Application of Remote-Sensing Data in Geochemical Studies of Soils of the Yertis River Basin Within East Kazakhstan

Ulykpanova Meruyert M. (), Auezova Zaure, Ramazanova Nurgul, Mussabaeva Meruert and Zhanguzhina Altyn
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Ulykpanova Meruyert M.: Department of Physical and Economic Geography, L.N.Gumilyov Eurasian National University, Astana, Kazakhstan
Auezova Zaure: Department of Social Work and Tourism, Esil University, Astana, Kazakhstan
Ramazanova Nurgul: Department of Physical and Economic Geography, L.N.Gumilyov Eurasian National University, Astana, Kazakhstan
Mussabaeva Meruert: Department of Physical and Economic Geography, L.N.Gumilyov Eurasian National University, Astana, Kazakhstan
Zhanguzhina Altyn: Department of Physical and Economic Geography, L.N.Gumilyov Eurasian National University, Astana, Kazakhstan

Quaestiones Geographicae, 2024, vol. 43, issue 1, 157-164

Abstract: This article presents the results of field research, as well as the results of the use of remote-sensing data in the geochemical study of the soil cover of the Yertis River basin. In the work, the content of the gross form of heavy metals in the soil of the river basin was investigated. The atomic absorption method determined the content of the Poor configuration of elements of elements in soils. Statistical processing of the obtained data from N. A. Plokhinsky was carried out using the Statistica program. Also, using the performed indices in the remote sensing of clay minerals, iron oxides, and carbonates, the spatial distribution and comparison of pollutants in the soil cover of the river basin were revealed. The methods and means of image processing tested in this study can be used to create maps of the distribution of pollutants. Also, the data obtained reflect the patterns of distribution of heavy metals in the soils of the basin and can be used to optimize landscapes and improve the organization of ecological and geochemical monitoring.

Keywords: soils; river basin; heavy metals; indices; remote sensing (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:quageo:v:43:y:2024:i:1:p:157-164:n:1009

DOI: 10.14746/quageo-2024-0009

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