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.
Translated title of the contributionWithin-field variability estimation based on variogram analysis of satellite data for precision agriculture
Original languageRussian
Pages (from-to)114-122
Number of pages9
JournalСОВРЕМЕННЫЕ ПРОБЛЕМЫ ДИСТАНЦИОННОГО ЗОНДИРОВАНИЯ ЗЕМЛИ ИЗ КОСМОСА
Volume17
Issue number2
DOIs
StatePublished - 2020

    Research areas

  • VARIOGRAM ANALYSIS, Precision agriculture, WITHIN-FIELD HETEROGENEITY, GEOSTATISTICAL MODEL, Variogram analysis, Within-field heterogeneity, Geostatistical model

    Scopus subject areas

  • Computers in Earth Sciences
  • Computer Networks and Communications
  • Computer Science Applications

ID: 53689621