KFU. Card publication. Spatial prediction of the properties of chernozem soils on a field scale using machine learning methods based on data from Landsat 8 OLI and Sentinel 2 images for precision farming

- RUS
- 中文
- ES

SPATIAL PREDICTION OF THE PROPERTIES OF CHERNOZEM SOILS ON A FIELD SCALE USING MACHINE LEARNING METHODS BASED ON DATA FROM LANDSAT 8 OLI AND SENTINEL 2 IMAGES FOR PRECISION FARMING

Form of presentation

Articles in international journals and collections

Year of publication

2021

��

��

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 the properties of chernozem soils on a field scale using machine learning methods based on data from Landsat 8 OLI and Sentinel 2 images for precision farming / I. Sahabiev, E. Smirnova, K. Giniyatullin // Proceedings:1st International Electronic Conference on Agronomy (IECAG-2021). -2021.- �4. P. 2-5

Keywords

Precision Agriculture, digital maps, machine learning methods, remote sensing

The name of the journal

Proceedings

URL

https://sciforum.net/paper/view/10023

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

https://repository.kpfu.ru/eng/?p_id=255914&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 the properties of chernozem soils on a field scale using machine learning methods based on data from Landsat 8 OLI and Sentinel 2 images for precision farming / I. Sahabiev, E. Smirnova, K. Giniyatullin // Proceedings:1st International Electronic Conference on Agronomy (IECAG-2021). -2021.- �4. P. 2-5	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=255914&p_lang=2	ru_RU
dc.description.abstract	Proceedings	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Precision Agriculture	ru_RU
dc.subject	digital maps	ru_RU
dc.subject	machine learning methods	ru_RU
dc.subject	remote sensing	ru_RU
dc.title	Spatial prediction of the properties of chernozem soils on a field scale using machine learning methods based on data from Landsat 8 OLI and Sentinel 2 images for precision farming	ru_RU
dc.type	Articles in international journals and collections	ru_RU