Mapping soil organic carbon under erosion processes using remote sensing

  • Azamat Suleymanov Laboratory of soil science, Ufa Institute of Biology, Ufa Federal Research Centre, Russian Academy of Sciences, Ufa, Russia
  • Ilyusya Gabbasova Laboratory of soil science, Ufa Institute of Biology, Ufa Federal Research Centre, Russian Academy of Sciences, Ufa, Russia
  • Ruslan Suleymanov Laboratory of soil science, Ufa Institute of Biology, Ufa Federal Research Centre, Russian Academy of Sciences, Ufa, Russia ; Department of Geodesy, Cartography and Geographic Information Systems, Bashkir State University, Ufa, Russia
  • Evgeny Abakumov Faculty of Biology, Department of Applied Ecology, Saint Petersburg State University, Saint Petersburg, Russia ; Laboratory of Microbiological Monitoring and Bioremediation of Soils, All-Russia Insitute for Agricultural Microbiology, St. Petersburg, Russia
  • Vyacheslav Polyakov Faculty of Biology, Department of Applied Ecology, Saint Petersburg State University, Saint Petersburg, Russia
  • Peter Liebelt Martin Luther University Halle-Wittenberg, Halle, Germany
Keywords: Soil organic carbon, remote sensing, sentinel, erosion, humic acids, 13C-NMR


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. The 13C-NMR spectroscopy method was used to estimate the content and nature of humic substances of different soil samples. Based on the 213C-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.


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How to Cite
SuleymanovA., GabbasovaI., SuleymanovR., AbakumovE., PolyakovV., & LiebeltP. (2021). Mapping soil organic carbon under erosion processes using remote sensing. Hungarian Geographical Bulletin, 70(1), 49-64.