Quantifying the effects of terrestrial laser scanner settings and survey configuration on land surface roughness measurement

Abstract

The application of terrestrial laser scanning (TLS) for measuring Earth surface features is increasing. However, TLS surveys require users to choose and specify certain properties of the scan (i.e., resolution, height, distance, number of scan positions), often with limited understanding of how these properties affect the accuracy of the data. This paper presents results from an experiment that quantifies the effects of different scan settings and survey configurations on the measurement of centimeter-scale surface roughness. The main goal is to provide quantitative evidence to help guide and optimize field-based surface roughness measurements involving TLS data. The experiment involved an array of artificial roughness elements placed on an asphalt surface, similar to the approach of using inverted buckets in boundary layer experiments to simulate a rocky or sparsely vegetated surface with smooth interspaces. The independent variables consisted of laser point spacing, number of scan positions, and the height and distance of the scanner relative to the roughness array. The dependent variables were roughness element height, data occlusion, relative vertical accuracy, the root mean square height of the cup array, and the relative roughness of the asphalt surface. Two roughness patterns were tested, isotropic and anisotropic. Results show that when the laser point spacing was greater than the size of the individual roughness elements, their calculated height was between 32% and 73% below their actual height, but with a smaller spacing the calculated height was either equivalent to their actual height or only slight lower. Therefore, before a TLS survey is undertaken, manual measurements of roughness elements should be used to determine the size of the smallest roughness elements of interest, thus guiding the selection of laser point spacing. Larger point spacing also decreased the vertical accuracy of surfaces interpolated from the point clouds compared to global positioning system points. By combining point clouds from three scan stations arranged in a triangular network around the roughness array, the proportion of data occlusion decreased to as little as 0.24%, but due to error associated with point cloud registration, the accuracy of roughness element height decreased and the roughness of the asphalt surface artificially increased. For the most accurate measurements of the roughness element height and interspace roughness our results suggest that high-resolution point clouds obtained from one vantage point should be used. In regard to scanner height and distance, we measured a doubling of the occluded area when the scanner height decreased and distance to the array increased, thus increasing the angle of incidence. Reducing the angle of incidence decreases occlusion but also limits the areal coverage of each TLS scan and increases the number of scan stations at different vantage points required to cover large areas, which ultimately affects the accuracy of other roughness metrics. Overall, this case study demonstrates that there are trade-offs in that the optimization of one metric (e.g., roughness element height) can have negative effects on another (e.g., data occlusion). The choice of TLS settings and survey configuration, therefore, influences the accuracy of surface roughness measurements.