Mining Deformation Life Cycle in the Light of InSAR and Deformation Models

Ilieva, Maya; Polanin, Piotr; Borkowski, Andrzej; Gruchlik, Piotr; Smolak, Kamil; Kowalski, A.; Rohm, Witold

doi:10.3390/rs11070745

Cited by 43 publications

(32 citation statements)

References 37 publications

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“…In contrast, consecutive DInSAR was able to capture fast deformation that reached −1.0 m in the vertical direction. Similar results were obtained in [4,7], in which the convergence of DInSAR results and mining modeling for USCB mines was studied. The deformation time series generated for selected points in large deformation spots demonstrate a reasonable agreement with the Knothe mining deformation model (e.g., see [4]) for spots (a) and (c) (Figure 9).…”

Section: Comparison Between Sbas and Dinsar Deformation Estimation Ansupporting

confidence: 78%

“…Thus, we do not describe interferometric principles in this work. Many studies have demonstrated the effective application of DInSAR for monitoring fast terrain displacements [4][5][6][7][8]. DInSAR provides reliable results when the displacement rate is much higher than atmospheric artifacts [35].…”

Section: Multi-temporal Consecutive Dinsar Processingmentioning

confidence: 99%

“…DInSAR provides reliable results when the displacement rate is much higher than atmospheric artifacts [35]. Despite these atmospheric artifacts, studies have effectively applied conventional DInSAR techniques [4,9,33]. Two methods of DInSAR exist, namely consecutive DInSAR and cumulative DInSAR.…”

Section: Multi-temporal Consecutive Dinsar Processingmentioning

confidence: 99%

“…If some errors appear in any of the estimated displacements (residual terrain, atmospheric delay, and other phases error) in the interferograms, then they propagate in the subsequent time-series deformation results in the accumulation process [31]. Nevertheless, many studies have reported the successful application of consecutive DInSAR for subsidence monitoring [4,7,33,36].…”

Section: Multi-temporal Consecutive Dinsar Processingmentioning

confidence: 99%

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Integration of DInSAR and SBAS Techniques to Determine Mining-Related Deformations Using Sentinel-1 Data: The Case Study of Rydułtowy Mine in Poland

2020

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Underground coal exploitation often results in land-surface subsidence, the rate of which depends on geological characteristics, the mechanical properties of the rocks, and the applied extraction technology. Since mining-related subsidence is characterized by “fast” displacement and high nonlinearity, monitoring this process by using Interferometric Synthetic Aperture Radar (InSAR) is very challenging. The Small BAseline Subset (SBAS) approach needs to predefine an a priori deformation model to properly estimate an interferometric component related to displacements. As a consequence, there is a lack of distributed scatterers (DS) when the selected a priori deformation model deviates from the real deformation. The conventional differential SAR interferometry (DInSAR) approach does not have this limitation, since it does not need any deformation model. However, the accuracy of this technique is limited by factors related to spatial and temporal decorrelation, signal delays due to the atmospheric artifacts, and orbital or topographic errors. Therefore, this study presents the integration of DInSAR and SBAS techniques in order to leverage the advantages and overcome the disadvantages of both methods and to retrieve the complete deformation pattern over the investigated study area. The obtained results were evaluated internally and externally with leveling data. Results indicated that the Kriging-based integration method of DInSAR and SBAS can be effectively applied to monitor mining-related subsidence. The root-mean-square Error (RMSE) between modeled and measured deformation by InSAR was found to be 11 and 13 mm for vertical and horizontal displacements, respectively. Moreover, DInSAR technique as a cost-effective and complementary method to conventional geodetic techniques can be applied for effective monitoring fast mining subsidence. The minimum and maximum RMSE between DInSAR displacement and specific leveling profiles were found to be 0.9 and 3.2 cm, respectively. Since the SBAS processing failed in subsidence estimation in the area of maximum deformation rate, the deformation estimates outside the maximum rate could only be compared. In these areas, the good agreement between SBAS and DInSAR indicates that the SBAS technique could be reliable for monitoring the residual subsidence that surrounds the subsidence trough. Using the proposed approach, we detected subsidence of up to −1 m and planar displacements (east–west) of up to 0.24 m.

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Section: Comparison Between Sbas and Dinsar Deformation Estimation Ansupporting

confidence: 78%

Section: Multi-temporal Consecutive Dinsar Processingmentioning

confidence: 99%

Section: Multi-temporal Consecutive Dinsar Processingmentioning

confidence: 99%

Section: Multi-temporal Consecutive Dinsar Processingmentioning

confidence: 99%

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Integration of DInSAR and SBAS Techniques to Determine Mining-Related Deformations Using Sentinel-1 Data: The Case Study of Rydułtowy Mine in Poland

2020

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“…Upper Silesian Coal Basin (USCB) which is located in Southern Poland covers an area of almost 6000km 2 (Przyłucka et al, 2016). Coal exploitation in the USCB dated back the nineteenth century (Ilieva et al, 2019). Coal exploitation performed underground has its consequence in ground movements such as subsidence, sinking or shaking (Mutke et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Psi and Dinsar Approach for the Subsidence Monitoring Caused by Coal Mining Exploitation

Pawłuszek-Filipiak

Borkowski

2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Underground coal exploitation has its reflection in ground movements such as subsidence, sinking or shaking. These cause buildings and infrastructure damage, therefore it is important to measure the magnitude of deformation. Last decades, Differential Interferometric Synthetic Aperture Radar (DInSAR) captured considerable attention as a tool for deformation monitoring. The results of conventional DInSAR, which utilizes two SAR images, are degraded due to atmospheric, topographic and orbital errors. To overcome these limitations, various stacking-based methods have been introduced. Therefore, the goal of presented study is to compare Persistent Scatterer Interferometry (PSI) as stacking-based method with classical DInSAR for monitoring of subsidence caused by underground coal exploitation. Deformations in the areas of active mining exploitation are characterised typically by rapid non-linear movement. The comparison has been performed for the area of active exploitation in Rydułtowy mine located in Upper Silesian Coal Basin (USCB) in Poland. Results from two separate PSI and DInSAR processing portray similar deformation pattern over the study area. Unfortunately, due to the temporal decorrelation, PSI clearly demonstrate smaller information coverage in respect to DInSAR results. Additionally, due to the applied linear deformation model, PSI failed in displacement estimation with magnitude higher than 12 cm. In contrast, DInSAR thanks 6-day temporal baseline and no assumption for a deformation model, was able to capture the maximum magnitude of subsidence reaching 86 cm/year. However, these results are affected by atmospheric artefacts which in presented case study can reach even 14 cm/year. To achieve few cm level of accuracy and to estimate high deformation magnitude such as in presented study case (1m/year), integrated use of both InSAR techniques seems to be the reasonable solution.

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Kalman filter-based integration of GNSS and InSAR observations for local nonlinear strong deformations

Tondaś,

Ilieva,

van Leijen

et al. 2023

J Geod

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The continuous monitoring of ground deformations can be provided by various methods, such as leveling, photogrammetry, laser scanning, satellite navigation systems, Synthetic Aperture Radar (SAR), and many others. However, ensuring sufficient spatiotemporal resolution of high-accuracy measurements can be challenging using only one of the mentioned methods. The main goal of this research is to develop an integration methodology, sensitive to the capabilities and limitations of Differential Interferometry SAR (DInSAR) and Global Navigation Satellite Systems (GNSS) monitoring techniques. The fusion procedure is optimized for local nonlinear strong deformations using the forward Kalman filter algorithm. Due to the impact of unexpected observations discontinuity, a backward Kalman filter was also introduced to refine estimates of the previous system’s states. The current work conducted experiments in the Upper Silesian coal mining region (southern Poland), with strong vertical deformations of up to 1 m over 2 years and relatively small and horizontally moving subsidence bowls (200 m). The overall root-mean-square (RMS) errors reached 13, 17, and 35 mm for Kalman forward and 13, 17, and 34 mm for Kalman backward in North, East, and Up directions, respectively, in combination with an external data source - GNSS campaign measurements. The Kalman filter integration outperformed standard approaches of 3-D GNSS estimation and 2-D InSAR decomposition.

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Mining Deformation Life Cycle in the Light of InSAR and Deformation Models

Cited by 43 publications

References 37 publications

Integration of DInSAR and SBAS Techniques to Determine Mining-Related Deformations Using Sentinel-1 Data: The Case Study of Rydułtowy Mine in Poland

Integration of DInSAR and SBAS Techniques to Determine Mining-Related Deformations Using Sentinel-1 Data: The Case Study of Rydułtowy Mine in Poland

Comparison of Psi and Dinsar Approach for the Subsidence Monitoring Caused by Coal Mining Exploitation

Kalman filter-based integration of GNSS and InSAR observations for local nonlinear strong deformations

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