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Effect of Slope Mesorelief on the Spatial Variability of Soil Properties and Vegetation Index Based on Remote Sensing Data

  • USE OF SPACE INFORMATION ABOUT THE EARTH STUDYING SOILS AND VEGETATION USING SATELLITE DATA
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Abstract

This article evaluates the effect of terrain morphometric parameters calculated from the digital elevation model (ASTER GDEM, 30 m) on the spatial variability of soil properties and the normalized difference vegetation index (NDVI) of a forb–oat mix. According to regression analysis, the morphometric parameters contribute 42% to the spatial variability of soil moisture; 59 and 46% to physical clay and humus content, respectively; and 86% to the NDVI of the oat-herb mixture. Indicators of moisture and physical clay and humus content in a plow layer of agro-grey soil of the transitional part of the slope are lower when compared with the alluvial part of the slope. In our opinion, this is a result of the development of erosional processes on the sloped terrain site, less favorable hydrothermal conditions, and human economic activities. The statistical relationships between soil properties and morphometric parameters of the terrain make it possible to build a predictive map of the soil properties.

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Funding

The study was carried out according to the state assignment of ISSA SB RAS.

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Authors and Affiliations

  1. Institute of Soil Science and Agrochemistry, Siberian Branch, Russian Academy of Sciences, 630090, Novosibirsk, Russia

    N. V. Gopp, T. V. Nechaeva, O. A. Savenkov & N. V. Smirnova

  2. Institute of Computational Technologies, Siberian Branch, Russian Academy of Sciences, 630090, Novosibirsk, Russia

    V. V. Smirnov

Authors
  1. N. V. Gopp
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  2. T. V. Nechaeva
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  3. O. A. Savenkov
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  4. N. V. Smirnova
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  5. V. V. Smirnov
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Correspondence to N. V. Gopp.

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The authors declare that they have no conflict of interest.

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Translated by E. Kuznetsova

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Gopp, N.V., Nechaeva, T.V., Savenkov, O.A. et al. Effect of Slope Mesorelief on the Spatial Variability of Soil Properties and Vegetation Index Based on Remote Sensing Data. Izv. Atmos. Ocean. Phys. 55, 1329–1337 (2019). https://doi.org/10.1134/S0001433819090202

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  • DOI: https://doi.org/10.1134/S0001433819090202

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