THE PECULIARITIES OF AUTOMATED DECODING OF SPACE IMAGES OF AGRICULTURAL LAND (ON THE EXAMPLE OF THE KIPTIV TERRITORIAL COMMUNITY) - Zatserkovnyi, V.; Babiy, V.; Skorobagatko, A. (Bulletin of Taras Shevchenko National University of Kyiv. Military-special sciences, 2020)
Historically, the role of agriculture in our country is quite large, and recently, after some decline, there’s a growing interest to this segment of the economy. This is usually due to a change in Ukraine’s land policy, with an owner appearing in the land who is interested in its optimal use. Huge areas of agricultural land are difficult to control due to a lack of accurate maps, an underdeveloped network of operational monitoring points, ground stations, including meteorological ones, a lack of aviation support due to expensive maintenance, and so on. In addition, due to various natural processes, the boundaries of sown areas, soil characteristics and growing conditions in different fields and from plot to plot are constantly changing. All these factors prevent the receipt of objective operational information necessary to ascertain the current situation, its assessment and forecasting. And without this it is almost impossible to increase agricultural production, optimize land use, forecast the harvest, reduce costs and increase profitability. Abroad, similar problems are successfully solved with the use of data from aerial and space imagery, as well as the widespread use of satellite navigation during crop and harvest monitoring, to study the state of vegetation and forecast the productivity of crops.The agricultural sector is one of the most promising industries in Ukraine, for which it is advisable to use remote sensing data, which provide detailed and necessary information that greatly simplifies the work of research and analysis of agricultural land productivity. Space images well reflect the boundaries of sown areas, it is possible to track the dynamics of crops, analysis of crop rotation and much more. According to the results of the work, a number of features of automated decoding of agricultural lands were formed.
Keywords: remote sensing of the Earth, decryption, agriculture