Аңдатпа
The need to automate and simplify the spatial and temporal monitoring of economically important soil characteristics, in particular the carbon content of intensively used lands, dictates the continued search for relatively simple ways of their remote evaluation. We discovered medium-strength significant relations of LS-factor (Slope Length and Steepness factor; erosion potential of the relief), and soil characteristics as a result of a statistical analysis of field observations, laboratory experiments, and digital elevation models obtained from space remote sensing data. Surface data were obtained from model transects located in different relief positions of long-term arable chernozems (Kursk Oblast, Russia). These relationships are expressed in decreased content of the key nutrients and compounds (SOC, nitrogen, and water), as well as in reduced presence and altered activity of soil microbiota. We assume that the main reason for this is water erosion and less water availability on steeper slopes. Based on our results, we believe that LS-factor calculated on the basis of satellite remote sensing data is applicable for evaluation of erosion hazard, as well as for prediction of carbon content and other related significant physical, chemical, and biological indicators of the state of perennial arable haplic chernozems for a large spatial scale. At the same time, we found that the spectral characteristics of the soil surface obtained from remote sensing data are less applicable for these purposes. This is due to the dependence of the obtained satellite data on the survey conditions (weather, soil tillage techniques, vegetation cover characteristics) and the limitations imposed by the insufficient resolution of the available satellite images.