Pavement surface texture is essential in wearing courses, being directly linked to their functional properties. Its regular assessment is crucial for an effective pavement management. This study investigates the relationships between profile's spatial wavelengths and physical properties of surfaces, evaluated through diffused empirical tests and indicators (MTD, PTV and GN). A novel Close-Range Photogrammetry (CRP) technique was applied for capturing the surface morphology of both laboratory-compacted and road pavement surfaces. Spectral analysis was performed to decompose the pavement texture into several distinct wavelengths, and the empirical test results were correlated through the specific wavelength sub-regions. The study identified a strong relationship between MTD and wavelengths in the coarse and medium macro-texture regions (R-2 > 0.8), while PTV and GN were more sensitive to the fine macro-texture and micro-texture regions. These findings highlight that spectral analysis complements the use of empirical tests, mitigating potential inaccuracies, while improving the surface evaluation process.
