MEASUREMENT AND VISUALIZATION OF DIRECTIONAL ROUGHNESS PROFILES USING THREE-DIMENSIONAL POINT CLOUDS

Practical measurements of rock surface roughness, often in the form of a joint roughness coefficient (JRC), have traditionally been made using methods that require direct contact with the rock. Although direct methods can produce accurate and useful results, they have some significant limitations. Traditional field-based measurements can be made only on rock surfaces that are accessible, which can require the use of technical rock climbing equipment or mechanical lifting devices that may expose field personnel to hazardous conditions. This presentation describes a method by which three-dimensional point cloud data obtained through terrestrial photogrammetry or laser scanning can be exported and used to extract surface roughness profiles in arbitrary directions referenced to a structurally or mechanically significant vector. If the significant vector is the dipline of the plane being characterized, as is often the case, its orientation can be determined objectively by fitting a plane to the point cloud data. Once a profile is extracted, the widely used Barton JRC can be estimated using any of several empirical correlations, including a new spectral method described in this presentation. Other techniques such as shaded relief images and contour maps can be used to visualize the roughness fabric of joints, faults, bedding planes, and other geological surfaces. Current technology allows for the calculation of outcrop-scale roughness coefficients over length scales ranging from meters to tens of meters.