Decomposition of displacement vectors from InSAR images of mining areas - a case study

Abstract

Mining activities are a major anthropogenic driver of ground surface deformation, often resulting in complex subsidence phenomena that are difficult to characterize using conventional geodetic methods. Interferometric synthetic aperture radar (InSAR) provides a powerful means of detecting displacements over large areas, but decomposing its line-of-sight (LOS) measurements into full 3D displacement vectors remains a challenge, especially when limited to data from two satellite tracks. This paper presents an iterative decomposition algorithm that supplements the classical two-LOS system with an empirical relationship between horizontal displacement components and the slope of the subsidence trough, derived from established mining deformation theories. The algorithm is validated through both a theoretical »blind« test case and three real-life examples of mining-induced seismic deformation in the Legnica-Głogów Copper District (LGCD), Poland. The results show that the proposed method significantly improves the accuracy of displacement vector estimation compared to classical decomposition techniques. This approach not only enhances our understanding of mining-induced ground movements but also offers practical benefits for ground surface deformation monitoring and hazard assessment in subsidence-prone regions.