Vegetation plays an active role in ecosystem dynamics, and monitoring its patterns and changes is vital for effective environmental resource management. This study explores the possibility of machine learning techniques and remote sensing data to improve the accuracy of forest detection. The research focuses on the southeastern part of the Republic of Serbia as a case study area, using Sentinel-2 multispectral bands. The study employs publicly accessible satellite data and incorporates different vegetation indices to improve classification accuracy. The main objective is to examine the practicability of expanding the input parameters for forest detection using a machine learning approach. The classification process is performed by employing support vector machines (SVM) algorithm and utilising the SVM module in the scikit-learn package. The results demonstrate that including vegetation indices alongside the multispectral bands significantly improves the accuracy of vegetation detection. A comprehensive assessment reveals an overall classification accuracy of up to 99.01% when the selected vegetation indices (MCARI, RENDVI, NDI45, GNDVI, NDII) are combined with the Sentinel-2 bands. This research highlights the potential of machine learning and remote sensing in forest detection and monitoring. The findings underscore the importance of incorporating vegetation indices to enhance classification accuracy using the Python programming language. The study’s outcomes provide valuable insights for environmental resource management and decision-making processes, particularly in regions with diverse forest ecosystems.

This paper describes how uncontrolled and illegal mining of sand and gravel can affect surface water and groundwater regimes in places where there is a hydraulic connection between them, based on a case study of the Velika Morava River in Serbia. Also, a change in cross-profile geometry, as a result of anthropogenic and natural factors, hinders the preparation of this river for inclusion among Serbia’s waterways. The Velika Morava River’s navigability would enable the development of waterborne transportation for both merchant ships and vessels of the Serbian Armed Forces River Flotilla. Correlations between water levels at gauging stations, as well as correlations between groundwater levels and river water levels at gauging stations, are used to show the dependence of these parameters on the change in the river bed profile after sand and gravel mining at the locations near gauging stations. In addition, the homogeneity of time-series of average annual elevations and the variance of the water levels of the Velika Morava River, measured in gauging stations during different periods, are statistically analyzed. The deepening of the Velika Morava riverbed where it was indiscriminately excavated in the 1980s led to the disruption of the groundwater regime and the hydraulic connection with the river, which lowered the water table of the aquifer used for the public water supply, as well as causing a number of other negative consequences.

Soviet and Mongolian geologists initiated geological exploration of Mongolia for minerals after World War II (1945). These activities lasted until the breakup of the USSR in 1991. As part of this exploration systematic uranium and rare element exploration was undertaken across Mongolia. New exploration resumed in Mongolia at the beginning of the 21st century for a range of ore and mineral deposit styles including uranium, coal, base and precious metals and Fe-ore. This was generally undertaken by Western-based companies. This paper presents the results from regional reassessment by company exploration in 2011 for uranium radiometric anomalism found during the early Soviet investigations located north of Sainshand Provincial City and the results of preliminary prospecting studies near the town of Mandakh, both in southeastern Mongolia. These radioactive sites are characterized by elevated phosphate–uranium-rare element abundance. The primary company exploration objective of the new study was to confirm and characterize the anomalies and investigate in more detail the concentration of uranium and rare elements at these sites and assess the economic potential for their exploitation. A secondary objective based on the results from radiochemistry and rare element content was to highlight the potential environmental impact on livestock pastoral activities and wellbeing of nomadic families who graze their stock over the anomalous zones in the region. The source of most of the anomalism is considered derived from erosion and subsequent transport in solution or in heavy minerals from extensively eroded granites and mafic magmas of various ages into graben basins and drainage depressions in the windswept arid terrain. The economic potential of the sites explored was considered too low to be of exploration interest. The anomalism does require characterization for environmental health and safety purposes, given sheep, goats, camels and other livestock traditionally bred in Mongolia are grazing on the enriched pasture and nomadic people reside on, or in their vicinity of elevated zones of radiometric anomalism from anomalous uranium, radon and radium held in phosphorus enriched soils.

The study area is the city of Zintan, in northwestern Libya, which has grown over the past 30 years. Its current population is roughly 30,000. Although the city is in part commercial, most of the population engages in agriculture and primarily grows cereal crops (wheat and barley). The demand of the growing city for agricultural products has increased, intensifying the use of fertilizers, pesticides, and insecticides. Consequently, concentrations of potentially toxic elements (PTE) in the soil have increased. To assess the soil quality (to provide a snapshot of the condition of the soil), systematic sampling was undertaken across a grid of about 2 km × 2 km. The main objective was to determine the chemical and mineral composition of the area of interest, keeping in mind the geological footprint of the terrain. The geologic framework itself is not conducive to elevated concentrations of elements like U, Th, Mo, As, Hg, Pb, and Cr. Therefore, metal concentrations greater than the amounts in the Earth’s crust are most likely of anthropogenic origin. A total of 143 samples were collected and chemical analyses were performed using a Thermo Fisher Scientific Niton XL3t GOLDD+ XRF analyzer for the following elements: Mo, Zr, Sr, U, Rb, Th, Pb, Au, Se, As, Hg, Zn, W, Cu, Ni, Co, Fe, Mn, Cr, V, Ti, Sc, Ca, K, S, Ba, Cs, Te, Sb, Sn, Cd, Pd, and Ag. This paper provides examples of elevated concentrations, potentially harmful to the environment, such as those of the following: sulfur of unknown origin (two to three times higher than the Earth’s crust average); arsenic, given that there are no related natural phenomena (all the samples measured displayed concentrations higher than those found in the Earth’s crust); mercury (concentrations much higher than permissible levels); cesium (additional investigations required to determine the origin); molybdenum; and uranium likely resulting from the use of superphosphates (concentrations nearly always significantly higher than those in the Earth’s crust).