S41A-2699
Shallow Subsurface Velocity Estimation Using Traffic Noise at Long Beach, CA

Thursday, 17 December 2015
Poster Hall (Moscone South)
Jason P Chang, Stanford University, Stanford, CA, United States
Abstract:
We demonstrate the effectiveness of using traffic noise for shallow subsurface imaging using a dense seismic array in Long Beach, California. Spectral analysis indicates that traffic-induced vibrations dominate the ambient seismic noise field at frequencies between 3 and 15 Hz. Using the ambient-noise cross-correlation technique, we extract fundamental and first-order Rayleigh waves generated by Interstate 405 and local roads. After accounting for the local noise source distribution, we pick group travel times associated with the fundamental mode and use them in a straight-ray tomography procedure to generate group velocity maps at 3.0 Hz and 3.5 Hz. The velocity trends in our results correspond to shallow depths and are consistent with lithologies outlined in a geologic map of the survey area. The most prominent features resolved in our velocity maps are the low velocities to the north corresponding to less-consolidated materials, high velocities to the south corresponding to more-consolidated materials, a low-velocity zone corresponding to artificial fill in Alamitos Bay, and a low-velocity linear feature in the Newport-Inglewood Fault zone. Our results have important applications for research investigations concerned with the shallow subsurface, such as geohazard mapping.