Characterization of Land Subsidence in Ravenna Using Sentinel-1 InSAR and Geostatistics

This study investigates the 2018-2022 evolution of land subsidence in Ravenna, Italy, employing Sentinel-1 C-band Differential Interferometric Synthetic Aperture Radar (DInSAR) displacement time series (TS). Temporal deformation patterns were analyzed by applying an automated classification tool that exploits regression analyses and conditional sequences of statistical tests including ANOVA F, and its performance is evaluated. Mean displacement velocity, acceleration, seasonality and trend classification maps were created, revealing distinct TS behaviors and spatial clusters across the study area. Anthropogenic drivers, including groundwater withdrawal and gas resource management activities, likely act as contributors to the subsidence process. The results indicate subsidence velocities ranging from -5 to -37 mm/year, with notable accelerations in agricultural and industrial zones, and a deceleration process occurring in the southern coastal area. Correlation with geological and land cover layers underscored the role of sediment compaction and landscape changes.