The impact of tree litter on soil chemistry leachate and sulfurous substrates of mine soils from former Jeziórko sulfur mine was investigated. Composites were used: soil substrate (less contaminated at mean 5090 mg kg⁻¹ S or high contaminated at 42,500 mg kg⁻¹ S) + birch or pine litter and control substrate (no litter). The composites were rinsed with distilled water over 12 weeks. In the obtained leachate, pH, EC, dissolved organic carbon, N, Ca, Mg, Al, and S were determined. Physicochemical parameters of the substrates and their basal respiration rate were determined. Rinsing and litter application lowered sulfur concentration in high contamination substrates. Pine litter application decreased EC and increased pH of the low-contaminated substrate. The substrate pH remained at low phytotoxic level (i.e., below 3.0), resulting in the low biological activity of the composites. Birch litter application increased leaching of N and Mg, indicating the possibility of an intensification of soil-forming processes in contaminated sites.

The present research investigated the possibility of using PlanetScope imageries and LiDAR point clouds for land cover assessment, especially vegetation mapping, in degraded and reclaimed areas. Studies were carried out on the former sulfur mine of Jeziórko located in Southeast Poland. In total, more than ca. 2000 ha of this mine area were reclaimed after borehole exploitation and afforestation. We investigated a total area of 216.72 ha. Integration of PlanetScope imageries and LiDAR point clouds processing offers the ability to derive information about the LULC classes and vegetation growth in the analyzed area and indicate the forest succession progress as an effect of the reclamation treatments. In the Jeziórko area, we identified coniferous forest (90.84 ha, 41.91% of the research area), broad-leaved forest (44.02 ha, 20.31%), and transitional woodland shrub areas with herbaceous communities (77.96 ha, 35.97%). The analyses focused on the detection and monitoring of the forest succession processes and obtaining the tree canopy profiles and characteristics of vegetation, i.e., the height and cover density.

This paper investigates the possibility of using fusion Sentinel-2 imageries (2016, ESA) and light detection and ranging (LiDAR) point clouds for the automation of land cover mapping with a primary focus on detecting and monitoring afforested areas and deriving precise information about the spatial (2D and 3D) characteristics of vegetation for reclaimed areas. The study was carried out for reclaimed areas – two former sulfur mines located in Southeast Poland, namely, Jeziórko, where 216.5 ha of afforested area was reclaimed after borehole exploitation, and Machów, where 871.7 ha of dump area was reclaimed after open cast strip mining. The current land use and land cover (LULC) classes at the Machów and Jeziórko former sulfur mines are derived based on Sentinel-2 image processing, and confirmed the applied type of reclamation for both analysed areas. The following LULC classes showed a significant spatial range: broad-leaved forest, coniferous forest, and transitional woodland shrub. The progress of afforested areas, not only in terms of the occupied area, but also in terms of the growth of trees and shrubs, was confirmed. The results of the study showed differences in vegetation parameters, namely, height and canopy cover. Various stages of vegetation growth were also observed. This indicates an ongoing process of vegetation development, as an effect of the reclamation treatment for these areas.