Quantitative characterization method of point cloud distribution in tunnel for optimizing TLS scanning plan

• Quantitatively described point cloud distribution in tunnels. • Uses point cloud spacing and thickness to represent density and unevenness. • The proposed calculation method was validated through tunnel field tests. • Evaluate resolution, station spacing, and linearity error effects on point cloud. • Provided a framework for TLS scanning optimization for precise tunnel inspection. A novel method for quantitatively describing the distribution of point clouds in tunnels is introduced to optimize tunnel scanning schemes. The method uses point cloud spacing and thickness to represent the density and unevenness of the point cloud, respectively. Point cloud spacing is categorized into point spacing and ring spacing based on the scanning trajectory, and these metrics are calculated using coordinates from a regularly distributed point cloud. Point cloud thickness is derived by combining the measurement error range in the laser incidence direction with the laser incidence angle. The above calculation method has been validated through tunnel field tests. The quantitative characterization method evaluates the effects of resolution, station spacing, and linearity error on point cloud spacing and thickness. It helps determine the necessary resolution, station spacing, and TLS scanner specifications to ensure that point cloud spacing and thickness meet the requirements for tunnel health assessment. By addressing the lack of comprehensive quantitative consideration of point cloud distribution in selecting scanning parameters, this method provides a robust framework for optimizing scanning schemes, ensuring accurate and reliable point cloud data for tunnel inspection.