The Hilbert spectral analysis based on the Empirical Mode Decomposition (EMD) method for analyzing nonlinear and non stationary data is introduced and applied to the analysis of the Atmospheric Boundary Layer (ABL) turbulent signals for the first time. The effectiveness of Hilbert the spectral analysis in the research on the ABL turbulence is explored. The energy distribution characteristics and the degree of statistic stationarity of the turbulent data above the urban and forest canopies are studied. The results show the Hilbert spectral analysis is powerful and effective in the study of ABL turbulence. The Hilbert marginal spectrum is effective to get the energy distribution characteristics of ABL turbulent signals, and the analysis of the statistic stationarity is also effective to quantitatively measure the stationarity of the ABL turbulent signals. This will help establish the appropriate data quality control methods and improve the calculation of diffusion parameters of air quality and dispersion models. The case analysis shows that the turbulent flow is well mixed above both canopies. Compared with the urban canopy, the turbulent energy above the forest canopy is more concentrated in the eddies on larger scales, and the high frequency part of wind disturbance is dominated by stronger intermittency. At a given height, turbulence eddies above the forest canopy are more unstable and contain less energy than those above the urban canopy.