| Issue |
E3S Web Conf.
Volume 175, 2020
XIII International Scientific and Practical Conference “State and Prospects for the Development of Agribusiness – INTERAGROMASH 2020”
|
|
|---|---|---|
| Article Number | 01004 | |
| Number of page(s) | 9 | |
| Section | Plant Growing and Cereal Grain | |
| DOI | https://doi.org/10.1051/e3sconf/202017501004 | |
| Published online | 29 June 2020 | |
Research of rice crops in Krasnodar region by remote sensing data
1
Federal Scientific Rice Centre, 3, Belozerny, 350921, Krasnodar, Russia
2
Kuban State University, 149, Stavropol st., 350040, Krasnodar, Russia
3
Agrophysical Research Institute, 14, Grazhdanskiy pr., 195220, Saint-Petersburg, Russia
* Corresponding author: sma_49@mail.ru
The concept of digitalization of agricultural production in the Russian Federation provides for the implementation of measures to develop and create a system of geographic information monitoring and decision support in crop production. The aim of the research was to conduct geoinformation monitoring of rice crops to develop methods for automated mapping of their condition and yield forecasting. The studies were carried out on a test site of the Federal State Budgetary Scientific Institution “Federal Scientific Rice Centre” with an area of 274 hectares. The survey was performed by a quadcopter with a MicaSense RedEdge-M multispectral camera mounted on a fixed suspension. The shooting period using an unmanned aerial vehicle (UAV) was limited to early June and additionally used the Sentinel-2A satellite. To assess the state of rice crops, the normalized relative vegetative index NDVI was used. Based on the NDVI distribution and yield information from the combine TUCANO 580 (CLAAS), a statistical analysis was carried out in fields 7 and 9. Testing of the experimental methodology for monitoring crops in 2019 on the basis of remote sensing of test plots and geoinformation modeling and the statistical apparatus should be considered satisfactory.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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