Measuring ground surface elevation changes in a slow-moving colluvial landslide using combinations of regional airborne lidar, UAV lidar, and UAV photogrammetric surveys

Abstract

Slow-moving, chronically destructive landslides are projected to grow in number globally in response to precipitation increases from climate change, and land disturbances from wildfire, mining, and construction. In the Cincinnati and northern Kentucky metropolitan area, USA, landslides develop in colluvium that covers the steep slopes along the Ohio River and its tributaries. Here we quantify elevation changes in a slow-moving colluvial landslide over 14 years using county-wide lidar, uncrewed aerial vehicle (UAV) structure from motion (SfM) surveys, and a UAV lidar survey. Because the technology and quality differ among surveys, the challenge was to calculate a threshold of detectable change for each survey combination. We introduce two methods, the first uses propagated elevation difference errors, and the second back-calculates the individual survey errors. Thresholds of detection range from ± 0.05 to ± 0.20 m. Record rainfall in 2011 produced the largest vertical changes. Since then, the landslide toe has continued to deform, and the landslide has doubled its width by extending into a previously undisturbed slope. While this study presents a technique to utilize older datasets in combination with modern surveys to monitor slow-moving landslides, it is broadly applicable to other studies where topographic data of differing quality is available.