Near-surface imaging from traffic-induced surface waves with dense linear arrays: An application in the urban area of Hangzhou, China

Abstract

Accurate understanding of near-surface structures of the solid earth is challenging, especially in urban areas where active source seismic surveys are constrained and difficult to perform. The analysis of anthropogenic seismic noise provides an alternative way to image the shallow subsurface in urban environments. We have developed an application of using traffic noise with seismic interferometry to investigate near-surface structures in Hangzhou City, Eastern China. Noise data were recorded by dense linear arrays with approximately 5 m spacing deployed along two crossing roads. We analyze the characteristics of traffic-induced noise using 36 h continuous recordings. Coherent Rayleigh surface waves between 2 and 20 Hz are retrieved based on crosscorrelations within 1 h time windows. Robust phase-velocity dispersion curves are extracted from virtual shot gathers using multichannel analysis of surface waves and coincide with the results from active seismic data, noise beamforming analysis, and measurements with the spatial autocorrelation method. S-wave velocity profiles are derived for the top 100 m of the subsurface at the array locations. The estimated S-wave velocities from traffic noise correspond to the velocities estimated from logging data. The 2D S-wave velocity maps reveal different soil deposits and bedrock structures in the estuarine sedimentary area. The results demonstrate the accuracy and efficiency of delineating near-surface structures from traffic-induced noise, which has great potential for monitoring subsurface changes in urban areas.