Detecting sinkholes and land surface movement in post-mining regions using multi-source remote sensing data

Abstract

This study investigated vertical land movement and sinkhole formation in the 40 km² abandoned “Siersza” mine area, Poland, by integrating multi-source remote sensing data and precise levelling measurements. First, publicly available InSAR products from the European Ground Motion Service (EGMS) were used to characterize broad-scale uplift and residual subsidence following mine closure. The EGMS “Ortho” and “Calibrated” datasets showed close agreement in regions with coherent scatterers, although the Calibrated data offered a higher spatial density. Second, airborne laser scanning (ALS) provided fine-scale insights into localized terrain changes, enabling the detection of around 60 % of documented sinkholes at a 0.90 probability threshold when compared to a field inventory. In contrast, comparisons with precise levelling revealed strong correlations (approximately 0.90–0.97) between EGMS and levelling data, but minimal concordance with ALS-derived displacements, likely due to the short-term, localized signals captured by ALS. A consistent offset of roughly 7 mm/year emerged between the satellite-derived and levelling measurements, indicating that some nominally stable geodetic reference points may be moving. Finally, the spatial distribution of vertical land movements was analysed concerning sinkhole centroids, showing that deformations become more variable within 200–300 m, reflecting overlapping regional uplift and localized subsidence linked to sinkhole formation. Overall, these findings highlight the importance of combining InSAR and ALS data for effective detection of early sinkhole-related hazards and emphasize the need to verify reference benchmark stability in post-mining environments.