The use of satellite data to support the structural health monitoring in areas affected by slow-moving landslides: a potential application to reinforced concrete buildings

The building stock around the world is exposed to different types of natural actions such as earthquakes or landslides. In particular, Italy is one of the countries worldwide most affected by landslides. Mitigation of landslide risk is a topic of great interest for the evaluation and management of its consequences. Periodical monitoring of the landslide-induced damage on structures require high costs due to the large number of exposed elements. With respect to the reinforced concrete structures, slow-moving landslides can affect primary structural elements, but more frequently damage occurs on the most vulnerable elements of the structure such as infills. The aim of this work is to demonstrate the potential utility of satellite data derived from a remote sensing technique, known as differential synthetic aperture radar interferometry, to support the structural health monitoring of reinforced concrete buildings affected by landslides. This article shows the structural health monitoring process for a reinforced concrete infilled building within a landslide-affected area, using the differential synthetic aperture radar interferometry data as input for the structural analysis in order to investigate the evolution of damage over the years. Three-dimensional structure, including the explicit infills consideration, has been modeled based on the information available from a visual survey, obtaining the missing parameters from a simulated design process and from the literature. In the field of the civil protection programs for the landslide risk reduction, this methodology can be quickly repeated for large sets of reinforced concrete buildings. Evidence of the visual survey showed a significant damage pattern in some infills. A good agreement has been found between analytical previsions and existing damage. Moreover, a global infills damage assessment of the case study building is proposed. Finally, assuming a constant increase in displacements in future years, a prediction of the future expected damage is shown.