Search academic texts

Information × Registration Number 0223U002956, 0121U108443 , R & D reports Title Information and analytical support of land resources management popup.stage_title Head Ibatullin Shamil I., д.е.н. Registration Date 20-03-2023 Organization Institut of Land Use NAAS Ukraine popup.description2  In order to justify information needs and requirements in accordance with the functions of management in the field of land use, including taking into account armed aggression in Ukraine, it is proposed to take into account the need to ensure food security of Ukraine through constant monitoring and analysis of available land resources, actual and forecast structure of cultivated areas. Among the collection and analysis tools, it is proposed to use remote sensing of the Earth and geo-information technologies, including solving problems: determining the boundaries of agricultural land massifs; identification of infrastructure objects and areas under natural resources that were damaged during hostilities and shelling; assessment of the availability of sown areas for their involvement in agricultural production; identification of boundaries and areas of crops under individual agricultural crops according to vegetation phases; analysis of the volume and structure of cultivated areas in a territorial section with forecasts of yield and gross harvest of agricultural crops using vegetation indices. Methodological principles and information requirements for data collection and processing in land resource management, including data from remote sensing of the Earth, have been developed. The composition and content of the reporting forms of field ground observations are proposed, taking into account the requirements for spatial and attributive information on the state and phases of vegetation of agricultural crops. Such reporting forms make it possible to form the informational and analytical basis necessary for monitoring agricultural crops using remote sensing of the Earth. A number of algorithms have been developed for the classification of agricultural crops using remote sensing of the Earth, which include the stages of unsupervised classification using the K-means method and controlled classification using the Random Forest method. Simultaneous use of Sentinel-1 and 2. Product Description popup.authors Avramchuk Bohdan O. BRATINOVA MARIIA V Dorosh Yosyp Myroslavovych Melnyk Denys M. Novakovska Iryna Oleksiivna Sakal Oksana Volodymyrivna Kharytonenko Roman A. popup.nrat_date 2023-03-20 Close