Determining the height of agricultural crops based on measurements of unmanned aircraft

Автор: Malchikov Nikita O., Botvich Irina Yu., Emelyanov Dmitry V., Ivchenko Vladimir K., Shevyrnogov Anatoly P.

Журнал: Вестник Красноярского государственного аграрного университета @vestnik-kgau

Рубрика: Агрономия

Статья в выпуске: 12, 2020 года.

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The purpose of the research was approbation and evaluation of the effectiveness of the method for determining the plant height of agricultural crops based on unmanned aerial vehicles data. The research objectives were measuring plant height by contact and remote methods; creating the map of spatial distribution of the plant height in barley and wheat. The studies were carried out on the lands of educational and experimental farm "Minderlinskoe", Sukhobuzimo district, Krasnoyarsk region on July, 22, 2020. The paper presented the analysis of the data processing results for line 1, 3 - sown with wheat "Novosibirskaya-15", 2 - with barley "Acha". The study was based on the data from a DJI Matrice 210 RTK V2 (ZENMUSE X5S camera) - a 3D terrain model was built; DJI Phantom 4 Multispectral - NDVI spatial distribution map was obtained. The plant height measurements of spring wheat and barley crops by contact and remote methods were carried out. The largest error value, 12.9 %, was obtained for barley crops. The error in determining the height of spring wheat crops ranged from 2.9 % to 3.8 % with different types of processing. It was found that the error magnitude had been caused by morphological characteristics of barley plants. The plant height spatial distribution maps of spring wheat and barley were obtained. The assessment of heterogeneity of crops of grain crops was carried out. The possibility of assessing the area of grain crops lodging based on the plant height spatial distribution data had been established. It was found that the most effective approach for identifying crop lodging is the combined use of the plant height maps and NDVI.

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Zenmuse x5s, crops, plant elevation map, unmanned aerial vehicles, uavs, precision farming

Короткий адрес: https://sciup.org/140250603

IDR: 140250603   |   DOI: 10.36718/1819-4036-2020-12-46-53

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