Combining Optical and SAR Remote Sensing Data for Landslide Detection and Monitoring after Extreme Climate Events: a Case Study in the Northeastern Italian Alps.

Following extreme climate events, a timely and detailed landslide mapping is necessary to determine which areas have been most affected and to support civil protection in rescue operations. Moreover, the monitoring of slope instabilities can lead to an appropriate hazard and risk assessment of the affected areas and to an effective design of remediation works. The integration of optical and SAR remote sensing data acquired by spaceborne sensors plays a key role in these types of evaluations. Optical sensors perform better in terms of spatial and temporal resolution; SAR sensors have the advantage of acquiring images in all weather and light conditions. In this case study, an unstable slope located on the left side of the Boite river in the municipality of Valle di Cadore (northeastern Italian Alps) was investigated after windstorm Vaia event that occurred in October 2018. Medium and high-resolution optical imagery acquired by Sentinel-2 and PlanetScope missions, respectively, have been exploited to calculate NDVI values before and after the event as well as to identify and delineate the most damaged areas using the change detection technique. Then, the processing of Sentinel-1 SAR data through the Small BAseline Subset (SBAS) multi-temporal algorithm allowed for monitoring the evolution of the slope during the post-event. The results show the benefits of combining optical and SAR data to map and monitor the evolution of a slope that was affected by an extreme event such as the windstorm Vaia. In particular, the optical data show the sectors affected by slope instabilities and the time series derived by the SBAS analysis quantifies the displacement rate, emphasizing that the slope is still active. In conclusion, the analysis carried out reveals how these techniques can now become a concrete part of the design of systems to mitigate geological risks derived from hydrometeorological phenomena, whose frequency appears to be increasing due to climate change.