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The research subject is the application of geographic information systems (GIS) in assessing land suitability for agriculture in the Sana River Basin in Bosnia and Herzegovina. The aim of the research is to apply the analytic hierarchy process (AHP) in identifying suitable areas for agricultural production. Within the AHP framework, the following factors were considered: pedology, land use, elevation, slope, aridity index, and distance from rivers. The results of the suitability assessment underwent reclassification (RP) and cluster analysis processes (CAPs). It was found that very unsuitable land (1) covers an area of 0.15% (RP) or 5.83% (CAP), unsuitable land (2) covers 3.44% (RP) or 17.52% (CAP), conditionally suitable land (3) covers 32.11% or 28.47% (CAP), suitable land (4) covers 56.29% or 28.57% (CAP), and very suitable land (5) covers 7.98% (RP) or 19.59% (CAP). At the study area level, a supervised classification process was conducted to identify land use classes: meadows/pastures, water, forest, agricultural, and built-up areas. RP and CAP results were overlaid with supervised classification results to determine the amount of land used for agricultural purposes within each suitability class. It was determined that currently, for agricultural purposes, 0.04 km2 (RP) or 0.88 km2 (CAP) of very unsuitable land (1) is used, 0.41 km2 (RP) or 7.28 km2 (CAP) of unsuitable land (2), 15.75 km2 (RP) or 27.52 km2 (CAP) of conditionally suitable land (3), 185.15 km2 (RP) or 107.06 km2 (CAP) of suitable land (4), and 42.99 km2 (RP) or 101.65 km2 (CAP) of very suitable land (5). The research findings hold substantial importance in elucidating both the potential and constraints of land use practices as a vital natural resource within agriculture. They also have practical importance for relevant institutions in terms of agricultural sector development and making timely land use planning decisions for sustainable development.

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.

The subject of the research paper is the use of remote sensing in monitoring and analyzing the impact of climate change on the occurrence of extreme precipitation, and the cause-and-effect occurrence of floods in the area of the Sana River Basin in Bosnia and Herzegovina. The goal is to process the "product" of remote sensing to identify the time intervals of occurrence of extreme precipitation, to assess their impact on water levels, and to map potential floods in space. Spatial identification of zones that are at risk of flooding is an integral part of the aforementioned goal. Precipitation monitoring was performed by processing Climate Hazards Group InfraRed Precipitation with Station Data through the Google Earth Engine platform. The observed 30-year period (1992-2022) was compared with the average precipitation for 2017, 2018 and 2019. The impact of extreme precipitation on the water level of the Sana River was analyzed. Flooding periods have been identified: February and December 2017, March 2018 and May 2019. Mapping of flooded areas was carried out by pre-processing and post-processing of Sentinel-1 radar satellite images. The total flooded area is: 710.38 ha (February 2017), 496.79 ha (December 2017), 417.86 ha (March 2018) and 422.42 ha (May 2019). Based on the identified flooded areas, a flood risk map was created on the main course of the Sana River. The research contributes to a better understanding of the changes that occur in the area under the influence of climate change, and the data presented are important for numerous practical issues in the field of water resource management and flood protection.

The paper investigates the spatial distribution of the seasonal and annual precipitation in Bosnia and Herzegovina. The mean monthly precipitation data from 40 meteorological stations covering the standard climatological thirty-year period (1961-1990) were used for the analysis. Seven precipitation-based parameters were used to regionalize climate in Bosnia and Herzegovina by using the Principal Component Analysis and clustering techniques. The spatial patterns of precipitation were determined by using the R-mode principal component analysis with varimax rotation. The first two principal components, which describe 97.60% of the total variance, were taken into consideration. The varimax rotated scores were subjected to the Cluster Analysis in order to identify homogeneous precipitation regions over the territory of Bosnia and Herzegovina. The agglomerative hierarchical clustering identified three sub-regions with different precipitation regimes. The complex orography, i.e., the influence of the Pannonian Basin, the Dinaric Alps, and the Adriatic Sea, is one of the most decisive factors that affect spatial patterns of precipitation in Bosnia and Herzegovina. [ABSTRACT FROM AUTHOR]