Ground deformation monitoring using InSAR and meteorological time series and least-squares wavelet software. A case study in Catania, Italy

Persistent Scatterers Interferometric Synthetic Aperture Radar (PS-InSAR) is an advanced satellite remote sensing technique which allows an effective monitoring of ground movement. In this work, PS-InSAR time series as well as precipitation and temperature time series in a region in Catania, Italy are utilized during 2018–2022, and their possible interconnections with land subsidence/uplift due to groundwater level change are investigated. First, the potential jumps in the displacement time series are removed, and then the Sequential Turning Point Detection (STPD) is applied to estimate the times when the velocity of the displacement time series changes. The results show a significant correlation between the frequency of turning points in displacement time series and precipitation trend change, particularly during the winter season. Furthermore, the Least-Squares Cross Wavelet Analysis (LSCWA) is applied to estimate the coherency and phase delay between the displacement and weather cycles in the time-frequency domain. The annual cycles of displacement and temperature show more coherency than the ones of displacement and precipitation across the study region. The results presented herein are important for infrastructure and water management planning.