Integrated SBAS-InSAR Within a 3D/4D WebGIS in a Decision Support Perspective Using Static and Dynamic Data for Landslide Susceptibility Analysis

The use of satellite products for the identification of landslide-prone areas and zones affected by subsidence represents a research field in continuous evolution, thanks to the possibility of integrating radar data in multiple ways. Such information can be used as a static feature, as a criterion for the selection of landslide-absence samples, or as a true dynamic input. This work adopts the latter perspective, proposing an integrated framework of backscatter analysis and SBAS-InSAR analysis for the identification and characterization of landslide-affected areas. GRD images were preprocessed and analyzed through Google Earth Engine, from which temporal backscatter descriptors useful for highlighting instability signals were extracted. These were then combined with the results of the SBAS-InSAR technique. The integration of the two components allows the synergistic combination of different information derived from satellite products together with data characterizing the territory, improving the ability to identify areas subject to instability. The results, obtained over a portion of territory in Southern Italy, show that the inclusion of dynamic Sentinel-1 data significantly improves the identification of susceptibility areas. The synergistic use of dynamic SAR information allows the model to move beyond static or single-source susceptibility mapping, providing an updatable framework that supports near-real-time monitoring. The outputs are integrated into a 3D/4D WebGIS with Decision Support System (DSS) connotation, which further enhances the practical applicability of the methodology by enabling the real-time visualization and interpretation of the results.