Geostatistical methods are important in analyzing natural resources providing input data for complex mathematical models that address environmental processes and their spatial distribution. Ten interpolation methods and one empirical-based classification grounded in empirical knowledge, with a total of 929 soil samples, were used to create the most accurate spatial prediction maps for clay, sand, humus, and soil depth in Montenegro. These analyses serve as a preparatory phase and prioritize the practical application of the obtained results for the implementation and improvement of the MEDALUS model. This model, used to assess sensitivity to land degradation, effectively integrates into broader current and future research. The study emphasizes the importance of incorporating auxiliary variables, such as topography, climate, and vegetation data, enhancing explanatory power and accuracy in delineating the environmental characteristics, ensuring better adaptability to the studied area. The results were validated by the coefficient of determination (R²) and root mean square error (RMSE). For the clay, EBKRP (empirical Bayesian kriging regression prediction) achieved R² = 0.35 and RMSE = 6.95%, for the sand, it achieved R² = 0.34 and RMSE = 17.38%, for the humus, it achieved R² = 0.50 and RMSE = 3.80%, and for the soil depth, it achieved R² = 0.76 and RMSE = 5.36 cm. These results indicate that EBKRP is the optimal method for accurately mapping soil characteristics in future research in Montenegro.

The glass industry contributes to long-term soil contamination. This study assesses the impact of over 150 years of industrial activity and over a century of glassmaking processes in the Serbian Glass Factory in Paraćin. Focusing on potentially toxic elements (PTEs) and polycyclic aromatic hydrocarbons (PAHs), ecological and human health risks were evaluated. Sampling was conducted at 34 locations within the factory area, including 33 soil samples (0–30 cm) and one industrial waste (IW) sample. Soil analyses indicate that Zn, Ni, Cu, and Cd exceeded both the maximum permissible concentrations (MPCs) and remediation values (RVs) in many samples, while As and Hg showed fewer exceedances. Based on the Potential Ecological Risk Index (RI), about 33% of soil samples were moderately to highly polluted, and Cd, Pb, As, and Hg were identified as the main contributors. High levels of PAHs and PTEs reflect the cumulative impact of long-term industrial operations, a historical fire, and secondary sources, including traffic-related emissions from nearby highways. These factors resulted in elevated total carcinogenic risk (TCR) for Ni, Cr, and As. This study highlights soil contamination and associated health risks at the glass factory, emphasizing the need for environmental monitoring and management.

This paper analyzes the application of two data processing methods, the method of remote sensing and digitization of ortho-photo images, in the Gledićka river basin. The data were processed using the ArcMap GIS software package, where the erosion potential method according to Gavrilović were applied using the erosion coefficients, as well as the transport and production of sediments, through which the two methods were compared.