Analyzing of land subsidence by Sentinel-1 time-series images using PSInSAR method: A case study of Thai Nguyen, Vietnam

Abstract

Natural disasters and human activities are now causing an increase in land subsidence, or surface displacement. The effects of land subsidence cause landslides and construction cracking. PSInSAR (Persistent Scatter Interferometry) was identified to estimate surface displacement from a time series of Synthetic Aperture Radar (SAR) images. This technique is a subset of the DInSAR (Differential Interferometric Synthetic Aperture Radar) method. In this article, the authors determined and analyzed land subsidence in Thai Nguyen Province, Vietnam, using time series Sentinel-1A data with VV polarization from July 2019 to December 2020 and the PSInSAR method. There are numerous mineral exploitation mines in Thai Nguyen Province. It is one of the causes of an unusual amount of land subsidence in the region. According to the results determined by the InSAR technique, the velocity of displacement along the line of sight (LOS) of the study area ranges from -23.2 mm per year to +21.0 mm per year. The analysis of time-series SAR images reveals anomalous land subsidence at persistent scatter (PS) points. By analyzing the time-series displacement at PS points using the StaMPS Visualizer tool, the land subsidence during the image acquisition period and surface displacement trends over time were determined. According to this, coal mining regions have the highest land subsidence values ranging from -40 mm to -60 mm. The city and mine regions of Thai Nguyen, where operations have stopped, are largely stable. In addition, the time-series analysis at PS points will allow us to identify unusual displacement points, enabling the implementation of early warning plans.