Correlation analysis of InSAR displacement data and inspection data towards multiple bridge monitoring in transportation network

This paper presents a study on multiple bridge monitoring in a wide area of transportation networks using satellite Synthetic Aperture Radar (SAR) technology. SAR has been expected to have potential to analyze displacements of multiple large-scale structures in wide areas and in long-term without installing any sensors on them. This study shows quantitative analysis of InSAR (interferometric SAR) data on multiple bridges regarding to structural condition using their periodic inspection data. The target bridges are seventeen bridges located at a region in Japan, Ibaraki prefecture. They are the bridges that has lengths over 100 m selected from ones operated by the rural-road office of MLIT, the transport ministry of Japan, where periodic inspection data are all opened and available. Their displacements are then obtained using Sentile1 satellite SAR data. The time period for the analysis is seven years from 2016 to 2022, with time interval of 12 days. Using those data, line-of-sight (LoS) displacements of each bridge are derived as a time-series data through interferometric processing. The LoS displacement time-series data are then analyzed for each bridge by principal component analysis (PCA) to extract significant components of time-series deformation behavior. The extracted principle components, air temperature, and inspection records are compared and analyzed. As a result, it is found that a stable correlation between the principle component and air temperature could be one of explanatory factors of bridge conditions. This may indicate the bridges having stable correlation between LoS displacements and air temperature are in a nominal and undamaged condition although further investigation to more bridges is required. Moreover, visualizations of time-series InSAR bridge deflection and extracted feature components and its pattern analysis in multiple bridges are shown to have high potential to contribute on multiple bridge operations in whole transportation network.