Project specifications are designed and enforced to determine whether or not delivered data met required standards. However, rapid advancements in LiDAR data capture technologies have led to major challenges for end users to validate the data and processes for fitness for use. The developed UDTEB model uses two approaches to fill this gap – 1) the deterministic approach employing CMP and SBET or their equivalent files of ALS surveys to extract the root mean square errors of points with respect to a trajectory and an estimated terrain, and 2) where these files are not available, the non-deterministic approach employing published LiDAR system performance reports to simulate flight conditions and estimate errors under defined conditions. To validate the UDTEB model, five areas of varying topography and land cover were investigated. TIN differencing and a new method for point by point comparison of checkpoints and corresponding LiDAR points using square windows around the checkpoints were employed. When the obstructions of the checkpoints were further categorized as “clear”, “light” and “dense”, average RMSE values observed were 0.06 m, 0.05 m and 0.10 m respectively. The UDTEB model proposes a method to equip end-users to perform error budgeting from data acquisition to the end product creation and validate the elevation accuracy of a LiDAR data at a given confidence interval. The method can be customized for a given error analysis task, allowing the user to include other error sources into the model. It can also be adopted for elevation error analysis of large datasets similar to LiDAR.
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