Risk assessment of building and infrastructure using InSAR-derived deformation gradients and pattern variations in the Beijing plain, China

Ground surface deformation and spatial differential deformation pose significant risks to urban buildings and infrastructures. Previous studies analyzed deformation risks using Interferometric Synthetic Aperture Radar (InSAR) but often lacked integration of temporal pattern variations or multi-source datasets. This study employed satellite InSAR to derive ground deformation in the Beijing Plain, China. We developed a method for detecting deformation pattern variations, enabling the identification of temporal evolution differences beyond conventional velocity analysis. To support macro-level risk assessment, we integrated multi-source external datasets, including nighttime remote sensing imagery, land cover data, and building height, to evaluate hazard and vulnerability. Risk indicators, including cumulative deformation, spatial gradients, and pattern variations, were extracted to identify potential high-risk zones at a micro level. Our analysis revealed two major subsidence funnels in northwestern Tongzhou and eastern Chaoyang, with cumulative settlements of –0.2 to –0.7 m, concurrent uplifts of 0.08 to 0.20 m in the northern Beijing Plain, and peak deformation gradients of β≈8.2×10−4 and ε≈2.6×10−4 (2015–2021). High-risk areas were detected in eastern Chaoyang, northwestern Tongzhou, and near Capital International Airport and subway lines 1 and 6. This study highlights the importance of integrating time series InSAR and multi-source datasets for deformation risk assessments.