For the first time, the technology of 4D passive microseismic monitoring (MSM) was used to study powerful gas blowout from the Earth's cryolithosphere in the Arctic. In the region of the deep thermokarst Lake Otkrytiye (Discovery), an active strong subvertical gas-hydrodynamic zone was revealed by MSM 4D. Based on the patterns of microseismic events distribution, the migration of formation fluids (primarily gas) was proved from the Cenomanian water-gas-saturated deposits of the Upper Cretaceous with powerful gas eruptions from the bottom of Lake Otkrytiye resulting in the formation of giant craters with a diameter of up to 30-40 m. The MSM 4D method contributes to solving the challenges of preventing and eliminating emergencies of a natural and man-made nature, and therefore belongs to the category of critical technologies.

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Machine learning and digital signal processing methods are used in various industries, including in the analysis and classification of seismic signals from surface sources. The developed wave type analysis algorithm makes it possible to automatically identify and, accordingly, separate incoming seismic waves based on their characteristics. To distinguish the types of waves, a seismic measuring complex is used that determines the characteristics of the boundary waves of surface sources using special molecular electronic sensors of angular and linear oscillations. The results of the algorithm for processing data obtained by the method of seismic observations using spectral analysis based on the Morlet wavelet are presented. The paper also describes an algorithm for classifying signal sources, determining the distance and azimuth to the point of excitation of surface waves, considers the use of statistical characteristics and MFCC (Mel-frequency cepstral coefficients) parameters, as well as their joint application. At the same time, the following were used as statistical characteristics of the signal: variance, kurtosis coefficient, entropy and average value, and gradient boosting was chosen as a machine learning method; a machine learning method based on gradient boosting using statistical and MFCC parameters was used as a method for determining the distance to the signal source. The training was conducted on test data based on the selected special parameters of signals from sources of seismic excitation of surface waves. From a practical point of view, new methods of seismic observations and analysis of boundary waves make it possible to solve the problem of ensuring a dense arrangement of sensors in hard-to-reach places, eliminate the lack of knowledge in algorithms for processing data from seismic sensors of angular movements, classify and systematize sources, improve prediction accuracy, implement algorithms for locating and tracking sources. The aim of the work was to create algorithms for processing seismic data for classifying signal sources, determining the distance and azimuth to the point of excitation of surface waves.

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The article describes the experience of creating a geodatabase of the melioration system of the Kaliningrad region for integration into an agriculture management automated system. The uniqueness of this melioration system is the scale of drainage facilities created during East Prussia time and Soviet period. The characteristic of the current condition of melioration system facilities is given. Actual problems and potential risks in the context of climate change are highlighted. The relevance of digitalization in melioration sector of public administration and in in the context of transboundary cooperation is explained. The primary data model, the structure of cartographic layers, and the composition of attribute information are considered. The features of the initial data and the problems of their preparation are described. The technology of inputting poorly formalized data has been developed. Authors used own service programs for geometry control, topology, and automation of operations, which allows increasing the productivity and accuracy of data input in comparison with standard means of basic geographic information systems. Thematic maps, examples of which are given, are the information basis for monitoring of drained lands of the Kaliningrad region to make environmental and economic management decisions. Promising areas of application of the geodatabase are proposed: geoportal project based on server data storage with using satellite information; project for hydrological modelling of hazardous and catastrophic occurrence in various melioration subsystems. The created geodatabase allows increasing the efficiency of processing and analysis of information about melioration systems on a local and regional scale enables the geographic visualization, helps in melioration management making-decisions.