Spatio-temporal analysis of georeferenced time-series applied to structural monitoring

Abstract

Spatio-temporal (S-T) analysis is not typical in structural monitoring applications of buildings and infrastructure. However, monitoring always includes the temporal component, and observations are often captured in specific locations. In other words, a monitoring dataset could also be considered a spatio-temporal archive, notwithstanding that not all monitoring applications can benefit from S-T processing methods. The paper discusses spatio-temporal analysis using the structural monitoring dataset of the Cathedral of Milan, which has an archive of vertical settlements collected from more than 50 years of measurements. The proposed methods can be adapted and extended for other structural monitoring applications, including single buildings, infrastructure, and the environmental level. The cases of pure temporal (T) and spatial (S) analyses are also discussed, comparing the different approaches, illustrating the pros and cons, and describing the opportunities of the S-T combined workflow. The paper specifically focuses on different typologies of S-T processing: data visualization and exploration techniques, clustering, change detection, prediction, and forecasting. The proposed algorithms were all implemented within the R open-source programming language. They can be replicated (and adapted) for other structural monitoring datasets featuring spatio-temporal correlation.