World-wide InSAR sensitivity index for landslide deformation tracking

Landslides are a major geohazard in hilly and mountainous environments. In-situ inspection of downslope motion is costly, sometimes dangerous and, requires prior knowledge of the existence of a landslide. Remote sensing from space is a way to detect and characterize landslides systematically at large scale. Interferometric Synthetic Aperture Radar (InSAR) has shown to be a valuable resource of deformation information, but it requires expert knowledge and considerable computational efforts. Moreover, the successful application of InSAR for landslides requires a favorable acquisition geometry relative to the landslide deformation pattern. Consequently, there is a need for a widely applicable tool to assess the potential of InSAR at a particular location a priori. Here we present a novel, generic approach to assess the potential of InSAR-based deformation tracking, providing a standardised and automated method applicable on any slope. We define the detection potential as the sensitivity of InSAR to detect downslope displacement combined with the presence of coherently scattering surfaces. We show that deformation can be detected on at least 91% of the global landslide-prone slopes, and provide an open source Google Earth Engine tool for the quick assessment of the availability of potential coherent scatterers. This tool enables any person interested in applying InSAR to routinely assess the potential for monitoring landslide deformation in their region of interest.

Automated summary

Landslides are major geohazards in hilly and mountainous areas. In-situ inspection of downslope motion is costly and sometimes dangerous. Remote sensing using Interferometric Synthetic Aperture Radar (InSAR) is a valuable method for systematically detecting and characterizing landslides on a large scale. This study presents a generic approach to assess the potential of InSAR-based deformation tracking, providing a standardized and automated method applicable to any slope. The researchers demonstrate that deformation can be detected on at least 91% of global landslide-prone slopes and provide a Google Earth Engine tool for assessing the availability of potential coherent scatterers.