Evaluating Three-Dimensional Elevation Program Lidar Consistency and Accuracy at Scale Using Cloud-Native, Open-Source Methods

The U.S. Geological Survey three-dimensional elevation program (3DEP) has significantly expanded national lidar coverage, necessitating scalable, reproducible methods for assessing data quality across diverse terrains and acquisition conditions. This study introduces a cloud-native, open-source workflow designed to evaluate the geometric accuracy and consistency of 3DEP lidar data sets at a national scale. Leveraging tools such as the Point Data Abstraction Library, Open3D, and Amazon Web Services infrastructure, the workflow integrates global navigation satellite system‐surveyed ground control points and terrestrial laser scanning data to validate airborne lidar collections. Two case studies demonstrate the application of this process. In Puerto Rico, the process identified vertical biases and inconsistencies in vegetated areas, while in Iowa and Arizona, the process confirmed high vertical accuracy with minimal bias. The results underscore the effectiveness of combining cloud computing with open-source tools to perform large-scale lidar data quality assessments. This process offers a reproducible, efficient solution for nationwide validation of 3DEP data sets, supporting enhanced decision-making in geospatial applications.