A Time-Series Surface Displacement Dataset for the Geumgwang Reservoir Using Sentinel-1 SAR Observations

Abstract

Reservoir-related disasters have become increasingly frequent in recent years due to abnormal climate phenomena, including heavy rainfall and droughts, driven by rapid climate change. As similar risks are also rising in South Korea, time-series observations were conducted in areas surrounding reservoirs using Synthetic Aperture Radar (SAR) satellite data, which are relatively unaffected by weather conditions and day-night constraints. In this study, 57 Sentinel-1 SAR images acquired between October 2023 and October 2025 were used to perform time-series interferometric analysis of the dam structure and surrounding areas of Geumgwang Reservoir in Anseong, Gyeonggi-do, South Korea. Two algorithms were employed: the small baseline sub - set method, which constructs interferometric networks from image pairs with short spatial and temporal baselines for time-series analysis, and the persistent scatterer interferometry method, which extracts persistent scatterers with stable backscattering characteristics and analyzes their temporal evolution. The results derived from both techniques were compared at four locations, and all sites showed relatively stable deformation signals. The strong agreement between the two interferometric approaches further confirms the reliability of the processed dataset. Consequently, the dataset can serve as a reliable reference for long-term safety monitoring and various secondary applications.