Improving PSI Processing of Mining Induced Large Deformations with External Models

Abstract

Ground subsidences, either caused by natural phenomena or human activities, can threaten the safety of nearby infrastructures and residents. Among the different causes, mining operations can trigger strong subsidence phenomena with a fast nonlinear temporal behaviour. Therefore, a reliable and precise deformation monitoring is of great significance for safe mining and protection of facilities located above or near the mined-out area. Persistent Scatterer Interferometry (PSI) is a technique that uses stacks Synthetic Aperture Radar (SAR) images to remotely monitor the ground deformation of large areas with a high degree of precision at a reasonable cost. Unfortunately, PSI presents limitations when monitoring large gradient deformations when there is phase ambiguity among adjacent Persistent Scatterer (PS) points. In this paper, an improvement of PSI processing, named as External Model-based Deformation Decomposition PSI (EMDD-PSI), is proposed to address this limitation by taking advantage of an external model. The proposed method first uses interferograms generated from SAR Single Look Complex (SLC) images to optimize the parameter adjustments of the external model. Then, the modelled spatial distribution of subsidence is utilized to reduce the fringes of the interferograms generated from the SAR images and to ease the PSI processing. Finally, the ground deformation is retrieved by jointly adding the external model and PSI results. In this paper, fourteen Radarsat-2 SAR images over Fengfeng mining area (China) are used to demonstrate the capabilities of the proposed method. The results are evaluated by comparing them with leveling data of the area covering the same temporal period. Results have shown that, after the optimization, the model is able to mimic the real deformation and the fringes of the interferograms can be effectively reduced. As a consequence, the large gradient deformation then can be better retrieved with the preservation of the nonlinear subsidence term. The ground truth shows that, comparing with the classical PSI and PSI with unadjusted parameters, the proposed scheme reduces the error by 35.2% and 20.4%, respectively.

A Novel Phase Unwrapping Method Used for Monitoring the Land Subsidence in Coal Mining Area Based on U-Net Convolutional Neural Network

“…After underground coal mining, a series of goaf will be formed (Hu et al, 2013;Yang et al, 2018). In the InSAR interferograms, it is usually manifested as a series of concentric circles or concentric ellipses with similar shapes (Du et al, 2019;Wang et al, 2021). According to the principle of phase unwrapping (Chiglia and Pritt, 1998;Yu et al, 2019), the number of phase-jump (or wrap-count) is calculated by the interferometric fringes of subsidence basin and the phase unwrapping is realized through adding or subtracting 2N in the position corresponded to the interferogram.…”

“…Low coherence, excessive deformation gradient, interferometric phase discontinuity caused by large displacement, and the atmospheric effect will influence the accuracy of InSAR technology when monitoring the deformation in the mining area (Chen et al, 2021). The deformation in the mining area is special, which is mainly characterized by uneven settlement rate, large deformation in the mining area, and small and dispersive settlement range (Fan et al, 2014;Du et al, 2016;Du et al, 2019). In addition, the surface of the mining area is mostly covered by vegetation and farmland, which leads to the low coherence of interferometric pair.…”

“…A solution was proposed to obtain complete deformation fields using the probability integral method to fuse deformation data derived from differential interferometric SAR (D-InSAR), sub-band InSAR, and offset-tracking (Wang et al, 2020). Du et al used the probability integral method (PIM) and D-InSAR to locate the goaf (Du et al, 2019). An improvement of PSI processing, named as external modelbased deformation decomposition PSI (EMDD-PSI) was proposed to address the limitations when monitoring large gradient deformations when there is phase ambiguity (Du et al, 2020).…”

“…Du et al used the probability integral method (PIM) and D-InSAR to locate the goaf (Du et al, 2019). An improvement of PSI processing, named as external modelbased deformation decomposition PSI (EMDD-PSI) was proposed to address the limitations when monitoring large gradient deformations when there is phase ambiguity (Du et al, 2020). Liu et al obtained the spatial-temporal characteristics of land subsidence caused by drilling solution mining activities using the time-series analysis (Liu et al, 2019).…”

“…With the continuous development of InSAR technology, the applications of InSAR technology for monitoring the mine subsidence are also increasing. The main research directions have evolved from obtaining single surface deformation information to parameter inversion or subsidence prediction based on deformation theory (Du et al, 2019;Sui et al, 2020;Wang et al, 2020). Most of these works are targeted at one or more subsidence basins, which have high requirements on the interferogram and phase unwrapping quality of the interferometric pair.…”