Every year, the world faces new difficult challenges in maintaining global security. Compliance with food security principles is an important component of the global context of world development. Recent military conflicts have had a strong impact on the development of regions that provide food for millions of people around the world. Ukraine plays a key role in providing agricultural products to the population of countries from different continents. The article is devoted to the study of the state of agricultural crops in a regional section during the period of active hostilities by means of geomatics, which allow one to assess the degree of transformation of sustainable farming quickly, determine the trend of the development of the industry, and calculate the likely scale of changes in the obtained products in the coming years. As a result, with the help of deep learning models integrated into geoinformation systems, the boundaries of agricultural fields in the Kherson and Zaporizhia regions were determined, the state of moisture and bioproductivity of agricultural crops was determined for three years, an analysis of changes has been made in the state of agricultural fields under the influence of new factors of conducting active hostilities during the first half of 2022, the next harvest productivity forecast was made in two southern regions of Ukraine. The study was carried out by the team of the World Data Center for Geoinformatics and Sustainable Development of the Igor Sikorsky Kyiv Polytechnic Institute. It was part of research on the analysis of the behavior of complex socio-economic systems and processes of sustainable development in the context of the quality and safety of people’s lives.
When assessing the level of development of territories, the problem of finding objective qualitative data that will characterize it arises. One of the possible sources of such data is the remote sensing of the Earth (RSE). The article is devoted to the analysis of the possibility of using the product of RSE – the map of night lights, for modeling the economical dimension of the sustainable development of the regions of Ukraine. Using the regression and correlation analysis and neural networks, appropriate models for assessing the level of economic development of the Kherson region, Donetsk region, and the AR of Crimea were obtained. The study was carried out by the team of the World Data Center for Geoinformatics and Sustainable Development of the Igor Sikorsky Kyiv Polytechnic Institute. It was part of research on the analysis of the behavior of complex socio-economic systems and processes of sustainable development in the context of the quality and safety of people’s lives.
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