Application of remote sensing in monitoring land degradation: A case study of Stanari municipality (Bosnia and Herzegovina)

The subject of the research represents the application of remote sensing in monitoring land degradation in the municipality of Stanari in Bosnia and Herzegovina (B&H). The aim of the study is to identify spatial changes during the research period (2017–2023) by processing remote sensing “products.” Within the changes in land use, the focus is placed on alterations resulting from surface mineral resource mining activities. The total approved exploitation area amounts to 3841.08 ha, covering almost a quarter of the municipality (23.89%). Monitoring changes in land use was conducted through the processing of Sentinel-2 images using supervised classification (SC). The classification results were compared with the Dynamic World (DW) dataset. Results indicate significant losses in forested areas, reduced by −7.23% (DW) or −2.43% (SC) at the municipal level and −11.48% (DW) or −5.90% (SC) within the exploitation area. Spatial extents of deforestation were identified and analyzed based on processing the Hansen Global Forest Data Change dataset. The deforestation area, caused by mining activity in B&H over the research period (2001–2021), amounts to 977.94 ha, with 264.25 ha (27.02%) within the Stanari municipality. Over 90% of the cleared forest area is within the exploitation area. High erosion coefficient values (Z) were recorded within the approved exploitation area, coinciding with the spatial coverage of deforestation. Additionally, results obtained using an empirical method for studying mechanical water erosion (W y) indicate a high intensity within the exploitation area. For the approved exploitation area, possibilities for the restoration of degraded land were analyzed, including an overview of activities conducted so far and mapping some of the previously reclaimed areas. The research contributes to a better understanding of spatial changes resulting from mining activities, and the presented data are significant for numerous practical issues, such as sustainable land use planning, spatial planning, protection of forest ecosystems, and the environment.