000004960 001__ 4960
000004960 005__ 20241203105543.0
000004960 0247_ $$2DOI$$a10.1029/2020GL089931
000004960 037__ $$aSCART-2020-0146
000004960 100__ $$aLindsey, N.J.
000004960 245__ $$aCity-scale dark fiber DAS measurements of infrastructure use during the COVID-19 pandemic
000004960 260__ $$c2020
000004960 520__ $$aThroughout the recent COVID-19 pandemic, real-time measurements about shifting use of roads, hospitals, grocery stores, and other public infrastructure became vital for government decision makers. Mobile phone locations are increasingly assimilated for this purpose, but an alternative, unexplored, natively anonymous, absolute method would be to use geophysical sensing to directly measure public infrastructure usage. In this paper, we demonstrate how fiber-optic distributed acoustic sensing (DAS) connected to a telecommunication cable beneath Palo Alto, CA, successfully monitored traffic over a 2-month period, including major reductions associated with COVID-19 response. Continuous DAS recordings of over 450,000 individual vehicles were analyzed using an automatic template-matching detection algorithm based on roadbed strain. In one commuter sector, we found a 50% decrease in vehicles immediately following the order, but near Stanford Hospital, the traffic persisted. The DAS measurements correlate with mobile phone locations and urban seismic noise levels, suggesting geophysics would complement future digital city sensing systems.
000004960 594__ $$aNO
000004960 700__ $$aYuan, S.
000004960 700__ $$aLellouch, A.
000004960 700__ $$aGualtieri, L.
000004960 700__ $$aLecocq, T.
000004960 700__ $$aBiondi, B.
000004960 773__ $$ce2020GL089931$$n16$$pGeophysical Research Letters$$v47$$y2020
000004960 85642 $$ahttps://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020GL089931
000004960 8560_ $$fthomas.lecocq@observatoire.be
000004960 8564_ $$s1154286$$uhttps://publi2-as.oma.be/record/4960/files/grl61048-fig-0002-m.jpg$$yVehicle observations from Stanford DAS-2 Experiment. (a) Example of DAS recordings bandpassed around 3–30 Hz showing vehicle surface waves and contrasting background energy between Stanford Hospital and Sand Hill Road sections. (b) Same as (a) but bandpassed around 0.1–1 Hz to highlight the high quality geodetic strain responses of the roadbed due to vehicle loading. Individual vehicles are numbered. (c) Continuous wavelet transform applied to spatial axis of unfiltered data shown in (a) and (b) highlighting dominant frequencies of different array segments. (d) Example processed strain data from DAS channel at 3.4 km, bandpass filtered as in (b) in gray, with a model of the horizontal strain for three vehicles passing the fiber on the southbound side of the road (black line), and three STA/LTA detections (red lines) for vehicles #5, #8, #10 shown in (b). A matched template algorithm was then applied using the median of approximately 200 detected vehicle signals and scanning over the full daily time series for the DAS channel
000004960 8564_ $$s12102$$uhttps://publi2-as.oma.be/record/4960/files/grl61048-fig-0002-m.jpg?subformat=icon-180$$xicon-180$$yVehicle observations from Stanford DAS-2 Experiment. (a) Example of DAS recordings bandpassed around 3–30 Hz showing vehicle surface waves and contrasting background energy between Stanford Hospital and Sand Hill Road sections. (b) Same as (a) but bandpassed around 0.1–1 Hz to highlight the high quality geodetic strain responses of the roadbed due to vehicle loading. Individual vehicles are numbered. (c) Continuous wavelet transform applied to spatial axis of unfiltered data shown in (a) and (b) highlighting dominant frequencies of different array segments. (d) Example processed strain data from DAS channel at 3.4 km, bandpass filtered as in (b) in gray, with a model of the horizontal strain for three vehicles passing the fiber on the southbound side of the road (black line), and three STA/LTA detections (red lines) for vehicles #5, #8, #10 shown in (b). A matched template algorithm was then applied using the median of approximately 200 detected vehicle signals and scanning over the full daily time series for the DAS channel
000004960 8564_ $$s14879$$uhttps://publi2-as.oma.be/record/4960/files/grl61048-fig-0002-m.gif?subformat=icon$$xicon$$yVehicle observations from Stanford DAS-2 Experiment. (a) Example of DAS recordings bandpassed around 3–30 Hz showing vehicle surface waves and contrasting background energy between Stanford Hospital and Sand Hill Road sections. (b) Same as (a) but bandpassed around 0.1–1 Hz to highlight the high quality geodetic strain responses of the roadbed due to vehicle loading. Individual vehicles are numbered. (c) Continuous wavelet transform applied to spatial axis of unfiltered data shown in (a) and (b) highlighting dominant frequencies of different array segments. (d) Example processed strain data from DAS channel at 3.4 km, bandpass filtered as in (b) in gray, with a model of the horizontal strain for three vehicles passing the fiber on the southbound side of the road (black line), and three STA/LTA detections (red lines) for vehicles #5, #8, #10 shown in (b). A matched template algorithm was then applied using the median of approximately 200 detected vehicle signals and scanning over the full daily time series for the DAS channel
000004960 905__ $$apublished in
000004960 980__ $$aREFERD