Dr. Evgenii Makarenko Profile

Dr. Evgenii Makarenko

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Proceedings Article | 6 July 2022 Paper

Management of farmland quality in the Leningrad region

Sergey Malashin, Evgenii Makarenko, Vyacheslav Samorukov, Vladimir Gorychkin, Konstantin Evdokimov

Proceedings Volume 12296, 122960F (2022) https://doi.org/10.1117/12.2642981

KEYWORDS: Agriculture, Soil science, Statistical analysis, Remote sensing, Potassium, Phosphorus, Modeling, Nitrogen, Data processing, Analytical research

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The comparable assessment of the agro-resource potential makes it possible to objectively assess the results of economic activities of administrative districts and individual agricultural enterprises, which have, as a rule, unequal soil and land resources located in different natural and climatic conditions. The models and methods used to forecast the dynamics of agricultural processes are based on quantitative information and are implemented as part of statistical quality control and potential loss estimation in state-supported agricultural insurance. On the one hand, only a comprehensive agrochemical survey of agricultural land can provide objective data on changes in soil fertility throughout the region and make calculations for its future development. On the other hand, real dynamic processes occurring in agriculture are represented by specific farming conditions, for which these requirements are rarely met, due to the great uncertainty of the factors determining their dynamics. This article discusses the possibilities of using system-situational modeling tools to predict the dynamics of processes in the agricultural sector on the basis of a project-based approach. Aiming at that, the surveys of the land surface (meadows, arable land under crops) were carried out in the region by means of optical methods, which under processing of information programs allowed us to obtain quantitative assessments of the cultivation of crops most demanding to a neutral environment reaction, and consequently the qualitative effectiveness of liming of soils. The digital system-situational model that we have received for analysis and assessment of soil fertility quality can serve as a new tool to describe the dynamics of agrarian processes under the uncertainty conditions and to forecast yield/loss under agricultural insurance with state support.

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