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Underground extraction can be roughly classified into three types, i.e., subcritical, critical, and supercritical extraction, in accordance with the geological conditions in the overburden and the geometry of mined-out areas. In 2016, we proposed an approach based on the interferometric synthetic aperture radar (InSAR) technique and the probability integral method (PIM) for the cost-effective prediction of 3-D mining-induced displacements (abbreviated as InSAR-PIM). Due to the inherent assumption of critical extraction in the PIM, the InSAR-PIM method performs well in predicting the 3-D displacements caused by critical and/or supercritical extraction, but poorly for subcritical extraction. In this paper, we first propose a generalized PIM (GPIM) by modifying the traditional PIM with a simplified Boltzmann function. We then replace the PIM of the InSAR-PIM with the proposed GPIM to develop an extension of InSAR-PIM (referred as to InSAR-GPIM). The InSAR-GPIM was tested in the Qianyingzi coal mining area, China. The results show that the InSAR-GPIM-predicted horizontal and vertical displacements caused by subcritical, critical, and supercritical extraction agree well with the in situ observations, with average root-mean-square errors of about 0.032 and 0.050 m, respectively. These accuracies represent improvements of 60.9% and 59% when compared with the accuracies predicted by the InSAR-PIM in the horizontal and vertical directions. The results indicate that the InSAR-GPIM is capable of accurately predicting 3-D mining-induced displacements under different extraction conditions (i.e., subcritical, critical, and supercritical extraction), and it performs much better than the InSAR-PIM in the case of subcritical extraction. It is therefore believed that InSAR-GPIM will have a wider scope of applications than the previous InSAR-PIM. [ABSTRACT FROM PUBLISHER]

Due to the side-looking imaging geometry of the current synthetic aperture radar (SAR) sensors, only ground deformation along the radar's line-of-sight (LOS) and azimuth directions can be potentially obtained from a single amplitude pair (SAP) of SAR using offset tracking (OT) procedures. This significantly hinders the accurate assessment of mining-related hazards and better understanding of the mining subsidence mechanism. In this paper, we propose a method for completely retrieving three-dimensional (3-D) mining-induced displacements with OT-derived observations of LOS deformation from a single amplitude pair of SAR (referred to as OT-SAP hereinafter). The OT-SAP method first constructs two extra constraints at each pixel of the mining area based on the proportional relationship between the horizontal motion of the mining area and the gradients of the vertical subsidence in the east and north directions. The full 3-D mining-induced displacements are then solved by coupling the two constructed extra constraints with the OT-derived observations of the LOS deformation. The Daliuta coal mining area in China was selected to test the proposed OT-SAP method. The results show that the maximum 3-D displacements of this mining area were about 4.3 m, 1.1 m, and 1.3 m in the vertical, east, and north directions, respectively, from 21 November 2012 to 6 February 2013. The accuracies of the retrieved displacements in the vertical and horizontal directions are about 0.201 m and 0.214 m, respectively, which are much smaller than the mining-induced displacements in this mining area and can satisfy the basic requirements of mining deformation monitoring. [ABSTRACT FROM AUTHOR]

It is crucial to locate underground goafs (i.e., mined-out areas) resulting from coal mining and define their spatial dimensions for effectively controlling the induced damages and geohazards. Traditional geophysical techniques for locating and defining underground goafs, however, are ground-based, labour-consuming and costly. This paper presents a novel space-based method for locating and defining the underground goaf caused by coal extraction using Interferometric Synthetic Aperture Radar (InSAR) techniques. As the coal mining-induced goaf is often a cuboid-shaped void and eight critical geometric parameters (i.e., length, width, height, inclined angle, azimuth angle, mining depth, and two central geodetic coordinates) are capable of locating and defining this underground space, the proposed method reduces to determine the eight geometric parameters from InSAR observations. Therefore, it first applies the Probability Integral Method (PIM), a widely used model for mining-induced deformation prediction, to construct a functional relationship between the eight geometric parameters and the InSAR-derived surface deformation. Next, the method estimates these geometric parameters from the InSAR-derived deformation observations using a hybrid simulated annealing and genetic algorithm. Finally, the proposed method was tested with both simulated and two real data sets. The results demonstrate that the estimated geometric parameters of the goafs are accurate and compatible overall, with averaged relative errors of approximately 2.1% and 8.1% being observed for the simulated and the real data experiments, respectively. Owing to the advantages of the InSAR observations, the proposed method provides a non-contact, convenient and practical method for economically locating and defining underground goafs in a large spatial area from space. [ABSTRACT FROM AUTHOR]