In recent years, the prolonged exploitation of coal resources has led to the depletion of coal reserves in some mining areas, resulting in the closure of certain mines worldwide. After mine closures, the fractured rock masses in abandoned mine cavities undergo weathering and degradation due to factors such as stress and groundwater, leading to reduced strength. This change alters the stress distribution and load-bearing capacity of the fractured rock within the abandoned voids, resulting in secondary or multiple deformations on the surface, which pose significant potential threats to surface infrastructure and public safety. Research into the mechanisms, patterns, and predictive methods of secondary surface subsidence in closed mines is thus of great theoretical and practical significance. Based on a literature review and practical monitoring experience in closed mine sites, this study systematically examines and analyzes the current state of secondary surface subsidence monitoring methods, formation mechanisms, spatiotemporal distribution patterns, and prediction methods in closed mines, as well as existing challenges. Initially, we compare the advantages and limitations of conventional surface deformation monitoring techniques with remote sensing techniques, emphasizing the benefits and issues of using InSAR technology for monitoring surface subsidence in closed mines. Next, by reviewing extensive data, we analyze the formation mechanisms and spatiotemporal evolution of secondary surface subsidence in closed mines. Building on this analysis, we discuss numerical and analytical methods for predicting secondary surface subsidence mechanisms in closed mines, evaluating the strengths and weaknesses of each approach. Predictive models for surface subsidence and uplift phases in the longwall collapse method are presented based on the constitutive relationships of fractured rock masses. Finally, the study highlights that the mechanisms and patterns of surface subsidence in closed mines represent a highly complex physical–mechanical process involving geological mining environments, fractured rock structures, constitutive relations, deformation characteristics, hydro-mechanical interactions, and groundwater dynamics, underscoring the need for further in-depth research.

This paper presents a strategy for extracting three-dimensional (3D) mining deformation from a single-geometry synthetic aperture radar (SAR) dataset. In light of the directionality of horizontal displacement caused by underground mining, we first re-model the proportional relationship between horizontal displacement and horizontal gradient of subsidence. Afterward, to improve the stability of the re-model, a solution strategy is proposed by setting different solution starting points and directions. The proposed method allows hiring of arbitrary single-geometry SAR data (e.g., air-borne, space-borne, and ground-borne SAR data) to reconstruct 3D displacements of mining areas. The proposed method has been validated through simulation and in-site data. The simulation data monitoring results indicate that the root mean square errors (RMSE) of the 3D displacements extracted by the proposed strategy are 0.45, 0.5, and 2.98 mm for the vertical subsidence, east–west, and north–south horizontal displacements, respectively. The in-site data monitoring results indicate that the RMSE of vertical subsidence compared with the leveling data are 7.3 mm. Furthermore, the MSBAS method was employed to further validate the reliability of the proposed method, the results show that the proposed method is effective to obtain the 3D deformation of the mining area, which greatly improves the applicability of SAR interferometry in the 3D deformation monitoring of the mining areas.

Accurate monitoring of mining three-dimensional deformation plays an important role in analyzing the subsidence mechanism and assessing potential geological hazards in the mining area. This paper combines TerraSAR-X and RADARSAT-2 heterogeneous SAR images employing MSBAS technology to obtain the three-dimensional time-series of deformation of the 132 610 working face in the Fengfeng mine from December 2015 to February 2016. The monitoring results show that the maximum surface subsidence and the subsidence rate during the monitoring period were –243 mm and 4.42 mm/day, and the maximum east-west horizontal movement was –80~30 mm. The surface subsidence basin is in the active stage, which is prone to pose a threat to the safety of the surrounding structures. Comparison with the leveling data shows that the root-mean-square deviation of the vertical deformation obtained by MSBAS technology is 10.7 mm, and the accuracy can reach the centimeter level. Meanwhile, based on the vertical deformation obtained by MSBAS technology, combined with the proportionality relationship between horizontal movement and tilt, the north-south horizontal movement was estimated as –80~70 mm, which provided a solution for obtaining the north-south horizontal movement of the mining area by InSAR. Analysis of the three-dimensional time-series of the surface deformation at the main sections shows that the surface deformation features during the mining process of the 132610 working face match well with the general model of mining subsidence, but the working face inclination angle has an influence on the surface deformation.

Mining-induced subsidence in coal mining areas is characterized by rapid subsidence rates and significant magnitude. High-intensity coal extraction induces substantial surface deformation with steep phase gradients, leading to phase unwrapping errors in interferometric synthetic aperture radar (InSAR) measurements. Conventional differential InSAR (DInSAR) techniques alone are insufficient to capture the principal components of surface subsidence under these conditions. To address the limitations of DInSAR in resolving large-gradient deformations and the inadequate precision of offset-tracking technology in monitoring minor deformations in mining regions, this study proposes an integrated deformation monitoring methodology combining DInSAR and offset-tracking techniques. The synergistic approach enables accurate extraction of large-gradient deformation fields in mining areas. Thirteen RADARSAT-2 images acquired between April 28, 2015, and March 5, 2016, from a coal mining area in Handan City, China, were analyzed. Validation against terrestrial leveling data demonstrated measurement discrepancies with a maximum bias of 0.22 m, a mean absolute error (MAE) of 0.052 m, and a root mean square error (RMSE) of 0.063 m. The results indicate strong consistency between the fused DInSAR-offset-tracking outputs and ground truth data, confirming the validity and reliability of the proposed methodology for monitoring large-gradient surface deformations. This integrated technique effectively reconstructs complete subsidence basin profiles induced by mining activities, providing a robust framework for subsidence monitoring in analogous mining environments. The methodological advancements offer critical insights for operational safety assessments and environmental impact mitigation in coal extraction regions.