Engineered surfaces show anisotropic characteristics and their topography parameters are direction dependent. Statistical characterization of these surfaces is still complex because of directional nature of surfaces. In this work, an attempt is made to simulate anisotropic surfaces through use of topography parameters (3D surface parameters). Firstly, 3D anisotropic random Gaussian rough surface is generated numerically with fast Fourier transform (FFT). Generated anisotropic random Gaussian rough surface shows the typical statistical properties similar to ground and similarly directional anisotropic rough surfaces. Thomas and Sayles (1976) theoretical model for directional anisotropic rough surface is adopted here for calculating the summit parameters i.e. summit density, equivalent bandwidth parameter, mean summit curvature, equivalent surface moments. Summit parameters are calculated using equivalent spectral moment approach. For numerically generated anisotropic Gaussian rough surface, important spatial and hybrid properties are discussed in details. This work demonstrates the variation of spectral moments in both across and parallel to the lay directions with pattern ratio (gamma= ßx/ßy ). Correlation length (ßx) is fixed and correlation length (ßy) is varied from 100 to10 . Variation of summit parameters with pattern ratio is also discussed in details. Results shows that mean summit curvature and skewness of summit heights increases with increase in pattern ratio, whereas standard deviation of summit heights and equivalent bandwidth parameter (ae) decreases with pattern ratio. A significant difference is found in ‘Abbott’ parameters when calculated in both perpendicular and parallel to lay directions. Effect of these parameters on wear process is discussed in brief.