InSAR-Informed In-Situ Monitoring for Deep-Seated Landslides

TL;DR

This study evaluates the effectiveness of InSAR data from Sentinel 1 and EGMS platforms in monitoring deep-seated landslide displacements, comparing it with in situ borehole measurements to enhance landslide monitoring accuracy.

Contribution

It demonstrates how InSAR can complement in situ monitoring for landslides and identifies the optimal number of in situ observations needed for accurate remote sensing-based displacement modeling.

Findings

InSAR data correlates well with borehole measurements for landslide displacement.

Optimal in situ observations for modeling are between 20 to 25 points.

InSAR can identify active landslide scarps using EGMS platform.

Abstract

This work focuses on assessing the fidelity of Interferometric Synthetic Aperture Radar (InSAR) as it relates to subsurface ground motion monitoring, as well as understanding uncertainty in modeling active landslide scarp displacement for the case study of the in situ monitored El Forn deep seated landslide in Canillo, Andorra. We used the available Sentinel 1 data on the Alaska Satellite Facility (ASF) Vertex platform to create deformation velocity maps and time series of the El Forn landslide scarp. We compared the performances of InSAR data from the recently launched European Ground Motion Service (EGMS) platform and the ASF Vertex Platform in a time series comparison of displacement in the direction of landslide motion with in situ borehole based measurements from 2019 to 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 landslide scarps may be possible via the use of EGMS platform, the intents and purposes of this work are in 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 on a remote sensing recreation of ground motion over the entirety of a landslide scarp, suggesting between 20 to 25 total observations provides the optimal normalized root mean squared error for an ordinarily kriged model of the El Forn landslide scarp.