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

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

According to the data of remote sensing of the Earth, the accuracy of the spatial prediction of soil indicators determining sorption properties in relation to pollutants was compared. To build spatial maps of changes in soil properties, machine learning methods based on support vector regression mod...

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Bibliographic Details
Main Authors: Kamil G. Giniyatullin, Ilnas A. Sahabiev, Elena V. Smirnova, Ildar A. Urazmetov, Rodion V. Okunev, Karina A. Gordeeva
Format: Article
Language:English
Published: Georesursy Ltd. 2022-03-01
Series:Georesursy
Subjects:
sorption properties of soil
spatial prediction
remote sensing data of the earth
machine learning methods
Online Access:https://geors.ru/archive/article/1144/

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