Scalable Platform for UAV Flight Operations, Data Capture, Cloud Processing and Image Rendering of Landslide Hazards and Surface Change Detection for Disaster-Risk Reduction

Abstract This International Programme on Landslide (IPL) Project 202 paper presents a scalable remote piloted aircraft system (RPAS) platform that streamlines unoccupied aerial vehicle (UAV) flight operations for data capture, cloud processing and image rendering to inventory and monitor slow-moving landslides along the national railway transportation corridor in southwestern British Columbia, Canada. Merging UAV photogrammetry, ground-based real-time kinematic global navigation satellite system (RTK-GNSS) measurements, and satellite synthetic aperture radar interferometry (InSAR) datasets best characterizes the distribution, morphology and activity of landslides over time. Our study shows that epochal UAV photogrammetry, benchmarked with periodic ground-based RTK-GNSS measurements and satellite InSAR platforms with repeat visit times of weeks (e.g., RADARSAT-2 and SENTINEL-1) to days (e.g. RADARSAT Constellation Mission) provides rapid landslide monitoring capability with cm-scale precision and accuracy.