Examination of UAS-SfM and UAS-Lidar for Survey Repeatability of Roadway Corridors

Uncrewed aircraft system (UAS)-based surveying offers an efficient way to produce dense point clouds of roadway corridors within the right-of-way (ROW). Common techniques include structure-from-motion and multi-view stereo (SfM/MVS) photogrammetry, or UAS-SfM, and UAS-based light detection and ranging (lidar), or UAS-Lidar. However, considerations such as measurement fidelity and post-processing workflows are necessary to effectively deploy these technologies. This study examines UAS-SfM and UAS-Lidar survey repeatability of a roadway surface by comparing direct georeferencing solutions with and without the use of a ground control point (GCP) network. Field tests examine differences in vertical accuracy and compare differences in digital terrain model (DTM)-based change detection of road-way surface elevation. Repeat UAS-SfM and UAS-Lidar flights were conducted over a flat runway surface acting as a proxy for a typical state highway roadway corridor. The UAS-SfM surveys were conducted with a platform equipped with a 42 MP RGB digital camera and a post-processed kinematic (PPK) global navigation satellite system (GNSS) receiver for accurate image geopositioning. The UAS-Lidar surveys were conducted using a geodetic-grade RIEGL VUX-1LR long-range scanner and a Livox Avia mapping-grade scanner. Direct georeferencing solutions resulted in vertical change detection errors (i.e., root mean square errors) within 2.9 cm for UAS-SfM and between 1.6 cm and 1.8 cm for UAS-Lidar depending on the lidar sensor. The inclusion of GCPs improved UAS-SfM change detection error to within 2.3 cm while UAS-Lidar improved to 0.9 cm for the survey-grade VUX sensor and degraded to 3.1 cm for the Avia sensor.