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This study explores the possibility of creating detailed maps of organic carbon content in the arable lands of northern Kazakhstan. The technology is based on filtering satellite images with convolutional neural networks and calculating the coefficients of the multi-temporal soil line using remote sensing data with a resolution of 30 meters. Calculating the coefficient of the multi-temporal soil line allowed us to create a map of the bare soil surface, highlighting areas of soil cover heterogeneity. The resulting ...

New methods for assessing soil cover heterogeneity, based on the analysis of extensive satellite data using neural network filtering technologies, were implemented to evaluate the territory of northern Kazakhstan. A comparative analysis of the quality of soil cover structure (SCS) determination, using remote sensing data, was conducted using two different methods. The first method is indirect and involves determining the SCS by analyzing and aggregating multitemporal vegetation indices (MVI). The second method is ...

The optimal solution of intensification and ecologisation of agricultural production is achieved in adaptive-landscape farming systems. To solve the problems of adaptive landscape agriculture, classical methods of soil-landscape mapping and new methods of remote diagnostics of intra-field heterogeneity were combined to identify features that will further improve the efficiency of producing maps of groups and types of land and increase their accuracy. Identification of the spectral characteristics of groups and typ...