Digital agriculture mapping (Crop monitoring) - a vector representation of the boundaries of lands used in agriculture: arable land, pastures, hayfields, orchards, etc. Depending on the objectives and available input parameters, the final data may include the following attribute information: field area, crop type, phosphorus and potassium content, and other agrochemical indicators.

The availability of digital agricultural land maps allows for the implementation of precision farming technologies and simplifies the procedure of environmental certification. It also helps to identify discrepancies between arable land and the cadastral register.

Digitalization of Agriculture - a promising direction that aligns with the goals of sustainable development and the increasing demand for product quality.

The purpose of creating digital agricultural land maps is to aggregate diverse information about fields in one file, which includes spatial referencing and information about field boundaries. The high-precision foundation obtained from the analysis of aerospace imagery allows for proper route planning of agricultural machinery and working with programs using GLONASS technologies.

The objectives that can be achieved using electronic agricultural land maps (crop monitoring) include:

• Implementation of precision farming or No-Till technologies;
• Creation of soil fertility passports;
• Environmental monitoring;
• Creation of cartograms of soil properties;
• Yield analysis and creation of thematic maps;
• Execution of land management and cadastral work;
• Territorial planning;
• Construction of roads, highways, and intersections;

Remote sensing data is the only source of continuous and multi-temporal information available for almost all regions of the world. The presence of multispectral information allows for the analysis of the territory in various channel combinations, which can correlate well with the essential properties of agro-landscapes. For example, analyzing the territory using the NDVI index in certain cases allows for assessing the nitrogen content available to plants. The high spatial resolution of the images ensures accuracy in modeling and digitizing land boundaries.