Mapping soil organic carbon under erosion processes using remote sensing

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Mapping soil organic carbon under erosion processes using remote sensing. / Suleymanov, Azamat; Gabbasova, Ilyusya; Suleymanov, Ruslan; Abakumov, Evgeny ; Polyakov, Vyacheslav; Liebelt, Peter.

In: Hungarian Geographical Bulletin, Vol. 70, No. 1, 06.04.2021, p. 49-64.

Research output: Contribution to journal › Article › peer-review

Author

Suleymanov, Azamat ; Gabbasova, Ilyusya ; Suleymanov, Ruslan ; Abakumov, Evgeny ; Polyakov, Vyacheslav ; Liebelt, Peter. / Mapping soil organic carbon under erosion processes using remote sensing. In: Hungarian Geographical Bulletin. 2021 ; Vol. 70, No. 1. pp. 49-64.

BibTeX

@article{4d150bafffb9421284b103f85b5f1baa,

title = "Mapping soil organic carbon under erosion processes using remote sensing",

abstract = "This study aimed to map soil organic carbon under erosion processes on an arable field in the Republic of Bashkortostan (Russia). To estimate the spatial distribution of organic carbon in the Haplic Chernozem topsoil, we applied Sentinel-2A satellite data and the linear regression method. We used 13 satellite bands and 15 calculated spectral indices for regression modelling. A regression model with an average prediction level has been created (R2 = 0.58, RMSE = 0.56, RPD = 1.61). Based on the regression model, cartographic materials for organic carbon content have been created. Water flows and erosion processes were determined using the calculated Flow Accumulation model. The relationship between organic carbon, biological activity, and erosion conditions is shown. The13C-NMR spectroscopy method was used to estimate the content and nature of humic substances of different soil samples. Based on the13C-NMR analysis, a correlation was established with the spectral reflectivity of eroded and non-eroded soils. It was revealed that the effect of soil organic carbon on spectral reflectivity depends not only on the quantity but also on the quality of humic substances and soil formation conditions.",

keywords = "13C-NMR, Erosion, Humic acids, Remote sensing, Sentinel, Soil organic carbon",

author = "Azamat Suleymanov and Ilyusya Gabbasova and Ruslan Suleymanov and Evgeny Abakumov and Vyacheslav Polyakov and Peter Liebelt",

note = "Publisher Copyright: {\textcopyright} 2021, Reasearch Centre for Astronomy and Earth Sciences Hungarian Academy. All rights reserved. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

year = "2021",

month = apr,

day = "6",

doi = "10.15201/hungeobull.70.1.4",

language = "English",

volume = "70",

pages = "49--64",

journal = "Hungarian Geographical Bulletin",

issn = "2064-5031",

publisher = "Hungarian Academy of Sciences, Geographical Research Institute",

number = "1",

}

RIS

TY - JOUR

T1 - Mapping soil organic carbon under erosion processes using remote sensing

AU - Suleymanov, Azamat

AU - Gabbasova, Ilyusya

AU - Suleymanov, Ruslan

AU - Abakumov, Evgeny

AU - Polyakov, Vyacheslav

AU - Liebelt, Peter

PY - 2021/4/6

Y1 - 2021/4/6

N2 - This study aimed to map soil organic carbon under erosion processes on an arable field in the Republic of Bashkortostan (Russia). To estimate the spatial distribution of organic carbon in the Haplic Chernozem topsoil, we applied Sentinel-2A satellite data and the linear regression method. We used 13 satellite bands and 15 calculated spectral indices for regression modelling. A regression model with an average prediction level has been created (R2 = 0.58, RMSE = 0.56, RPD = 1.61). Based on the regression model, cartographic materials for organic carbon content have been created. Water flows and erosion processes were determined using the calculated Flow Accumulation model. The relationship between organic carbon, biological activity, and erosion conditions is shown. The13C-NMR spectroscopy method was used to estimate the content and nature of humic substances of different soil samples. Based on the13C-NMR analysis, a correlation was established with the spectral reflectivity of eroded and non-eroded soils. It was revealed that the effect of soil organic carbon on spectral reflectivity depends not only on the quantity but also on the quality of humic substances and soil formation conditions.

AB - This study aimed to map soil organic carbon under erosion processes on an arable field in the Republic of Bashkortostan (Russia). To estimate the spatial distribution of organic carbon in the Haplic Chernozem topsoil, we applied Sentinel-2A satellite data and the linear regression method. We used 13 satellite bands and 15 calculated spectral indices for regression modelling. A regression model with an average prediction level has been created (R2 = 0.58, RMSE = 0.56, RPD = 1.61). Based on the regression model, cartographic materials for organic carbon content have been created. Water flows and erosion processes were determined using the calculated Flow Accumulation model. The relationship between organic carbon, biological activity, and erosion conditions is shown. The13C-NMR spectroscopy method was used to estimate the content and nature of humic substances of different soil samples. Based on the13C-NMR analysis, a correlation was established with the spectral reflectivity of eroded and non-eroded soils. It was revealed that the effect of soil organic carbon on spectral reflectivity depends not only on the quantity but also on the quality of humic substances and soil formation conditions.

KW - 13C-NMR

KW - Erosion

KW - Humic acids

KW - Remote sensing

KW - Sentinel

KW - Soil organic carbon

UR - http://www.scopus.com/inward/record.url?scp=85104389578&partnerID=8YFLogxK

U2 - 10.15201/hungeobull.70.1.4

DO - 10.15201/hungeobull.70.1.4

M3 - Article

AN - SCOPUS:85104389578

VL - 70

SP - 49

EP - 64

JO - Hungarian Geographical Bulletin

JF - Hungarian Geographical Bulletin

SN - 2064-5031

IS - 1

ER -

ID: 76773199