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Urban sensing using existing fiber-optic networks

Author

Listed:
  • Jingxiao Liu

    (Massachusetts Institute of Technology)

  • Haipeng Li

    (Stanford University)

  • Hae Young Noh

    (Stanford University)

  • Paolo Santi

    (Massachusetts Institute of Technology
    Istituto di Informatica e Telematica del CNR)

  • Biondo Biondi

    (Stanford University)

  • Carlo Ratti

    (Massachusetts Institute of Technology
    Politecnico di Milano)

Abstract

The analysis of urban seismic signals offers valuable insights into urban environments and society. Yet, accurate detection and localization of seismic sources on a city-wide scale with conventional seismographic network is unavailable due to the prohibitive costs of ultra-dense seismic arrays required for imaging high-frequency anthropogenic sources. Here, we leverage existing fiber-optic networks as a distributed acoustic sensing system to accurately locate urban seismic sources and estimate how their intensity varies over time. By repurposing a 50-kilometer telecommunication fiber into an ultra-dense seismic array, we generate spatiotemporal maps of seismic source power (SSP) across San Jose, California. Our approach overcomes the proximity limitations of urban seismic sensing, enabling accurate localization of remote seismic sources generated by urban activities, such as traffic, construction, and school operations. We also show strong correlations between SSP values and environmental noise levels, as well as various persistent urban features, including land use patterns and demographics.

Suggested Citation

  • Jingxiao Liu & Haipeng Li & Hae Young Noh & Paolo Santi & Biondo Biondi & Carlo Ratti, 2025. "Urban sensing using existing fiber-optic networks," Nature Communications, Nature, vol. 16(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-57997-y
    DOI: 10.1038/s41467-025-57997-y
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    References listed on IDEAS

    as
    1. Guillermo Rey Gozalo & Enrique Suárez & Alexandra L. Montenegro & Jorge P. Arenas & Juan Miguel Barrigón Morillas & David Montes González, 2020. "Noise Estimation Using Road and Urban Features," Sustainability, MDPI, vol. 12(21), pages 1-18, November.
    2. Charles Raux & Tai-Yu Ma & Eric Cornelis, 2016. "Variability in daily activity-travel patterns: the case of a one-week travel diary," Post-Print halshs-01389479, HAL.
    3. Jiaxuan Li & Taeho Kim & Nadia Lapusta & Ettore Biondi & Zhongwen Zhan, 2023. "The break of earthquake asperities imaged by distributed acoustic sensing," Nature, Nature, vol. 620(7975), pages 800-806, August.
    4. Rositsa T. Ilieva & Timon McPhearson, 2018. "Social-media data for urban sustainability," Nature Sustainability, Nature, vol. 1(10), pages 553-565, October.
    5. Emmanouil Tranos & Peter Nijkamp, 2015. "Mobile phone usage in complex urban systems: a space–time, aggregated human activity study," Journal of Geographical Systems, Springer, vol. 17(2), pages 157-185, April.
    6. Jingxiao Liu & Haipeng Li & Hae Young Noh & Paolo Santi & Biondo Biondi & Carlo Ratti, 2025. "Urban sensing using existing fiber-optic networks," Nature Communications, Nature, vol. 16(1), pages 1-10, December.
    7. Susu Xu & Joshua Dimasaka & David J. Wald & Hae Young Noh, 2022. "Seismic multi-hazard and impact estimation via causal inference from satellite imagery," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
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    1. Jingxiao Liu & Haipeng Li & Hae Young Noh & Paolo Santi & Biondo Biondi & Carlo Ratti, 2025. "Urban sensing using existing fiber-optic networks," Nature Communications, Nature, vol. 16(1), pages 1-10, December.

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