Kazan (Volga region) Federal University, KFU
KAZAN
FEDERAL UNIVERSITY
 
DIGITAL MAPPING OF INDICATORS THAT DETERMINE THE SORPTION PROPERTIES OF SOILS IN RELATION TO POLLUTANTS, ACCORDING TO REMOTE SENSING DATA OF THE EARTH USING MACHINE LEARNING
Form of presentationArticles in international journals and collections
Year of publication2022
Языкрусский
  • Gordeeva Karina Andreevna, author
  • Okunev Rodion Vladimirovich, author
  • Smirnova Elena Vasilevna, author
  • Urazmetov Ildar Anvarovich, author
  • Bibliographic description in the original language Giniyatullin K.G., Sakhabiev I.A., Smirnova E.V., Urazmetov I.A., Okunev R.V., Gordeeva K.A. (2022). Digital mapping of indicators that determine the sorption properties of soils in relation to pollutants, according to remote sensing data of the Earth using machine learning. Georesursy = Georesources, 24(1), pp. 84–92. DOI: https://doi.org/10.18599/grs.2022.1.8
    Keywords сорбционные свойства почвы, пространственный прогноз, данные дистанционного зондирования Земли, методы машинного обучения
    The name of the journal GEORESURSY
    URL https://www.scopus.com/record/display.uri?eid=2-s2.0-85128675408&origin=resultslist&sort=plf-f&src=s&st1=Okunev&st2=R+V&nlo=1&nlr=20&nls=count-f&sid=818902b9840dee051f4a362dfa81a590&sot=anl&sdt=aut&sl=49&s=AU-ID%28%22Okunev%2c+Rodion+Vladimirovich%22+56156815600%29&relpos=0&citeCnt=0&searchTerm=&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1
    Please use this ID to quote from or refer to the card https://repository.kpfu.ru/eng/?p_id=266084&p_lang=2

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