The paper presents the results of testing the various methods of permanent stations’ velocity residua interpolation in a regular grid, which constitutes a continuous model of the velocity field in the territory of Poland. Three packages of software were used in the research from the point of view of interpolation: GMT (The Generic Mapping Tools), Surfer and ArcGIS. The following methods were tested in the softwares: the Nearest Neighbor, Triangulation (TIN), Spline Interpolation, Surface, Inverse Distance to a Power, Minimum Curvature and Kriging. The presented research used the absolute velocities’ values expressed in the ITRF2005 reference frame and the intraplate velocities related to the NUVEL model of over 300 permanent reference stations of the EPN and ASG-EUPOS networks covering the area of Europe. Interpolation for the area of Poland was done using data from the whole area of Europe to make the results at the borders of the interpolation area reliable. As a result of this research, an optimum method of such data interpolation was developed. All the mentioned methods were tested for being local or global, for the possibility to compute errors of the interpolated values, for explicitness and fidelity of the interpolation functions or the smoothing mode. In the authors’ opinion, the best data interpolation method is Kriging with the linear semivariogram model run in the Surfer programme because it allows for the computation of errors in the interpolated values and it is a global method (it distorts the results in the least way). Alternately, it is acceptable to use the Minimum Curvature method. Empirical analysis of the interpolation results obtained by means of the two methods showed that the results are identical. The tests were conducted using the intraplate velocities of the European sites. Statistics in the form of computing the minimum, maximum and mean values of the interpolated North and East components of the velocity residuum were prepared for all the tested methods, and each of the resulting continuous velocity fields was visualized by means of the GMT programme. The interpolated components of the velocities and their residua are presented in the form of tables and bar diagrams.

Wrocław is a major city located in the southwestern part of Poland in an aseismic tectonic fault zone. Slow, long-term, vertical displacements have been observed there from the 1930s based on the levelling network measurements with the use of a precise levelling method. Due to the high cost of classic surveys, these were performed at intervals of several decades and the most recent measurement of ground surface displacement was performed in 1999. The main aim of this study is to determine the ground surface displacements on the area of Wrocław in the 1995–2019 period, the spatio-temporal analysis of deformations and the identification of the potential factors causing these deformations. To determine the ground movements, an advanced PSI technique and data from ERS-2, Envisat, and Sentinel-1 sensors were used. Application of SAR technology for the first time in this area, provided new knowledge about the process of deformation in short time intervals over the entire area of the city. The results verify the hypothesis on the linearity of displacements obtained from historical geodetic observations. The obtained results show that the displacements, which continue to occur in the area of Wrocław have a cyclic character with 4–5 year long period of subsidence and 2–3 year long periods of stabilization or uplift. The displacement trends indicate that the area of the city gradually subsides in relation to the reference area located on the Fore-Sudetic Block.

In this paper, the regionalization of geographical space according to selected topographic factors and the spatial distribution of precipitation is discussed. The model takes into account qualitative and quantitative data describing the conditions associated with the studied precipitation. In the modelling, data mining methods including data clustering methods for agglomeration and artificial neural networks for classification have been used. The reason for their use was the classification of the area due to conditions related to precipitation, the distinguishing of similar areas and the delimitation of the propagation of the phenomenon or transition zones. To realize the research aims, professional software for data management, spatial data analysis, mathematical calculations and data mining have been used. The result of the research was a model of the classes representing areas with specific conditions affecting the phenomenon, transition zones between classes and areas with conditions other than those in the surroundings of the measuring stations, which are not classified in any of the classes. Classification results indicate the boundaries of the areas in which we can model the values measured at stations, the transition zones of possible discontinuous change and areas in which the phenomenon should not be modelled due to significantly different conditions from those in the neighbourhoods of measuring stations. Unclassified areas are also potential locations for new measuring stations.

Nowadays, satellite remote sensing produces vast amounts of Earth observation data, but without appropriate processing, visualization and interpretation, they are of limited use for a regular user. Web map applications are one of the approaches to share the data online. They allow not only for visualization, but also for analysis and interaction with geographic data. Such web services are used for a variety of purposes, fulfilling informational and educational roles. The SARforMINE is a geoportal service for monitoring, analysis and visualisations of predictive modelling of environmental impacts above underground gas storage facilities. The designed web map application represents information on selected environmental components, ground movements and vegetation condition derived from open-access satellite imagery, SAR and optical respectively. Additionally, historical data are analysed using machine learning for the purpose of predictive modelling of the potential future changes. The proposed approach outlines how web GIS services can augment traditional monitoring of underground gas storage sites.