Abstract
Although laser-scanning total propagated uncertainty (TPU) is an active topic in the research community, there is a current dearth of commercial or open-source software for generating point clouds with per-point, three-dimensional (3D) coordinate uncertainties from terrestrial, mobile, and airborne laser scanning.
Consequently, there is a corresponding lack of tools for on-the-fly 3D visualization of these point cloud uncertainties. Visualization tools could be incredibly valuable for analyzing and communicating the spatial variability of uncertainty in a data set, ultimately enhancing both qualitative and quantitative analyses.
This study presents an efficient visualization framework for terrestrial laser-scanning (TLS) point cloud uncertainty calculation utilizing the OpenGL Shader Language (GLSL). The methods were tested on four data sets, ranging from a controlled indoor scene containing objects representing simple geometric shapes (e.g., spheres and cones) to a complex forest environment with many types of natural objects.
OpenGL shader-based uncertainty visualization was found to aid with the assessment of the effects of modifying models of measurement uncertainty, such as accounting for the nonlinear increase in laser beam radius at short ranges when modeling laser beamwidth-derived uncertainty, as well as range- and angular-based component uncertainties.
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