interpreted 10–50 Hz as the frequency band of passing
vehicles.
In addition, we identified higher frequency noise associated with
construction activities. On the western campus, a new parking garage and
utility upgrades near the fibers were planned to be constructed from
December 17, 2019, to April 20, 2021. Due to the suspension of the
industrial activity during the stay-at-home measures, the data on April
15 show no detected events (Figure 3i). After restarting industrial
activities since May 7 (Phase Yellow), we observe strong industrial
noise on June 1 in Figure 3j. The noise in the frequency band of 10–30
Hz could be identified as noise from construction vehicles and the
broadband impulses (10–100 Hz) between 11:09 – 11:10 am were from
machinery, which produced short bursts of vibrations.