This paper elaborates soil, water, and lettuce contamination status with respect to selenium, sulphur, trace metals, and BTEX (benzene, toluene, ethylbenzene, and xylenes) in a coal-based area (Raša Bay, Adriatic Sea, Croatia). A local coal-fired power plant polluted soil with S, Se, Cd, and PAHs due to the combustion of domestic superhigh-organic-sulphur coal. The locality is dotted with waste from coal mining/separation, coal combustion, former metal factories, untreated municipal and coal mine effluents, along with various harbour activities, which contribute to environmental contamination. The methodology involved ICP-MS and GC-MS for the measurement of trace elements and BTEX, respectively, while soil sulphur was determined with Eschka’s mixture. The max values of the analysed trace elements in soil (mg/kg) are reported: Hg 1.14, Cd 3.29, V 624, Se 10.3, Pb 872, Cr 1860, Zn 6580, Cu 1850, and U 25.2. According to ecological indices, these values fall into the category of an extremely high level of soil pollution. Elevated total Se values in surface water are ascribed to leaching of seleniferous coal, ash, and coal-polluted soil. Levels of BTEX in water samples were very low (0–0.83 µg/L). The data provide basic information on the inorganic and organic contamination status of the Raša Bay area.

Recent development of lightweight and small size multi-frequency GNSS receivers allows determination of the precise position of the moving platform and spatial data acquisition without the need for setting up and measuring of ground control points. The main advantage of this approach is a higher operational capacity with reduced time and cost of field measurement. This relates to fieldwork in inaccessible areas with demanding terrain configuration. In this paper development and use of a UAS with direct georeferencing of camera sensor for spatial data acquisition is described, and the possibility of 3D scene reconstruction based on the precise position of the camera with predetermined interior parameters is examined. Modern computer vision-based SfM photogrammetry algorithms are used for determining attitude parameters and reconstruction of the scene. For that purpose, several tests on two different test fields were performed using various system parameters for collecting and analysis of several spatial data sets. The presented results demonstrate a satisfactory accuracy (3.1 cm planar and 6.4 cm spatial) of the system for various applications in geodesy.