Soil organic carbon, clay content and cation exchange capacity play a key role in the productivity of agricultural soils, and are therefore fundamental parameters for environmental monitoring and modelling. However, studying these properties using traditional laboratory methods is labour-intensive and costly. An equally important factor is the steepness of slopes, which affects erosion processes and nutrient distribution in the soil. Geospatial analysis is a powerful tool for examining spatial patterns and the distribution of various indicators. When assessing soil quality indicators, GIS technologies enable the accurate and detailed monitoring of soil conditions in various areas, the assessment of their characteristics, and the identification of potential problem areas. This study presents observation and analysis of the impact of soil quality indicators, including soil organic carbon (SOC), physical clay, and cation exchange capacity (CEC), on the development of soil quality degradation using SoilGrids 250 m 2.0 data. To estimate the level of erosion, a slope steepness map was generated using the SRTM digital elevation model, which was downloaded through Google Earth Engine at a 30-m resolution. The results showed that high organic carbon content and optimal CEC values reduce soil vulnerability to the development of erosion, while steep slopes and low organic carbon content increase the risk of degradation. The vulnerability index developed based on these data allows us to effectively identify areas at high risk of soil degradation and develop protection strategies.