Acquiring empirical Green's functions with a real and high signal-to-noise ratio serves as a prerequisite for deriving surface wave dispersion and inverting underground structures.However,the distribution of actual noise sources differs from the theory,and the energy and quantity of noise sources are limited in the high-altitude areas.Acquiring empirical Green’s functions with a high signal-to-noise ratio is challenging,apart from a prolonged data acquisition period required.Given these,this study presented a method for screening ambient noise data based on power spectral density.Using this method,this study screened 92-hour ambient noise data from a high-altitude area.Consequently,this method significantly reduced the calculation time of cross-correlation,effectively extracted surface waves with a high signal-to-noise ratio,reduced the interference waves with high apparent velocities,and obtained a high-resolution shallow shear wave velocity structure of shallow parts with burial depths ranging from 0~140 m.This study provides a novel method for challenging,short-term exploration of water conservancy and hydropower generation in high-altitude areas.