A remote sensing-enhanced Digital Twin framework for multi-scale infrastructure monitoring

This paper introduces an integrated Digital Twin framework for monitoring and managing transport infra structure, with a specific focus on bridges, through the integration of multi-source geospatial and structural survey data. By incorporating Terrestrial Laser Scanning, Global Navigation Satellite System surveying, space borne Multi-Temporal Interferometric Synthetic Aperture Radar, and Building Information Modeling, the pro posed approach facilitates a dynamic high-resolution visualization of key infrastructure conditions and its surrounding environment. The framework enables the integration of multi-source Non-Destructive Testing methods (NDTs) survey data with varying spatial or temporal resolutions, allowing semi-automatic updates of the Digital Twin after each spaceborne and on-site round of survey cycle and predictive analytics. A case study involving a masonry bridge in Italy demonstrates the system's capability to visualize deformation patterns derived from persistent scatterer (PS) measurements and examine their potential association with environmental hazards such as landslides. The integrated Digital Twin brings together bridge geometry and observed defor mation data to support infrastructure condition assessment and maintenance planning. This approach highlights the transformative potential of Digital Twins for infrastructure life-cycle management, particularly in contexts characterized by complex geotechnical conditions.