Identification and Preliminary Classification of Critical Buildings in an Urban Context: A Combined Approach with DInSAR Satellite Measurements and Hierarchical Clustering

The conventional framework for Structural Health Monitoring (SHM) primarily focuses on individual structures. However, to effectively identify the most vulnerable elements, preliminary studies are required at a wide area scale. This becomes particularly challenging in urban settings, where numerous buildings of varied shapes, ages, and structural conditions are closely spaced from one another. A twofold task is therefore required: the automated identification and differentiation of various structures, coupled with a ranking system based on perceived structural risk, here assumed to be linked to their deformation patterns. It integrates displacement measurements acquired through the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique, specifically employing the full-resolution Small Baseline Subset (SBAS) approach, with Hierarchical Clustering. The effectiveness of this method is successfully demonstrated and validated in two selected areas of Rome, Italy, serving as case studies. The results achieved on this wide area scale monitoring can be used to select the constructions that need a more in-depth assessment.