Interactive Visualization of 3D Coordinate Uncertainties in Terrestrial Laser Scanning Point Clouds

Laser scanning, also known as lidar, is being used by a growing number of scientific studies and engineering applications. The spatially-varying geometric uncertainty of the resulting three-dimensional (3D) point cloud can have a substantial impact on the validity of derived products (e.g., digital surfaces and 3D models) and the quality of observations and findings. While total propagated uncertainty (TPU) for laser scanning is an active research topic, there is a shortage of software solutions for computing and efficiently visualizing per-point, 3D coordinate uncertainties from terrestrial, mobile, and airborne laser scanning data. Intuitive visualization of uncertainty is effective for communicating and analyzing the spatially-varying nature of laser scanning point cloud uncertainties and can inform subsequent qualitative and quantitative analyses. This work proposes a visualization framework for terrestrial laser scanning (TLS) point cloud data, which performs the calculation and display of per-point spatial uncertainty during interactive 3D visualization. On the fly manipulation of the TPU model is made possible by an out-of-core approach that relies on OpenGL Shader Language (GLSL) programming running on a graphics processing unit (GPU). The proposed framework was tested on indoor and outdoor TLS datasets acquired with three different commercially available TLS instruments. OpenGL shader-based uncertainty visualization allowed for the assessment of individual TPU components (e.g., range, beamwidth, and angular-based uncertainties) and aided in the manipulation of the TPU model to account for the nonlinear increase in laser beam radius at short ranges.