The issue of monitoring surface motions in post-mining areas in Europe is important due to the fact that a significant number of post-mining areas lie in highly-urbanized and densely-populated regions. Examples can be found in: Belgium, the Czech Republic, France, Germany, the Netherlands, Spain, the United Kingdom, as well as the subject of this study, the Polish Walbrzych Hard Coal Basin. Studies of abandoned coal fields show that surface deformations in post-mining areas occur even several dozen years after the end of underground coal extraction, posing a threat to new development of these areas. In the case of the Walbrzych area, fragmentary, geodetic measurements indicate activity of the surface in the post-mining period (from 1995 onward). In this work, we aimed at determining the evolution of surface deformations in time during the first 15 years after the end of mining, i.e., the 1995–2010 period using ERS 1/2 and Envisat satellite radar data. Satellite radar data from European Space Agency missions are the only source of information on historical surface movements and provide spatial coverage of the entirety of the coal fields. In addition, we attempted to analyze the relationship of the ground deformations with hydrogeological changes and geological and mining data. Three distinct stages of ground movements were identified in the study. The ground motions (LOS (Line Of Sight)) determined with the PSInSAR (Persistent Scatterer Interferometry) method indicate uplift of the surface of up to +8 mm/a in the first period (until 2002). The extent and rate of this motion was congruent with the process of underground water table restoration in separate water basins associated with three neighboring coal fields. In the second period, after the stabilization of the underground water table, the surface remained active, as indicated by local subsidence (up to −5 mm/a) and uplift (up to +5 mm/a) zones. We hypothesize that this surface activity is the result of ground reaction disturbed by long-term shallow and deep mining. The third stage is characterized by gradual stabilization and decreasing deformations of the surface. The results accentuate the complexity of ground motion processes in post-mining areas, the advantages of the satellite radar technique for historical studies, and provide information for authorities responsible for new development of such areas, e.g., regarding potential flood zones caused by restoration of groundwater table in subsided areas.

The article presents the results of applying a Small Baseline Subset (SBAS) method to the monitoring of the influence of underground mining exploitation on terrain surface. Calculations were performed on the basis of two large SAR data sets. Calculations of time series additionally employed the Tymofyeyeva and Fialko empirical method for estimating atmospheric delay. A series of test calculations allowed verifying the potential of the method. The SBAS calculations were based on theoretical data prepared with the use of the Mogi model. This approach allowed simulating both underground mining exploitation and induced tremors. The results indicate that the model is useful in detecting sudden ground surface deformations. In such a situation, the image of a tremor can be observed in the atmospheric component. The actual data used in the analysis covered a region of underground copper ore extraction in southwest Poland. The calculations were based on SAR data obtained from the Sentinel 1A/B satellites, for the period between the end of 2014 and May 2018, from paths 22 and 73. In both cases, the total number of images exceeded 120. They served to calculate over 420 interferograms for each set. The results of ground surface displacements allowed precise identification of areas affected by underground mining activity. Over the acquisition period of six days, sufficient amount of SAR data was obtained to precisely monitor surface changes in the analyzed area. The employed empirical atmospheric delay reduction method was demonstrated to enable the detection of sudden ground surface changes due to mining tremors. This feature makes the method useful in detecting induced seismic events in areas characterized by intensive mining activity. It allows determining tremor locations in cases when acquisition dates are greater than the optimal value of 6–12 days (in the case of Sentinel 1A/B).

The paper presents the concept of the deformation information system (DIS) to support and facilitate studies of mining-ground deformations. The proposed modular structure of the system includes data collection and data visualisation components, as well as spatial data mining, modelling and classification modules. In addition, the system integrates interactive three-dimensional models of the mines and local geology. The system is used to calculate various parameters characterising ground deformation in space and time, i.e. vertical and horizontal displacement fields, deformation parameters (tilt, curvature, and horizontal strain) and input spatial variables for spatial data classifications. The core of the system in the form of an integrated spatial and attributive database has been described. The development stages and the functionality of the particular components have been presented and example analyses utilising the spatial data mining and modelling functions have been shown. These include, among other things, continuous vertical and horizontal displacement field interpolations, calculation of parameters characterising mining-ground deformations, mining-ground category classifications, data extraction procedures and data preparation preprocessing procedures for analyses in external applications. The DIS has been developed for the Walbrzych coal mines area in SW Poland where long-time mining activity ended at the end of the 20th century and surface monitoring is necessary to study the present-day condition of the former mining grounds.

In this article, we present a possible approach to use satellite radar data for a complete description of the formation process of a subsidence trough resulting from an induced seismic event—a mining tremor. Our main goal was to verify whether SAR data allow for the calculation of the basic indicators for the trough (w—subsidence, T—trough slope, K—curvature, u—horizontal displacements, $\epsilon$—horizontal deformations). We verified the extent to which the Mogi and Yang models can be fitted to match the actual displacements recorded after an induced seismic tremor. The calculations were performed for the Legnica-Glogow Copper Belt (LGCB) area in southwest Poland. Due to intensive mining operations and specific geological and tectonic conditions, the area shows a high level of induced seismic activity. Our detailed analysis focused on four powerful mining tremors: the first tremor occurred on 29 November 2016 (M${}_W$3.4), the second on 7 December 2017 (M${}_W$3.3), the next on 26 December 2017 (M${}_W$3.6) and the last tremor on 29 January 2019 (M${}_W$3.7). For each analyzed event, we determined the displacements based on the Differential Interferometric Synthetic Aperture Radar (DInSAR) method and Sentinel 1 synthetic aperture radar (SAR) data from two paths (22 and 73). Additionally, for the period from November 2014 to October 2020, we calculated the displacements using the Small Baseline Subset method (SBAS) time series method. In all cases, the tremor was followed by the development of long-lasting surface deformations. The obtained results allowed us to conclude that it is possible to calculate indicators that result from a specific induced mining event. Considering the full moment tensor and nature of the tremor source, we demonstrated that the Mogi and Yang models can be employed to describe the influence of an induced tremor on the surface in an area of mining activity. We also confirmed the global character of the influence of the reduced troposphere on SAR data calculations. Our conclusions indicate that accounting for the tropospheric correction does not distort horizontal and vertical displacement values in regions influenced by mining activity/tremors.

Open access to SAR data from the Sentinel 1 missions allows analyses of long-term ground surface changes. The current data-acquisition frequency of 12 days facilitates the continuous monitoring of phenomena such as volcanic and tectonic activity or mining-related deformations. SAR data are increasingly also used as input data in forecasting phenomena on the basis of machine learning. This article presents the possibility of using selected machine learning algorithms in forecasting the influence of underground mining activity on the ground surface. The study was performed for a mining protective area with a surface of over 500 km${}^2$ and located in western Poland. The ground surface displacements were calculated for the period from November 2014 to July 2021, with the use of the Small Baseline Subset (SBAS) method. The forecasts were performed for a total of 22 identified subsidence troughs. Each of the troughs was provided with two profiles, with a total of more than 10,000 identified points. The selected algorithms served to prepare 180-day displacement forecasts. The best results (significantly better than the baseline) were obtained with the ARIMA and Holt models. Linear models also provided better results than the baseline and their performance was very good at up to 2 months forecasting. Tree-based models including their sophisticated ensemble versions: bagging (Random Forest, Extra Trees) and boosting (XGBoost, LightGBM, CatBoost, Gradient Boosting, Hist Gradient Boosting) cannot be used for this type of predictions since Decision Trees are not able to extrapolate and thus are not a valid stand-alone tool for forecasting in this type of problems. A combination of satellite remote sensing data and machine learning facilitated both the simultaneous quasi-permanent monitoring of ground surface displacements and their forecasting in a relatively long time period.