We apply the spatial autocorrelation (SPAC) method to construct the 3D subsurface shear‐wave velocity structure model using the short‐period dense seismic array (containing 725 nodal geophones) located at the Guangdong–Hong Kong–Macao Greater Bay area (GBA). We first divided the dense array into numerous subarrays, with each subarray consisting of nine nodal geophones, and obtained 562 subarrays that can provide 1D VS profiles of the same quantity. Then, the SPAC method and genetic algorithm are utilized to extract the dispersion curve of the Rayleigh wave from the raw microtremor data and invert VS structure, respectively. Finally, a 3D VS structure model from the surface to 3.3 km depth is derived by combining all 1D VS structures. Relatively low‐velocity anomalies above 700 m are considered unconsolidated shallow sediments as well as relatively high‐velocity anomalies beneath 1100 m are attributed to consolidated granite bedrock. Meanwhile, low‐velocity anomalies that are identified through the vertical VS profile at a depth of about 900–3000 m can be contributed to the fractured zone, and striped low‐velocity anomalies in the horizontal VS maps reveal the location of the deeply buried faults in the study area. The results also mean that the SPAC method combined with the records of short‐period dense seismic array can be effectively applied to image subsurface structures in high‐populated urban area. The development of this noise‐resistance and environment‐friendly geophysical technique provides a reliable and effective way to explore the complicated subsurface geological structures, which is of great significance to urban engineering construction and earthquake disaster reduction work in densely populated urban agglomerations.

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