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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, 2020, Vol. 17, No. 2, pp. 114-122

Within-field variability estimation based on variogram analysis of satellite data for precision agriculture

V.P. Yakushev 1 , V.M. Bure 2, 1 , O.A. Mitrofanova 1, 2 , E.P. Mitrofanov 1, 2 , A.F. Petrushin 1 , S.Yu. Blokhina 1 , V.V. Yakushev 1 
1 Agrophysical Research Institute, Saint Petersburg, Russia
2 St. Petersburg State University, Saint Petersburg, Россия
Accepted: 17.02.2020
DOI: 10.21046/2070-7401-2020-17-2-114-122
The method for estimating the variability of canopy parameters in a specific agricultural area based on variogram analysis of satellite data is presented. A geostatistical model of the agricultural field heterogeneity that represents an indicator of within-field variability and consists of a sum of macro-, meso- and micro-components provides the basis of the proposed method. It is assumed that the estimation of the transition to precision agriculture technologies based on the analysis of nugget dispersion is the most effective when the within-field variation of the indicator has considerable contribution to the general picture of the field heterogeneity. The paper considers an example of a computational experiment in which the initial data are Sentinel-2 satellite images (processing level L2A, survey date 06.23.2019), covering the territory of the Detskoselskiy farm in Leningrad Region. A comparative assessment of the within-field heterogeneity of two randomly selected farm fields was carried out by the proposed method using satellite data to determine the prospects of precision agrochemical application technologies based on NDVI values. Statistical programming language R was used for data processing and analysis.
Keywords: variogram analysis, precision agriculture, within-field heterogeneity, geostatistical model
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