Open AccessImpacts of Sample Size on Calculation of Pavement Texture Indicators with 1mm 3D Surface Data
Author(s) -
Lin Li,
Kelvin C.P. Wang,
Qiang Li,
Wenting Luo,
Jinqiu Guo
Publication year - 2017
Publication title -
periodica polytechnica. transportation engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.388
H-Index - 15
eISSN - 1587-3811
pISSN - 0303-7800
DOI - 10.3311/pptr.9587
Subject(s) - sample (material) , sample size determination , texture (cosmology) , linear regression , data collection , statistics , surface finish , variance (accounting) , environmental science , mathematics , computer science , engineering , artificial intelligence , chemistry , accounting , chromatography , business , image (mathematics) , mechanical engineering
The emerging 1mm resolution 3D data collection technology is capable of covering the entire pavement surface, and provides more data sets than traditional line-of-sight data collection systems. As a result, quantifying the impact of sample size including sample width and sample length on the calculation of pavement texture indicators is becoming possible. In this study, 1mm 3D texture data are collected and processed at seven test sites using the PaveVision3D Ultra system. Analysis of Variance (ANOVA) test and linear regression models are developed to investigate various sample length and width on the calculation of three widely used texture indicators: Mean Profile Depth (MPD), Mean Texture Depth (MTD) and Power Spectra Density (PSD). Since the current ASTM standards and other procedures cannot be directly applied to 3D surface for production due to a lack of definitions, the results from this research are beneficial in the process to standardize texture indicators’ computations with 1mm 3D surface data of pavements.