Eroded slope lands are characterised by significant spatial heterogeneity of the soil cover, which complicates an objective assessment of their agricultural potential based on average-field agrochemical indicators. The aim of the study was to establish the patterns of spatial assessment of the agricultural potential of eroded slope lands based on the relationship between agronomic soil indicators and the parameters of the USLE (Universal Soil Loss Equation) model. The study was conducted in 2024-2025 at the “Dokuchaievske” experimental field of the State University of Biotechnology in the Left-Bank Forest-Steppe region of Ukraine. A total of 68 soil samples were collected from the arable layer using an irregular grid pattern, taking into account the characteristics of the terrain. The samples were analysed for organic carbon content, nitrate nitrogen and pH. The spatial distribution of these parameters was assessed using geographic information system (GIS) mapping, whilst erosion risk was characterised using the LS topographic factor of the USLE model. It was found that the organic carbon content ranged from 1.35 to 3.05 per cent, and the LS values ranged from 0.039 to 2.22. A strong inverse relationship was found between LS and organic carbon content: Spearman’s correlation coefficient was -0.725. The linear model Y = 2.7175 – 0.5124x confirmed a decrease in organic carbon content as erosion risk increased. When LS values were grouped, the average organic carbon content decreased from 2.610-2.636 to 1.853-1.949%, whilst the relationship between LS and nitrate nitrogen was weak, r = -0.066. Thus, organic carbon is a more reliable indicator for the spatial adjustment of the agricultural potential of eroded slope lands. The proposed approach can be used to construct map charts of adjustment coefficients, implement differentiated fertilisation, plan soil conservation measures and introduce elements of precision farming
organic carbon; nitrate nitrogen; topographical factor; soil resource potential; geographic information system mapping; haplic chernozem