On the Joint Exploitation of Satellite DInSAR Measurements and DBSCAN-Based Techniques for Preliminary Identification and Ranking of Critical Constructions in a Built Environment

The need for widespread structural safety checks represents a stimulus the research of advanced techniques monitoring at scale single constructions or wide areas. In this work, strategy to preliminarily identify and rank possible critical in built environment is presented, based on joint exploitation satellite radar remote sensing measurements artificial intelligence (AI) techniques. are represented by displacement time series obtained through Differential Synthetic Aperture Radar Interferometry (DInSAR) technique known as full resolution Small BAseline Subset (SBAS) approach, while exploited AI Density-Based Spatial Clustering Applications with Noise (DBSCAN) methodology. DBSCAN applied SBAS-DInSAR products relevant achieved Persistent Scatterers (PSs), clusters pixels corresponding buildings within investigated area. analysis deformation evolution each building cluster performed terms velocity rates statistics DInSAR measurements. maps areas then retrieved buildings. proposed methodology three city Rome (Italy), imaged COSMO-SkyMed SAR constellation from ascending descending orbits (in interval 2011–2019). Starting measurements, algorithm provides automatic clustering selected Exploiting derived study area, preliminary identification ranking achieved, thus confirming validity approach.