Methodology of the Digital Platform of Smart Accurate Ecologically Balanced Agriculture of Adygea

The digital platform being developed is an information and mathematical model of the space of agricultural lands of Adygea, designed to solve an urgent problem of our time: automated visualization of the boundaries of spatial and temporal heterogeneity of crops and their habitat. For the first time, an automated computational model of the redistribution of agrochemical indicators in morphometrically classified quasi–homogeneous relief surfaces – geotopes in comparison with soil conditions, climatic and microclimatic fluctuations has been created. The tasks of the development include: providing automated monitoring, analysis, forecasting and optimization of crop growth conditions at the local and meso-level of natural and economic areas of the region, as well as creating an intelligent information support system for technological solutions in relation to the soil, climatic and economic conditions of a particular agricultural enterprise. At the regional and meso-level, the basic information component of the digital platform includes the hierarchy of natural and economic areas identified by methods of landscape-climatic, ecological-soil and natural-anthropogenic zoning according to the quasi-homogeneous distribution of parent rocks and natural and ecological conditions of the formation of meso-, microclimate and soils. At the local level, information is integrated with respect to the author’s information-mathematical 3D geometric structural model of the field relief surface, which provides extraction of morphometric characteristics and calculation of current lines determining the direction of movement of matter along geotopes, determination of representative points of agrochemical examination and interpolation of agrochemical analysis data in the field relief. The digital platform is being developed on the basis of the free cross-platform Quantum GIS in the form of an extension module in Python using QGIS libraries. The database of the digital platform is created on the PostgreSQL database management system. The extension module directly processes the information stored in the database to obtain consolidated information on the hierarchy of units of analysis – natural and economic area and agricultural enterprise, geotope and field.

1. Atlas of the Republic of Adygea. Maikop: Associated Cartographic Center-M, 2005. (In Russ.)

2. Varshanina T.P., Mitusov D.V. Climatic resources of landscapes of the Republic of Adygea. Maikop: Adyghe State University, 2005. (In Russ.)

3. Varshanina T.P., Plisenko O.A. Integrated GIS of the region on the example of the Republic of Adygea. Moscow; Maykop: Tuning fork, 2011. (In Russ.)

4. Vinogradov B.V. Fundamentals of landscape ecology. Moscow: GEOS, 1998. (In Russ.)

5. Lastochkin A.N. General technological scheme of geoecological research on a systemic-morphological basis. Applied geomorphology based on the general theory of geosystems. SPb., 2008:364–370. (In Russ.)

6. Volkov S.N. Land management. Volume 2. Land management design. On-farm land management. Moscow: Kolos, 2001. (In Russ.)

7. Plisenko O.A. Application of expert systems in GIS for spatial analysis of relief. InterCarto / InterGIS 22. Geoinformation support of sustainable development of territories in the context of global climate change. T. 1. Moscow: Scientific Library. 2016:157-167. (In Russ.)

8. Plisenko O.A. Modeling elementary geomorphic surfaces on digital maps. Applied aspects of geology, geophysics and geoecology using modern information technologies: materials of the IV International Scientific and Practical Conference. Maykop: Kucherenko V.O., 2017. (In Russ.)

9. Yakushev K.P., Yakushev V.V., Blokhin S.Yu. Scientific foundations for building intelligent systems for precision farming. Plant Protection Bulletin. 2020;103(1):25–36. (In Russ.)

10. Tang J., Pilesjö P., Persson A. Estimating slope from raster data – a test of eight algorithms at different resolutions in flat and steep terrain [Electronic resource]. Geodesy and Cartography. 2013;39 (2):41–52. URL: https://doi.org/10.3846/20296991.2013.806702

11. Zhou Q.M., Liu X.J. Analysis of errors of derived slope and aspect related to DEM data properties. Computers & Geosciences. 2004;30(4):369–78.

12. Kostianoy A.G. [et al.] General Characteristics of the Climate in the Republic of Adygea. Springer Crossref DOI link: https://doi.org/10.1007/698_2021_7352021 (In Russ.)

13. Kostianoy A.G. [et al.] Regional Climate Change in the Republic of Adygea [Electronic resource]. Springer Crossref DOI link: https://doi.org/10.1007/698_2021_7342021 (In Russ.)

14. Varshanina T.P. [et al.] Methodology and scientific and practical significance of visualization of integral geophysical fields/Electronic journal. Scientific Visualization [Electronic resource]. URL: http://www.sv-journal.org/2017-4/11.php?lang=ru (In Russ.)