Analysis tools for supporting the exploitation of MTInSAR products in monitoring landscape evolution

Multi-temporal SAR interferometry (MTInSAR), by providing both mean displacement maps and displacement time series over coherent objects on the Earth’s surface, allows analyzing wide areas, identifying ground displacements, and studying the phenomenon evolution at a long-time scale. The analysis of MTInSARbased displacement time series can provide useful information for long-term monitoring, management, and risk assessment at the regional level, when combined with planning tools, and support decision-makers at a local level in risk management. This analysis can be complicated due to the amount of data and, for this reason, it is essential to identify tools to accelerate the investigation of MTInSAR products. This work presents the results obtained by using analysis tools of MTInSAR data in Rheticus® Safeland, developed by Planetek Italia, which provides prevention and mitigation services of land instability hazards. We tested two tools (density and distribution tool) aimed at assessing the reliability of the information provided by MTInSAR products and two automated procedures (Fuzzy Entropy indicator, FE, Nonlinear Trend Analysis, NLTA), recently developed (Bovenga et al., 2022; Bovenga et al., 2021; Refice et al., 2022), for the identification of a smaller set of coherent targets (CTs) showing nonlinear displacement trends related to instability phenomena. The density tool concerns the percentage of surface of the study area covered by CTs. The tool combines the satellite geometry defined according to parameters coming from the MTInSAR processing (i.e. LOS direction and orbital state vectors), and the ground geometry obtained by exploiting geomorphic information (i.e. the average slope, the prevailing exposure, and the surface area). The distribution tool evaluates the spatial distribution of CTs: the velocity values derived from a dense spatial distribution of CTs covering uniformly the whole study area are more reliable than those derived from a few sparse targets. The FE index is able to recognize displacement time series characterized by strong non linearities and jumps related to phase unwrapping errors, which should be corrected before further analysis. The NLTA, based on the Fisher statistics, allows classifying targets according to the degree of a polynomial function, which optimally describe the displacement trend. Density and distribution tools were successfully exploited for assessing the reliability of the data provided by MTInSAR products, and, based on this, for identifying areas where the actual displacement is properly represented by MTInSAR data. FE and NLTA were very effective in supporting the analysis of ground displacements provided by MTInSAR, since they allow focusing on a smaller set of CTs corresponding to unstable areas or structures on the ground. Consequently, the integration of these tools within Rheticus® Safeland increases the level of information for users, who may respond more effectively to their needs.