City-scale dark fiber DAS measurements of infrastructure use during the COVID-19 pandemic
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Abstract (arXiv)
Throughout the recent COVID-19 pandemic when government officials around the world ordered citizens to quarantine inside their homes, real-time measurements about the use of roads, hospitals, grocery stores, and other public infrastructure became vital to accurately forecast viral infection rates and inform future government decisions. Although mobile phone locations provide some information about community-level activity, dense distributed geophysical sensing of ground motions across a city are more complete and also natively anonymous. In this paper, we demonstrate how fiber-optic Distributed Acoustic Sensing (DAS) connected to a telecommunication cable beneath Palo Alto, CA captured seismic and geodetic signals produced by vehicles during the COVID-19 pandemic outbreak and subsequent quarantine. We utilize DAS strain measurements of roadbed deformation caused by local cars and trucks in an automatic template matching detection algorithm to count the number of vehicles traveling per day over a two-month period around the timing of the San Francisco Bay Area shelter-in-place order. Using a segment of the optical fiber near a major grocery store on Sand Hill Road we find a 50% decrease in vehicle count immediately following the order, but data from near Stanford Hospital showed a far more subtle change due to on-going hospital activities. We compare the information derived from DAS measurements to other quarantine response metrics and find a strong correlation with the relative changes reported by Google and Apple using mobile phone data.
Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). First posted on arXiv 11 May 2020.
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Citing papers per year: 2024: 2; 2025: 0; 2026: 1.
3 papers.
- 2024Self-Updating Vehicle Monitoring Framework Employing Distributed Acoustic Sensing towards Real-World Settingscited by 0
- 2024Training a Distributed Acoustic Sensing Traffic Monitoring Network With Video Inputscited by 0
- 2026Monitoring Urban Traffic Dynamics at Fine Spatiotemporal Resolution Using Distributed Acoustic Sensing and Deep Learningcited by 0
- 2026Monitoring Urban Traffic Dynamics at Fine Spatiotemporal Resolution Using Distributed Acoustic Sensing and Deep Learning23 Sep 2026
- 2024Training a Distributed Acoustic Sensing Traffic Monitoring Network With Video Inputs17 Dec 2024
- 2024Self-Updating Vehicle Monitoring Framework Employing Distributed Acoustic Sensing towards Real-World Settings16 Sep 2024