Pavement Macrotexture Parameters: Data, Supplementary Materials, and Code for Parameter Computation

Published: 9 July 2025| Version 1 | DOI: 10.17632/2xmw2t23z7.1
Contributors:
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Description

This data repository accompanies a study focused on the quantification and characterization of 86 scale-dependent spatial macrotexture parameters of pavement surfaces. Its primary purpose is to promote transparency and reproducibility while enabling researchers to replicate, enhance, or extend the work conducted by Dr. Sabillon-Orellana. The ZIP folder includes the following files: • Readme.txt: A brief guide to understanding the two Excel files used in the study. • D1_Processed_Profiles.xlsx: Contains the transverse pavement profiles after being processed using the Sabillon-Orellana Filtering Algorithm (SOFA). • D2_Computed_Parameters.xlsx: Includes the computed values of all 86 texture parameters for each profile prior to aggregation. • Code_Pavement_Parameters.R: An R script that provides the source code for all functions used to compute the complete set of pavement texture parameters. • Supplementary Material A – Parameter Table.docx: Provides a list of the 86 parameters, their abbreviations as used in the study, and their corresponding source documents. • Supplementary Material B – Texture Parameters.docx: Contains equations, brief descriptions, and practical applications for each parameter. All data were collected by the contributors and represent a subset of a larger dataset of texture measurements and pavement images gathered under TxDOT Project 0-7139: Determination of Pavement Surface Type. For access to the raw pavement profiles, further details on the processing algorithm, or additional information about the study, please contact Dr. Sabillon-Orellana.

Files

Steps to reproduce

To reproduce the computed parameters, users should consult the original source material for each parameter, refer to the equations in Supplementary Material B, and review the corresponding function code. When implementing their own calculations, users must account for the varying lengths of pavement profiles across sections. Users are also responsible for developing their own routines to execute the parameter computation functions. To replicate the correlation analysis presented in the main study, follow the procedures outlined in the methodology section of the manuscript (manuscript not included in this database).

Institutions

  • University of Tennessee Knoxville
  • University of Texas at Austin

Categories

Civil Engineering, Surface Texture, Pavement, Texture Analysis

Funders

Licence