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Table 1 Review of pavement texture research methods

From: 2D-wavelet based micro and macro texture analysis for asphalt pavement under snow or ice condition

Method/Equipment Description Measuring parameters Characteristics
Sand patch method Spread sand with a volume of 25 cm3 on the measuring point to form a uniform circle and measure the diameter of the circle. The result is the volume of the sand divided by the spread area. Mean Texture Depth (MTD) The method is simple but with large error, and is not suitable for large sample detection.
The 1-kHz laser scanner The scanner is capable of measuring texture with wavelength as low as 0.03 mm. Mean Profile Depth (MPD), Root Mean Square (RMS) This equipment can be used to evaluate both macro and micro textures. Besides, it allows users to produce repeatable texture parameters and to capture the detailed surface features.
HandySCAN 300 The device provides resolutions as clear as 0.100 mm, and precision as high as 0.040 mm. The coordinates of the 3D data of surface point cloud High adaptability, high precision, after obtaining the point cloud data, the 3D model can be reconstructed by software.
Close range (stereoscopic) photogrammetry or microscopic measurement Based on images captured by a camera or microscope, proprietary software is used to model and analyze them in three dimensions. Mean Texture Depth (MTD), spectral indicators the visualization of 3D terrain, Overlay micro texture, macro texture and coarse texture.
VR-3000 (this paper) This paper aims to implement a two-dimensional discrete wavelet transform to decompose pavement surface texture at micro and macro scales. Mean Texture Depth (MTD), Normalized Energy (NE) Compared with MTD values, the NE values have the advantages of full coverage, full automation and wide analytical scale.