KFU. Card publication. Spatial prediction of agrochemical properties on the scale of a single field using machine learning methods based on remote sensing data

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SPATIAL PREDICTION OF AGROCHEMICAL PROPERTIES ON THE SCALE OF A SINGLE FIELD USING MACHINE LEARNING METHODS BASED ON REMOTE SENSING DATA

Form of presentation

Articles in international journals and collections

Year of publication

2021

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Authors, employees of KFU

Giniyatullin Kamil Gashikovich, author

Sakhabiev Ilnaz Alimovich, author

Smirnova Elena Vasilevna, author

Bibliographic description in the original language

Sahabiev I, Smirnova E, Giniyatullin K., Spatial prediction of agrochemical properties on the scale of a single field using machine learning methods based on remote sensing data//Agronomy. - 2021. - Vol.11, Is.11. - Art. �2266.

Keywords

precision agriculture; digital maps; machine learning methods; remote sensing

The name of the journal

Agronomy

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119659604&doi=10.3390%2fagronomy11112266&partnerID=40&md5=d45102bee046d50938446e10bfd7fcec

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=260598&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Giniyatullin Kamil Gashikovich	ru_RU
dc.contributor.author	Sakhabiev Ilnaz Alimovich	ru_RU
dc.contributor.author	Smirnova Elena Vasilevna	ru_RU
dc.date.accessioned	2021-01-01T00:00:00Z	ru_RU
dc.date.available	2021-01-01T00:00:00Z	ru_RU
dc.date.issued	2021	ru_RU
dc.identifier.citation	Sahabiev I, Smirnova E, Giniyatullin K., Spatial prediction of agrochemical properties on the scale of a single field using machine learning methods based on remote sensing data//Agronomy. - 2021. - Vol.11, Is.11. - Art. �2266.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=260598&p_lang=2	ru_RU
dc.description.abstract	Agronomy	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	Spatial prediction of agrochemical properties on the scale of a single field using machine learning methods based on remote sensing data	ru_RU
dc.type	Articles in international journals and collections	ru_RU