Search Results - "Environmental pollution-monitoring studies" :: K.UTB vyhledávací portál

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A novel method to determine background concentrations and spatial distributions of heavy metals in soil at large scale using machine learning coupled with remote sensing-terrain attributes

by Sulieman, Magboul M., Kaya, Fuat, Al-Farraj, Abdullah S., Brevik, Eric C.
Published in MethodsX (01.06.2025)

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Determination of metals in Anemonia sulcata (Pennant, 1777) as a pollution bioindicator

by Lozano-Bilbao, Enrique, Espinosa, José María, Lozano, Gonzalo, Hardisson, Arturo, Rubio, Carmen, González-Weller, Dailos, Gutiérrez, Ángel J.
Published in Environmental science and pollution research international (01.06.2020)

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Heavy Metal and Mineral Composition of Soil, Atmospheric Deposition, and Mosses with Regard to Integrated Pollution Assessment Approach

by Mentese, Sibel, Yayintas, Özlem Tonguc, Bas, Batuhan, İrkin, Latife Ceyda, Yilmaz, Selehattin
Published in Environmental management (New York) (01.05.2021)

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Spatial variability of some heavy metals in arid harrats soils: Combining machine learning algorithms and synthetic indexes based-multitemporal Landsat 8/9 to establish background levels

by Sulieman, Magboul M., Kaya, Fuat, Keshavarzi, Ali, Hussein, Abdullahi M., Al-Farraj, Abdullah S., Brevik, Eric C.
Published in Catena (Giessen) (01.01.2024)

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OPTIMIZATION OF SOIL POLLUTION MONITORING METHODS BY USE OF BIOLOGICAL TESTS

by Elena BONCIU, Elena ROȘCULETE, Cătălin Aurelian ROȘCULETE, Aurel Liviu OLARU
Published in Scientific papers series "management, economic engineering in agriculture and rural development" (01.01.2022)

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Journal Article

A novel method to determine background concentrations and spatial distributions of heavy metals in soil at large scale using machine learning coupled with remote sensing-terrain attributes

Determination of metals in Anemonia sulcata (Pennant, 1777) as a pollution bioindicator

Heavy Metal and Mineral Composition of Soil, Atmospheric Deposition, and Mosses with Regard to Integrated Pollution Assessment Approach

Spatial variability of some heavy metals in arid harrats soils: Combining machine learning algorithms and synthetic indexes based-multitemporal Landsat 8/9 to establish background levels

OPTIMIZATION OF SOIL POLLUTION MONITORING METHODS BY USE OF BIOLOGICAL TESTS

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