URBAN SEISMIC AMBIENT NOISE ANALYSIS: INNOVATIONS AND APPLICATIONS

Seismic ambient noise generated by human activities provides an opportunity to monitor aboveground human activities without intruding on privacy. However, extracting specific signals from noisy seismic noise is challenging. Seismic ambient noise also contains information about the underground layers. The high-energy near-field traffic noise generated by direct loading of motor vehicles is rarely used for monitoring near-surface physical properties and needs to be analyzed. Distributed acoustic sensing (DAS) is a recently developed seismic sensor that allows for long-term, high-spatial resolution, and real-time monitoring at lower costs. However, traditional processing methods may not be reliable when applied to DAS ambient noise data. Resolving far-field ambient noise source propagation direction and surface wave contents from DAS ambient noise data is crucial to reconstructing a reliable near-surface shear-wave velocity model. This thesis addresses these issues and proposes new algorithms and methods for urban seismic ambient noise monitoring with traditional seismic sensors and DAS.

Author dc:creator

• ZHAO YUMIN

• seismic ambient noise, footstep signals, seismic attenuation, DAS ambient noise, beamforming, near-surface imaging