In this study, the data sourced from hyperspectral data of 96 tidal soil samples in Miyun, Tongzhou and Shunyi Districts of Beijing are processed and analyzed by means of continuous wavelet multiscale analysis technique. Firstly, the hyperspectral data are decomposed to generate wavelet coefficients and the correlation between the coefficients and soil organic matter content is analyzed, and the characteristic band is selected. Finally, the model to estimate soil organic matter content is constructed by using the characteristic band. The research results show that the estimation of soil organic matter by the reflectivity of soil spectrum is better than that of the traditional spectral transformation technology after continuous wavelet transformation. The ability of estimating soil organic matter by continuous wavelet decomposition decreases first and then increases with the reduction of spectral resolution. The results of continuous wavelet analysis can improve the ability to estimate the content of organic matter by the soil spectrum. Compared with the high spectral reflectivity of soil, the accuracy of soil organic content based on continuous wavelet is improved by 19%. Since the model accuracy is higher when built with the spectral resolution of 80 nm, its R2 reaches 0.632, which indicates that the wide band data can be used for the monitoring of soil organic matter content by using the continuous wavelet technique.