InSAR-informed in situ monitoring for deep-seated landslides: insights from El Forn (Andorra)

Abstract

Monitoring deep-seated landslides via borehole instrumentation can be an expensive and labor-intensive task. This work focuses on assessing the fidelity of interferometric synthetic-aperture radar (InSAR) as it relates to sub-surface ground motion monitoring, as well as understanding uncertainty in modeling active landslide displacement for the case study of the in situ monitored deep-seated El Forn landslide in Canillo, Andorra. We used the available Sentinel-1 data to create a velocity map from deformation time series from 2019–2021. We investigated the performance of InSAR data from the recently launched European Ground Motion Service (EGMS) platform and the Alaska Satellite Facility (ASF) On Demand InSAR processing tools in a time series comparison of displacement in the direction of landslide motion with in situ borehole-based measurements from 2019–2021, suggesting that ground motion detected through InSAR can be used in tandem with field monitoring to provide optimal information with minimum in situ deployment. While identification of active landslides may be possible via the use of the high-accuracy data processed through the EGMS platform, the intent and purpose of this work are the assessment of InSAR as a monitoring tool. Based on that, geospatial interpolation with statistical analysis was conducted to better understand the necessary number of in situ observations needed to lower error in a remote sensing re-creation of ground motion over the entirety of a landslide, suggesting between 20–25 total observations provide the optimal normalized root mean square error for an ordinarily kriged model of the El Forn landslide surface.