title: On the issue of semivariograms constructing automation for precision agriculture problems
metadata.name: dc.contributor.author
metadata.value: Iakushev, Viktor P.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Bure, Vladimir M.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Mitrofanova, Olga A.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Mitrofanov, Evgenii P.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2020-08-24T21:10:48Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2020-08-24T21:10:48Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2020-06
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Iakushev V. P., Bure V. M., Mitrofanova O. A., Mitrofanov E. P. On the issue of semivariograms constructing automation for precision agriculture problems. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2020, vol. 16, iss. 2, pp. 177–185.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/11701/spbu10.2020.209
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/19019
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: Most precision agriculture (PA) problems are based on assessing the variability of agroecological
  parameters (differentiated fertilizer application, allocation of heterogeneous zones of
  the agricultural field, etc.). In this connection, the study of the spatial structure of such data
  using geostatistical methods seems to be a relevant and promising direction. To validate
  the semivariogram model, determine its parameters, analyze anisotropy, and carry out other
  stages of the experiment, a large number of numerical calculations are required. Manually all
  these calculations are extremely difficult to perform, therefore, automation of these processes
  is necessary. Most existing programs exclude certain actions that may be important in solving
  PA problems (there is no possibility of studying anisotropy or spatial trend, the number of
  theoretical variogram models, etc., is limited), and the use of programming languages (R,
  Python, etc.) requires deep expertise. Therefore, there was a need to automate the solution
  of a certain range of problems by geostatistical methods. For the implementation of the
  module under consideration, it seems optimal to use the R programming language, which
  has a number of significant advantages: open source code and free access, a large number of
  supported and regularly updated packages, wide graphical capabilities, cross-platform, etc.
  General suggestions for automating the construction of semivariograms are presented and
  further use in solving a certain range of PA tasks.
metadata.lang: en_GB
metadata.name: dc.description.sponsorship
metadata.value: This work was supported by the Russian Foundation for Basic Research (grant N 19-29-05184 mk).
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Applied Mathematics. Computer Science. Control Processes;Volume 16; Issue 2
metadata.lang: -
metadata.name: dc.subject
metadata.value: variogram analysis
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: precision agriculture
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: geostatistics
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: automation
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: programming language R
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: On the issue of semivariograms constructing automation for precision agriculture problems
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 177-185.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/19019/1/177-185.pdf
resources.format: Adobe PDF
resources.size: 620,09 kB