| Issue |
E3S Web Conf.
Volume 623, 2025
IV International Conference on Ensuring Sustainable Development: Ecology, Earth Science, Energy and Agriculture (AEES2024)
|
|
|---|---|---|
| Article Number | 01002 | |
| Number of page(s) | 7 | |
| Section | Ecology, Biodiversity and Ways of its Conservation | |
| DOI | https://doi.org/10.1051/e3sconf/202562301002 | |
| Published online | 08 April 2025 | |
Assessment of the use of remote sensing methods to protect agricultural lands from invasive plants
1 Moscow State University of Geodesy and Cartography, 4, Gorokhovsky per., Moscow, 105064 Russia
2 Financial University under the Government of the Russian Federation, 49/2, Leningradsky avenue, Moscow, 125167, Russian Federation
3 Shenzhen University, 3688, Nanhai Blvd., Nanshan, Shenzhen, Guangdong Province, 518060, China
* Corresponding author: morkovkinde@mail.ru
The article examines the problems of detecting the contamination of agricultural lands with invasive plants using the example of Sosnowskyi's hogweed. The use of remote sensing methods is proposed, on the basis of which it is possible to build cartographic models for the protection of agricultural lands from invasive plants of various natural zones of the European part of Russia. The article substantiates the position that the optimal application of the method helps to solve the problem of controlling the distribution sites of hogweed and providing cartographic data on of Sosnowskyi's hogweed to the required territory. As a result of the study, the possibility of using this method was confirmed, which most fully displays the group of the mapping object in binary image format, and possible methods to improve the results. It is determined that the binary image format makes it possible to use the automation process in thematic mapping to protect agricultural land from invasive plants of various species, including of Sosnowskyi's hogweed, and to ensure environmentally sustainable agriculture.
© The Authors, published by EDP Sciences, 2025
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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