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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 5, pp. 71-84

Decision making tools on precision farming technologies feasibility based on geostatistical analysis of remote sensing data

O.A. Mitrofanova 1 , E.P. Mitrofanov 1 , V.P. Yakushev 1 , V.V. Yakushev 1 , V.M. Bure 1, 2 , S.Yu. Blokhina 1 
1 Agrophysical Research Institute, Saint Petersburg, Россия
2 Saint Petersburg State University, Saint Petersburg, Russia
Accepted: 16.08.2023
DOI: 10.21046/2070-7401-2023-20-5-71-84
The possibility of achieving economic efficiency from the introduction of precision agriculture technologies requires the development of predictive methods to assess the prospects for implementation those technologies, taking into account specific conditions. The authors propose a toolkit to support a method for assessing the feasibility of applying precision agriculture technologies on a given agricultural territory on the basis of variogram analysis of remote sensing data. In order to make a decision, it is necessary to investigate statistical relationships of the spatial distribution of the values of the parameter under study in the agricultural field and assess the degree of within-field heterogeneity, on which the application of differentiated agro-technological operations depends. The paper considers one of the approaches to constructing a geostatistical module for conducting predictive computational experiments, which allows to automate all stages of solving the problem of assessing the prospects for using precision agriculture technologies for specific soil and climatic conditions of an agricultural producer. The toolkit was developed using specialized statistical programming language R, in addition to standard libraries gstat, e1071, lattice, sp, etc. Visualization of the prototype was carried out on the basis of the shiny package. In the future it is planned to refine the prototype module for implementation in a single service for the analysis of heterogeneous geospatial data by various new and modern methods in order to make management decisions.
Keywords: precision farming, remote sensing data, geostatistics, nugget to sill ratio, geostatistical module, R
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