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• Propose a methodology to retrieve 3-D multi-level mining deformation with OTD-InSAR. • Improve the deformation precision with about 82.6% in the south-north direction. • Eliminate large errors caused by ground fissures in the horizontal deformation map. • Present 3-D mining deformation with more details. Underground longwall mining activities usually induce three-dimensional (3-D) multi-level surface deformation, which could lead to serious natural hazards. Offset-tracking (OT) and differential interferometric synthetic aperture radar (DInSAR) technology (referred to as OTD-InSAR) can be used to observe the large-level and small-level mining deformations based on single InSAR pair, but the measured deformation is only along the radar line-of-sight (LOS) or the azimuth directions rather than in the 3-D directions. The conventional InSAR-based methods to resolve 3-D mining deformation have the strict restrictions and low south-north accuracy. In this paper, a novel methodology is proposed to utilize a multi-level deformation fusion model and the Lagrange multiplier method based on single OTD-InSAR pair (hereafter called MAOTD-InSAR) to estimate and optimize the 3-D multi-level surface deformation. The Daliuta coal mining area of China was selected to verify the feasibility and precision of the proposed method using high resolution TerraSAR-X (TSX) SAR images with six pairs. Results show that the root mean square errors (RMSEs) of MAOTD-InSAR against in-situ measured data are less than 0.2214 m, 0.1612 m and 0.1880 m in the east, north and vertical directions, respectively. The minimum RMSE in the horizontal direction could reach 0.0361 m with an improvement of about 82.6%, which particularly improve the accuracy in the south-north direction for the TSX satellite since its direction of azimuth deformation is approximately north direction, and this is also adequate for the other satellites in the near-polar orbit. In addition, an empirical model was generated with respect to the gradients of ground fissures on horizontal deformation, and this model enabled us to remove large errors caused by ground fissures. The verification results show that the proposed method provides higher precision and reliability for the resolved 3-D multi-level surface deformation, which presents 3-D mining deformation with more details from the edge to the center of the subsidence basin and will show some possibilities for new findings and interpretations in the process of coal mining. [ABSTRACT FROM AUTHOR]

• Propose a new fusion model to retrieve multi-level mining deformation. • Monitor the long-term mining deformation using the DInSAR and OT technology. • Present the prediction model to forecast deformation with insufficient SAR data. • Bring about a comprehensive analysis of the deformation evolution of the full workface. Caused by the underground longwall mining activities, ground deformation, which includes sudden large-level deformation, slow small-level deformation and the middle-level deformation between them, can lead to serious construction damage and ecological environment degradation. In this paper, we propose a new fusion model that is able to completely retrieve multi-level deformation with measured radar line-of-sight (LOS) deformation from offset-tracking (OT) and differential interferometric synthetic aperture radar (DInSAR) technique (referred to as OTD-InSAR). The results from OTD-InSAR show that small-level deformation on the edge of subsidence basin and large-level deformation in the central portion of subsidence basin are measured with high accuracy. The multi-level deformation fusion model considers the geographic information and SAR data information simultaneously to fuse large-level and small-level deformation and use inverse distance weighting method (IDW) to estimate the middle-level deformation. Due to the insufficient measured data in the actual situation, we present the prediction model to forecast the long period deformation evolution of full workface based on the exponent Knothe model and the fusion results. The 52,303 workface in Daliuta coal mining area in China was selected to verify the effectiveness of the fusion model and prediction model. The comparison between the fusion results and the in-situ measured data shows that the root mean square error (RMSE) is less than 0.23 m. Results of deformation prediction model are found to be very close to fusion results and the RMSE is less than 0.027 m. This research work has brought about a comprehensive analysis of the deformation evolution of the full workface with high precision from the beginning to the end of coal mining for about 18 months. As a result, the monitoring results can support the requirements of mining deformation monitoring in the management of surface disaster. [ABSTRACT FROM AUTHOR]