Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/123456789/28693
Title: Assessment of the State of Plant Biomass Based on the Integration of Multispectral Sensors of Optical and Radio Ranges
Authors: Linets, G. I.
Линец, Г. И.
Bazhenov, A. V.
Баженов, А. В.
Melnikov, S. V.
Мельников, С. В.
Malygin, S. V.
Малыгин, С. В.
Grivennaya, N. V.
Гривенная, Н. В.
Keywords: Optical and radio ranges;Plant biomass;Multispectral sensors
Issue Date: 2024
Publisher: EDP Sciences
Citation: Linets, G., Bazhenov, A., Melnikov, S., Malygin, S., Grivennaya, N. Assessment of the State of Plant Biomass Based on the Integration of Multispectral Sensors of Optical and Radio Ranges // E3S Web of Conferences. - 2024. - 539. - статья № 02035. - DOI: 10.1051/e3sconf/202453902035
Series/Report no.: E3S Web of Conferences
Abstract: One of the main tasks of using remote sensing in agriculture for precision farming purposes is to identify management zones or management zones within which the timing and parameters of agrotechnical measures differ significantly. To clarify the boundaries of these zones, it is proposed to use jointly data on soil moisture (electrical conductivity) and the normalized plant index (NDVI) in a field of about 70 hectares. Based on spatial variations of humidity data obtained using a bistatic radar system and electrical conductivity obtained using electromagnetic scanning, as well as NDVI indices obtained using multispectral cameras, maps of the spatial distribution of these parameters are constructed. To determine the control zones, a fuzzy clustering algorithm was used, three target classes for assessing the state of plant biomass with restrictions on the percentage of moisture in the soil were identified. An analysis of 813 points of the soil surface was carried out with reference to geographical coordinates, the elements of the array were assigned to one of the target classes corresponding to one of the three control zones. The results of the analysis of arrays formed by classes allow us to conclude that it is possible to use fuzzy clustering to determine the boundaries of control zones in conditions of significant heterogeneity of the studied fields in terms of physico-chemical properties and relief.
URI: https://dspace.ncfu.ru/handle/123456789/28693
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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