Landslide Monitoring with RADARSAT Constellation Mission InSAR, RPAS-Derived Point-Clouds and RTK-GNSS Time-Series in the Thompson River Valley, British Columbia, Canada

Abstract

AbstractIn this paper, we evaluate the effectiveness of four land-deformation measurement techniques for monitoring slow-moving landslides along a high-risk section of the national railway corridor traversing the Thompson River valley, British Columbia, Canada. The geomorphically active North Slide acts as an ideal field laboratory for testing and evaluating novel monitoring techniques and methods. We compare differential processing of Structure from Motion (SfM) products such as point-cloud elevation models and orthophotos derived from Remotely Piloted Aircraft Systems (RPAS), along with satellite based Interferometric Synthetic Aperture Radar (InSAR) deformation measurements derived from RADARSAT Constellation Mission (RCM). These results are ground-truthed with periodic real-time kinematic (RTK) global navigation satellite system (GNSS) measurements. We evaluate point-cloud comparison techniques, including the multi-scale model-to-model cloud comparison (M3C2) algorithm and digital ortho image correlation techniques. Multi-temporal RCM InSAR deformation measurements are processed using a semi-automated processing system for interferogram generation and unwrapping. Manual processing of small baseline subsets (SBAS) leads to the recovery of 1-dimensional line-of-sight (LoS) and 2-dimensional deformation measurements. Lastly, we discuss the strengths and limitations of these techniques, considerations for interpreting their outputs, and considerations for direct comparisons between InSAR, RPAS and RTK-GNSS deformation measurements.