esoilБюллетень Почвенного института имени В.В. ДокучаеваDokuchaev Soil Bulletin0136-16942312-4202V.V. Dokuchaev Soil Science Institute10.19047/0136-1694-2022-110-22-50esoil-694Research ArticleСтатьиОб оптимизации размещения сети датчиков интернета вещей на пахотных угодьяхOn optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plotshttps://orcid.org/0000-0002-8739-5441СавинИ. Ю.SavinI. Yu.savin_iyu@esoil.ruБлохинЮ. И.BlokhinYu. I.blohin3k4@gmail.comПочвенный институт им. В.В. ДокучаеваРоссияFederal Research Centre “V.V. Dokuchaev Soil Science Institute”Russian FederationАгрофизический научно-исследовательский институтРоссияAgrophysical Research InstituteRussian Federation20222506202201102250Copyright © Савин И.Ю., Блохин Ю.И., 20222022Савин И.Ю., Блохин Ю.И.Savin I.Y., Blokhin Y.I.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://bulletin.esoil.ru/jour/article/view/694

Одним из направлений цифровизации в сельском хозяйстве является внедрение технологий интернета вещей. Оно выражается в создании и использовании специализированных датчиков свойств почв и посевов, которые размещаются на полях. Размещение подобных датчиков в пространстве должно позволить охарактеризовать все микронеоднородности параметров плодородия почв на поле. То есть их количество и пространственное размещение должно быть оптимальным, с одной стороны, с точки зрения затрат на их приобретение и эксплуатацию, а с другой стороны, с точки зрения точности интерполяции получаемых с их помощью данных на всю территорию поля. Показано, что использование карт состояния посевов, полученных по спутниковым данным, и выделение по ним рабочих участков (management zones) может приводить к значительным ошибкам при интерполяции результатов мониторинга в отдельных точках на все поле. Предложен подход для оптимизации размещения датчиков, основанный на использовании карт пестроты плодородия почв полей, которые являются результатом доработки, обновления и уточнения традиционно составленных почвенных карт на основе данных дистанционного зондирования высокого или сверхвысокого пространственного разрешения. Возможности использования подхода продемонстрированы на примере тестового поля.

One of the main stream of digitalization in agriculture is the introduction of Internet of Things technologies, which is expressed in the creation and use of specialized sensors that are placed in the fields. The placement of such sensors within agricultural plot should make it possible to characterize all the microvariability of soil fertility parameters in the field. That is, their number and spatial location should be optimal, on the one hand, in terms of costs of their acquisition and operation, and, on the other hand, in terms of accuracy of interpolation of data obtained with their help to the entire plot. It has been shown that the use of crop condition maps obtained on the basis of satellite data and the separation based on them of management zones can lead to significant errors in the interpolation of monitoring results, obtained in separate points, on the whole plot. An approach for optimization of sensor placement is proposed based on the use of soil fertility mapping, which is the result of refinement, updating and clarification of traditionally drawn soil maps on the basis of high spatial resolution remote sensing data. The possibilities of using the approach are demonstrated by the example of a test plot in Leningrad region of Russia. 

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The authors declare that there are no conflicts of interest present.