Georgii Korepanov’s research while affiliated with Riga Technical University and other places

The study is focused on gathering information to monitor sustainable land development and biodiversity. The article discusses the objectives and measures required to achieve Sustainable Development Goal 15 “Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss”. This paper shows the results of the analysis of key indicators and values for Ukraine. It also contains the developed conceptual diagram for managing the sustainable development of ecosystems and biodiversity. There were identified the main sources of statistical information, including traditional enterprise-level data and big data, and analyzed changes in indicators for monitoring the achievement of the Sustainable Development Goals at micro level under section “Environmental area”. The study also identified potential sources of information for calculating the presented indicators and explored the use of big data to develop an information base for monitoring, evaluating, and policy development related to sustainable land development and biodiversity. Further research and studies are needed to determine the algorithms of data processing, modelling and constructing of integrated indicators.

The article addresses the problems related to the functioning of the worldwide market of wheat and meslin. The authors identify the countries that over the past 17 years have been among the top 10 world leaders in terms of the value of export and import of wheat and meslin. The structure of wheat export by Ukrainian regions is analysed in comparison with the total export. The localisation coefficient is applied to measure the regional unevenness of the distribution of wheat export volumes and the total export by regions of the country. The modelling and forecasting of the volumes and prices of export of wheat and meslin from Ukraine are based on Singular Spectrum Analysis. The study particularly focuses on the individual components of time series, such as trend, annual, semi-annual, four-month, three-month seasonal components. The reliability of the forecast is confirmed by the calculation of the MAPE forecast error and Henry Theil’s inequality coefficient. The article proposes an algorithm for calculating the relative indicators of the structure for the individual components of the reconstructed time series, identified through the singular spectral analysis.

To make informed decisions, modern society, like modern business, must operate with adequate information about many complex interrelated aspects of its activities. Land use is only one of such aspects. Agricultural lands are of particular importance today. Land data are needed to analyse environmental processes, as well as end unsystematic, uncontrolled use of agricultural land, environmental degradation, destruction of important wetlands, loss of fish diversity and destruction of wildlife habitats. To solve these problems, it is advisable to conduct regular analysis and evaluation of land resources, justification and analysis of factors influencing the agricultural land market in the country. The tasks were solved using multidimensional statistical methods, in particular, factor analysis, which helped to get rid of subjectivity in the choice of factors influencing the market under study. Based on the model of influence of factors on the national market of agricultural land in Ukraine, six main factors were identified, the most influential of which were the components of agricultural development (first factor) and, to a lesser extent, the component of vegetable production and yield (fourth factor). The interrelationships and the degree of influence of the selected factors on the main indicators of the agricultural land market, namely, on the area of purchase and sale plots, the price of purchase and sale plots, and the number of transactions were also analysed.