The improper and unconscious use of the soil, a production material for humans, increases the risk of desertification and degradation. This study examines the some erosion susceptibility parameters such as soil erosion factor (USLE-K), dispersion ratio, and aggregate stability by applying various algorithms in decision trees and evaluating the spatial distribution of these properties using multiple interpolation method. While determining statistically significant correlations (P < 0.01) between aggregate stability of soils and mass fractal dimension and mean diameter weight, these features were employed as the root node and inner node in decision trees. The highest estimation rate was determined categorically with the CART algorithm in the prediction phase with decision trees. Aggregate stability was determined by applying two tree depths and mass fractal dimension and silt variables with 81.1% accuracy. In predicting the K factor, the silt and clay variables were estimated at 90.6% by forming nodes. In comparison, the dispersion ratio was calculated at 77.4% accuracy with clay, EC, and mean diameter weight. Soils categorized as moderately erodible according to the USLE-K factor were estimated at 92.3% level of accuracy with decision trees. In the predictive values obtained by numerical data, the highest aggregate stability and the USLE-K factor were obtained with the lowest prediction accuracy. This change was similar in distribution maps. The lowest root means squarer error (8.074; 5.106) was obtained by the simple kriging interpolation method in the distribution maps of the aggregate stability observed and predicted values.

对人类生产材料土壤的不当和无意识使用会增加荒漠化和退化的风险。本研究通过在决策树中应用各种算法并使用多重插值方法评估这些特性的空间分布，来检查一些侵蚀敏感性参数，例如土壤侵蚀因子 (USLE-K)、分散比和团聚体稳定性。在确定土壤团聚体稳定性与质量分形维数和平均直径权重之间的统计显着相关性（P < 0.01）时，这些特征被用作决策树的根节点和内部节点。在使用决策树的预测阶段，使用 CART 算法分类确定最高估计率。通过应用两个树深度和质量分形维数和淤泥变量来确定骨料稳定性，准确度为 81.1%。在预测 K 因子时，通过形成节点估计淤泥和粘土变量为 90.6%。相比之下，使用粘土、EC 和平均直径重量以 77.4% 的准确度计算出分散比。根据 USLE-K 因子归类为中度可蚀性土壤的决策树估计准确度为 92.3%。在通过数值数据获得的预测值中，以最低的预测精度获得了最高的骨料稳定性和USLE-K因子。这种变化在分布图中是相似的。最低均方根误差 (8.074; 5.