On 29 January 2019, the collapse of a mine roof resulted in a significant surface deformation and generated a tremor with a magnitude of 4.6 in Rudna Mine, Poland. This study combines the seismological and geodetic monitoring of the event. Data from local and regional seismological networks were used to estimate the mechanism of the source and the ground motion caused by the earthquake. Global Navigation Satellite System data, collected at 10 Hz, and processed as a long-term time-series of daily coordinates solutions and short-term high frequency oscillations, are in good agreement with the seismological outputs, having detected several more tremors. The range and dynamics of the deformed surface area were monitored using satellite radar techniques for slow and fast motion detection. The radar data revealed that a 2-km² area was affected in the six days after the collapse and that there was an increase in the post-event rate of subsidence.

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.

In this study, Differential Interferometric Synthetic Aperture Radar Interferometry (DInSAR) of artificial Corner Reflectors (CRs) were validated in the area of fast and nonlinear deformation gradient caused by active coal longwall exploitation. Three Sentinel-1 datasets were processed using conventional DInSAR, Persistent Scatterer Interferometry (PSI), and Small BAseline Subset methods implemented in ENVI SARscape™. For evaluation, leveling and Global Navigation Satellite System (GNSS) measurements were used. Considering the challenge of snow cover, the removal of all winter images was not a successful strategy due to the long temporal baseline and strong movement, which cause phase unwrapping problems and underestimate the real deformation. The results indicate that only conventional DInSAR and SBAS with low network redundancy allow us to capture maximal deformation gradient and the root mean square error calculated between the CRs and the ground truth is on the level of 2–3 cm for the vertical and easting deformation component, respectively. For the small deformation gradient represented by the permanent GNSS station (4 cm/year), all SBAS techniques appeared to be more accurate than DInSAR, which corresponds to higher redundancy and better removal of the atmospheric signal. In contrast, DInSAR results allowed to capture information about two subsidence basins, which was not possible with SBAS and PSI approaches.

Ground deformations can be determined via various measurement methods, such as levelling, laser scanning, satellite navigation systems, synthetic aperture radar, and many others. In this paper, the authors present cross-validation displacement monitoring results obtained via real-time (RT) and near real-time (NRT) GNSS (Global Navigation Satellite System) calculation scenarios. To verify and validate the quality of RT and NRT long-term displacements, an independent post-processing (P-P) service was established. The study area was located in the Upper Silesian coal mining region in Poland. The verification procedure for the RT and NRT systems included a demonstration of the achieved accuracy, the time span required to detect a significant displacement, and the determination of the minimum detectable value of deformation. Regarding the P-P data source, the NRT service had RMS errors of approximately 2 and 4 mm for the horizontal components, while the RT errors ranged from 5 to 10 mm. In the vertical direction, the NRT strategy had RMS errors of 5-6 mm, while the RT service achieved the accuracy of 10 mm. The minimum detectable values of deformation for the NRT procedure were 5, 7, and 11 mm in the northern, eastern, and up directions, respectively. For the RT system, the significant values were determined to be 10 and 15 mm for the horizontal and 20 mm for the vertical components.

One of the most critical factors which determine the accuracy of deformation maps provided by Differential Synthetic Aperture Radar Interferometry (DInSAR) are atmospheric artefacts. Nowadays, one of the most popular approaches to minimize atmospheric artefacts is Generic Atmospheric Correction Online Service for InSAR (GACOS). Nevertheless, in the literature, the authors reported various effects of GACOS correction on the deformation estimates in different study areas Therefore, this paper aims to assess the effect of GACOS correction on the accuracy of DInSAR-based deformation monitoring in USCB by using Sentinel-1 data. For the accuracy evaluation, eight Global Navigation Satellite Systems (GNSS) permanent stations, as well as five low-cost GNSS receivers were utilized. GACOS-based DInSAR products were evaluated for: (1) single interferograms in different geometries; (2) cumulative deformation maps in various geometries and (3) decomposed results delivered from GACOS-based DInSAR measurements. Generally, based on the achieved results, GACOS correction had a positive effect on the accuracy of the deformation estimates in USCB by using DInSAR approach and Sentinel-1 data in each before mentioned aspect. When considering (1), it was possible to achieve Root Mean Square Error (RMSE) below 1 cm for a single interferogram for only 20% and 26% of the ascending and descending investigated interferograms, respectively when compared with GNSS measurements. The RMSE below 2 cm was achieved by 47% and 66% of the descending and ascending interferograms, respectively.

The determination of ground deformation may be carried out by applying various measurement methods such as levelling, laser scanning, satellite navigation systems, Synthetic Aperture Radar (SAR) and many others. In this work, we focus on the comparison of the deformation effects measured by Global Navigation Satellite Systems (GNSS) and satellite Interferometric SAR (InSAR) methods in the Upper-Silesian coal mining region (SW Poland).An unquestionable advantage of GNSS technology is the possibility of continuous monitoring of deformations in three-dimensional space. Moreover, the evolution of real-time (RT) techniques such as: near real-time (NRT), ultra-fast NRT or RT allows to obtain a high precise position determination with a relatively slight latency (ranging from a few seconds to less than one hour). The limitation of the satellite navigation technology is the spatial range of the measurements. The deformation can only be observed at the point where the GNSS antenna is located. Furthermore, the acquisition, installation and maintenance of the equipment may also involve high costs.In contrast to the GNSS technique, the InSAR methods enable measurement of the large-scale subsidence areas with possibility to use free products and software (e.g. Sentinel-1 and SNAP). The large-scale InSAR investigations provide a better overview of local terrain changes. Unfortunately, InSAR methods also have some limitations related to data acquisition technology:  a few days latency in acquiring a new image, insensitivity to changes in the northern component, acquiring deformation only in the LOS direction. The main goal of this research is to analyse the deformation results obtained using GNSS and InSAR methods with respect to the capabilities and limitations of these two techniques. We investigated the level of agreement of eight GNSS and InSAR time series in areas with no subsidence, together with results acquired on seven regions of mining deformation where the maximum subsidence velocity exceeds 50 cm/year. The mean RMS time series fitting error obtained in subsidence basin is more than 5 cm and in non-deformed areas is equal to 2 cm. The study also investigated the effect of coherence threshold levels (0.3 ÷ 0.6) with introduction of the northern GNSS component on the InSAR decomposition process. Assuming the same GNSS deformation value in each directions (north, east, and up), the impact of the northern component was estimated as 10% of the total LOS subsidence.