Understanding how topography affects the distribution of soil properties is essential in the management of landscape hydrology and establishment of sustainable soil management practices. This study investigated the impact of topography on the variation in particle size distribution, coarse fragments, and soil bulk density using different interpolation techniques and fractal analysis. It also evaluated the performance of various interpolation techniques in predicting and characterizing the distribution of soil properties. The study was conducted using data from 620 samples extracted from the Tellus and LUCAS databases in Eglinton and Castlederg counties, Northern Ireland. Terrain attributes were obtained at a 30 x 30 m resolution using a global digital elevation model (GDEM) reintroduced to the Universal Transverse Mercator (UTM) projection. Interpolation analyses were conducted using inverse distance weighting (IDW), ordinary kriging (OK), block kriging (BK) and co-kriging (CK). Among the terrain attributes, elevation was the most influential covariate for CK. In addition, fractal analysis was conducted to assess the self-similarity of the soil properties. Prediction accuracy of the interpolation methods was evaluated using the Nash-Sutcliffe efficiency, mean absolute error, index of agreement, and Pearson correlation coefficient. Spatial maps produced from the kriging techniques showed high accuracy in the prediction of soil particle size distribution and bulk density. The use of elevation as an auxiliary variable was successful in producing accurate soil property distribution maps with CK. The fractal parameters showed that the soil properties had short range spatial variability, anti-persistent nature, and strong spatial structure. Additionally, the fractal dimension was strongly correlated with sand, silt and clay contents and bulk density, and weakly correlated with the coarse fragments.