Rock surface roughness estimation using TLS data

Rock surface roughness is an important property influencing the shear strength of a rock mass and
therefore its stability. For safety reasons and appropriate engineering design on potentially instable
slopes, accurate and reliable measurement of surface roughness is needed. In this research the stateof-the-art terrestrial laser scanning (TLS) technology is used to remotely sense large rock surfaces
and further on estimate the roughness as a function of direction and scale. The research attempts to
answer the following question: what is the smallest scale of surface roughness that can be reliably
extracted from TLS point clouds? To answer the question, TLS capabilities and limitations are studied
in detail. The main limitation of TLS is the range measurement noise, which can result in
overestimation of surface roughness. To reduce the noise effect, different image de-noising methods
(Discrete Wavelet Transform and Non-Local Mean) are applied on TLS meshes and their results are
compared. A second limitation of TLS data is the effective resolution of the point cloud caused by the
divergence of laser beam, which defines the smallest observable surface detail. Therefore, the
effective resolution of TLS data is analyzed. Firstly a theoretical-empirical method based on Average
Modulated Transfer Function is applied. This method implies some assumptions about measurement
procedure in a laser scanner that usually cannot be tested or are unknown to the end-user. Thus, we
aim to develop an empirical method that is time-efficient and simple in order to be performed in-situ
immediately before or after rock surface acquisition.