Persistent Scatterer Interferometry and Statistical Analysis of Time-Series for Landslide Monitoring: Application to Santo Stefano d’Aveto (Liguria, NW Italy)

Abstract

Landslides are a major threat for population and urban areas. Persistent Scatterer Interferometry (PSI) is a powerful tool for identifying landslides and monitoring their evolution over long periods and has proven to be very useful especially in urban areas, where a sufficient number of PS can be generated. In this study, we applied PS interferometry to investigate the landslide affecting Santo Stefano d’Aveto (Liguria, NW Italy) by integrating classic interferometric techniques with cross-correlation analysis of PS time-series and with geological and geotechnical field information. We used open-source software and packages to process Synthetic Aperture Radar (SAR) images from the Copernicus Sentinel-1A satellite for both ascending and descending orbits over the period 2015–2021 and calculate both the vertical motion and the E-W horizontal displacement. By computing the cross-correlation of the PS time-series, we identified three families of PS with a similarity greater than 0.70. The cross-correlation analysis allowed subdividing the landslide in different sectors, each of which is characterized by a specific type of movement. The geological meaning of this subdivision is still a matter of discussion but it is presumably driven by the geomorphological setting of the area and by the regional tectonics.

Keywords

• landslide
• Persistent Scatterer Interferometry
• SNAP
• StaMPS
• time-series
• cross-correlation