The article proves a particular bias in the agricultural land use for assessing the ecological and economic efficiency of only cost indicators. The methodology for evaluating the ecological and economic efficiency of agricultural land use by the energy content of foods is considered. The purpose of the article is to consider the methodology and justification of the practical significance of assessing the environmental and economic efficiency of the agricultural land use by the energy content of products. The article presents the initial data for correlation-regression analysis on the average performance of agricultural producers of Ukraine to determine the weight of each indicator.We used land statistical collections, National reports on the state of the environment in Ukraine for the period 2012–2018. The analysis was carried out based on the average performance indicators of agricultural producers of Ukraine to determine the weight of factors and leverage on the ecological and economic efficiency of agricultural land use. The output of a unit of land in relative terms through exchange energy is not only a kind of indicator, a criterion for the efficient use of agricultural land but also a criterion for the effectiveness of all production activities of agricultural producers, a particular district, and even regions. The main advantage of the proposed approach is the focus on achieving the ultimate goal of agricultural production, which allows us to recommend it for extended use in assessing the ecological and economic efficiency of agricultural land use.

The object of the study is the processing of space images on the territory of the Carpathian territory in the Lviv region, obtained from the Landsat-8 satellite. The work aims to determine the area of deforestation in the Carpathian territory of the Lviv region from different time-space images obtained from the Landsat-8 satellite. Methods of cartography, photogrammetry, aerospace remote sensing of the Earth and GIS technology were used in the experimental research. The work was performed in Erdas Imagine software using the unsupervised image classification module and the DeltaCue difference detection module. The results of the work are classified as three images of Landsat-8 on the territory of the Carpathian territory in the Lviv region. The areas of forest cover for each of them for the period of 2016-2018 have been determined. During the three years, the area of forests has decreased by 14 hectares. Our proposed workflow includes six stages: analysis of input data, band composition of space images on the research territory, implementation of unsupervised classification in Erdas Imagine software and selection of forest class and determination of implementing this workflow, the vector layers of the forest cover of the Carpathians in the Lviv region for 2016, 2017, 2018 were obtained, and on their basis, the corresponding areas were calculated and compared.