COMPARISON OF TERRESTRIAL LASER SCANNING AND STRUCTURE FROM MOTION TECHNIQUES FOR ASSESSMENT OF UNSTABLE ROCK SLOPES IN ALASKA

Terrestrial lidar scanning (TLS) has been proven as a valuable technique for assessment and monitoring of unstable slopes; however, comprehensive TLS surveys of slopes and cliffs commonly require numerous discreet instrument setups, which can be time consuming. Even with numerous setups, portions of a slope or cliff are often not visible from areas accessible to the scanner, and valuable information of the slope geomorphology cannot be captured. The use of unmanned aircraft systems (UAS) to gather overlapping aerial imagery can be used to generate similar 3D point cloud reconstructions by way of Structure from Motion (SfM) and multi-view stereo (MVS) photogrammetric techniques. Acquisition of cliff geometry using a UAS can provide superior accessibility when compared to TLS methods. To evaluate the capabilities of SfM, this study examines three sites with unstable rock slopes, which were surveyed along the Glenn Highway in Alaska using both TLS and SfM techniques. The datasets were acquired simultaneously and linked to a rigorous survey control network. An accuracy evaluation of the SfM derived surface models was performed using two independent reference datasets: the TLS data numerous reflectorless total station observations across the cliff surface. Additional comparisons between TLS and SfM were performed to examine model completeness, resolution, and distributions of morphological properties including slope, surface roughness, and a rock activity index. Results indicate that SfM reconstruction is a viable option for unstable rock slope characterization when tied to rigorous survey control. The SfM models were generally more complete than the TLS models and had a more uniform point density across the cliff surface. While the TLS models were able to obtain more sampling directly below thick vegetation for creating a bare-earth DEM, the UAS SfM models showed benefits in capturing bare earth behind and around sparser vegetation due to the flexible look angle. However, some concerning artifacts, over-smoothing, and inconsistencies were observed in the SfM derived models, which question its suitability for reliably detecting small changes on unstable rock slopes.