Functional transformation of settlements in coal exploitation zones: A case study of the municipality of Stanari in Republic of Srpska (Bosnia and Herzegovina)

3.1 Methodology for monitoring previous functional transformation

The data used for the analysis of functional transformation within the settlement network were obtained from the population censuses of 1971 [69] and 2013 [67]. These sources include data from the time before surface mining began, as well as data from the most recent census conducted in B&H. The functional transformation of the settlement network at the municipal level was assessed using the ternary diagram method – Fehre’s triangle [70]. The ternary diagram method has been employed in earlier research examining functional transformation processes at the level of both local self-government units and settlements [11,14,20,21,29,32,34,42,44,70]. Changes in settlement functional types were monitored through the application of the settlement functional typology developed by Tošić [38], while a more detailed classification was carried out using the typology developed by Grčić [24,25]. The aforementioned typologies have been used in numerous studies on the functional structure and transformation of the settlement network in Serbia [16,17,18,20,21,23,28,32,33,34,36,39,40,41,42,44,45,46], but have not previously been applied to the territory of B&H. Their methodological foundation and relevance within a similar spatial and socio-economic context indicate the applicability of these typologies within the framework of this research. Both typologies are based on the method of calculating the share of employed persons by economic sector, with specific conditions regarding the relationships between these shares. Tripartite division into primary, secondary, and tertiary sectors has been widely used due to its analytical simplicity and historical prevalence in employment structure analysis. But, the model does not separately recognize the increasingly important quaternary sector, which encompasses knowledge-intensive activities such as scientific research, information technologies, and advanced services in education, culture, and management. However, for the purposes of this research, the quaternary sector has been integrated into the broader tertiary sector, in line with standard statistical classifications. This integration enables the application of previously established typologies and ensures comparability across datasets. In this way, 9 (Figure 3a) and 11 (Figure 3b) functional settlement types are distinguished, respectively.

Figure 3

Functional typology of settlements according to Tošić from 1999 [37] (a) and Grčić from 1999 [23] (b).

To assess the spatial distribution of functional transformation, the results obtained through the application of selected typologies were mapped using the geographic information system (GIS). GIS plays a central role in geospatial analysis, enabling the integration, visualization, and spatial modeling of complex environmental processes [71,72,73,74,75,76,63,77,78]. As an essential tool for geospatial analysis, GIS not only supports the systematic examination of spatial patterns and relationships, but also demonstrates remarkable applicability.

For the purposes of the analyses conducted in this study, QGIS 3.28 “Firenze” software (https://qgis.org/) was used. The impact of surface exploitation on the functional transformation of settlements was analyzed by considering each settlement’s distance from the current surface mine, as well as the proportion of its area currently affected by exploitation.

For this analysis, vector data representing settlements and exploitation zones in polygon geometry were used as input. The polygon layer of settlements was converted into point geometry (centroids) using the Centroids geometry tool in QGIS. Subsequently, the spatial relationship between settlement centroids and the surface mine was examined through vector-based proximity analysis. The shortest Euclidean distance between each centroid and the boundary of the mining polygon was computed using the Distance to Nearest Hub (points) algorithm, which enabled the identification of the closest point of contact between settlements and the exploitation zone.

Additionally, the extent to which each settlement is currently affected by surface exploitation was assessed through overlay analysis using the intersection geoprocessing tool. This procedure spatially intersected the settlement boundary polygons with the digitized footprint of the active surface mine, enabling the calculation of the affected area per settlement. The mine footprint was manually digitized from a Sentinel-2 satellite image (granule ID: S2C_MSIL2A_20250406T095051_N0511_R079_T33TYK_20250406T151618), acquired on April 6, 2025, and visualized using true color composite (Red [B4], Green [B3], and Blue [B2] – RGB), allowing for precise delineation of surface mining activities.

3.2 Methodology for monitoring hierarchy shifts in the settlement network

The data used for analyzing changes in the hierarchy of the settlement network were also obtained from the 1971 [69] and 2013 [67] population censuses. These sources include data from the period before the onset of surface mining, as well as from the most recent census conducted in B&H. The hierarchical transformation within the settlement network was tracked by analyzing changes in settlement centrality through the application of Schmook’s index [79] (1). This index calculates the degree of deviation in the share of employees in the tertiary–quaternary sector in a specific settlement compared to the regional average. One of the main advantages of this approach lies in its ability to enable a targeted analysis of individual central functions within each settlement. It also allows for the assessment of the specific capacity of other functional sectors, providing more detailed insights into the settlement’s role and overall functional structure. However, a notable limitation of this method is the potential distortion of centrality values, as the calculation includes the regional average – which also reflects the concentration of tertiary and quaternary functions in major central settlements. These often exceed the minimum needed to meet the population’s basic needs, thus inflating centrality values in comparative terms. Despite this limitation, Schmook’s index was selected for its practicality and alignment with the objectives of this study, having been successfully applied in previous analyses of hierarchical shifts within settlement networks [19,22,47,80,81]. The formula for calculating the centrality index (C) is as follows [79]:

where A S represents the total employed population in the settlement, TQ s is the number of people employed in the tertiary–quaternary sector within the settlement, TQ m refers to the number of people employed in the tertiary–quaternary sector at the municipal level, and A m denotes the total employed population in the municipality. Positive values derived from this calculation point to the significance of centrality within the settlement [82]. In addition, the significance of secondary sector activities (SSA) was assessed using a modified version of Schmook’s index (2), which has been employed in comparable research contexts [22,81]. The secondary sector includes activities associated with the mining and processing of ores, energy production, and the manufacturing of material goods [7]. The SSA index was computed for both 1971 and 2013 to identify settlements where the importance of SSA either increased or decreased over time. Due to differences in sectoral classification between the 1971 and 2013 census methodologies, a harmonization process was conducted based on the classification of activities provided by the Institute of Statistics of the RS [83]. In the 1971 census, the secondary sector included the following activities: industry, mining, and construction. In the 2013 census, it comprised: mining and quarrying, manufacturing, electricity supply, water supply, and construction. SSA was determined using an adjusted formula:

where A S represents the total employed population in the settlement, SS s is the number of people employed in SSA within the settlement, SS m refers to the number of people employed in SSA at the municipal level, and A m denotes the total employed population in the municipality. Given the spatial and economic specificity of the study area, special emphasis was placed on the analysis of mining activities as a key component of the secondary sector. In line with the aim of this research, a modified Schmook’s index was also applied to examine the significance of mining and related activities (SMA), in order to identify settlements where the mining function plays a dominant role (3). To assess whether the importance of these activities has increased or declined across individual settlements, the SMA index was computed for both 1971 and 2013. The data for its calculation were derived by extracting mining-related activities from the overall secondary sector. For the year 1971, mining activities included those directly or indirectly related to mining operations, namely, industry and mining. In the 2013 classification, they encompassed mining and quarrying, manufacturing, and electricity supply. The adjusted formula for determining SMA is as follows:

where A S represents the total employed population in the settlement, MA S refers to the number of people employed in mining activities within the settlement, MA m denotes the number of people employed in mining activities at the municipal level, and A m is the total employed population in the municipality.

The graphical interpretation of changes in the settlement network hierarchy based on C, as well as SSA and SMA, was conducted using Rochefort method [84], which has also been applied in similar studies [19,81]. The formula for determining the position of a settlement based on the centrality (4) within the coordinate system (X and Y coordinates) is as follows [84]:

where TQ s represents the number of people employed in the tertiary–quaternary sector within the settlement, A m denotes the total employed population in the municipality, and TQ m refers to the number of people employed in the tertiary–quaternary sector at the municipal level.

The formula for determining the position of changes in the settlement network hierarchy based on SSA (5) within the coordinate system (X and Y coordinates) is as follows:

where SS s is the number of people employed in SSA within the settlement, A m denotes the total employed population in the municipality, and SS m refers to the number of people employed in SSA at the municipal level.

The formula for determining the position of changes in the settlement network hierarchy based on SMA (6) within the coordinate system (X and Y coordinates) is as follows:

where MA S refers to the number of people employed in mining activities within the settlement, A m is the total employed population in the municipality, and MA m denotes the number of people employed in mining activities at the municipal level.

3.3 Methodology for assessing future functional transformation

In order to anticipate the potential directions of future functional transformation within the settlement network, the results obtained through the application of functional typologies and the calculation of settlement centrality indices were compared with the spatial extent of the approved exploitation field. As for the projected impact of future surface exploitation on settlements, it was evaluated using the intersection geoprocessing tool in QGIS software, by overlaying the polygon boundaries of settlements with the vector layer representing the approved exploitation field. This vector layer was digitized based on publicly available coordinates from the Cadastre of Approved Exploitation Fields, published by the Ministry of Energy and Mining of the RS. The resulting intersection enabled the calculation of the proportion of each settlement’s area expected to be affected by future surface mining.

The prediction of potential functional transformation within the settlement network was methodologically enriched by an analysis of survey data on residents’ intentions regarding relocation and changes in employment. These indicators were selected for analysis because intentions to relocate and change employment directly affect the potential destabilization of the existing functional structure within the settlement network. For this purpose, a survey was conducted in the territory of the Stanari municipality during 2024, among the local population, employees of public institutions (municipal administration, primary school, health center), and workers employed at the TPP. The survey was anonymous and included 373 adult respondents. Given that the focus of the analysis is the functional transformation of settlements, only the responses of employed individuals were considered relevant. Accordingly, the dataset was filtered by excluding the responses of unemployed and retired participants. Following this procedure, the final sample consisted of 261 respondents, representing 16.08% of the employed population in the Stanari municipality [68]. In order to identify the spatial pattern of potential settlement transformation in the future, respondents’ answers regarding their place of residence were analyzed in relation to their stated intentions concerning relocation and the retention of their current job after relocation. All responses were digitized and processed using IBM SPSS Statistics 23, through the application of Crosstabulation and the Pearson Chi-Square (χ ²) test, with Monte Carlo simulations. The results were mapped at the level of settlements within the municipality of Stanari using QGIS software.

4.1 Previous functional transformation

In order to analyze the general functional transformation of the settlement network, and in accordance with the previously described methodology, a ternary diagram of the functional structure for the year 1971 was created, illustrating the functional orientation of settlements prior to the opening of the surface coal mine (Figure 4a), as well as a ternary diagram of the functional structure for the year 2013, showing the contemporary functional orientation of settlements (Figure 4b). Each corner of the triangle corresponds to the proportion of the employed population working in the primary (A), secondary (B), and tertiary (C) sectors, respectively. In 1971, the majority of settlements were oriented toward the primary sector. More than half of the settlements (Brestovo, Mitrovići, Radnja Donja, Cvrtkovci, Jelanjska, Cerovica, and Dragalovci) had an exclusively agrarian function. The remaining settlements (Ostružnja Gornja, Raškovci, Ostružnja Donja, Ljeb, Osredak, and Stanari) were mostly slightly oriented toward activities in the secondary sector. The only settlement that deviated from this pattern was Stanari, which showed a noticeable share of employment in the secondary sector, indicating early industrial or mining activities. Overall, the functional structure of the municipal settlement network exhibited a monofunctional agrarian character. The current functional orientation of the settlement network reflects a more complex and diversified structure. All settlements underwent a decline in employment in the primary sector and a rise in the secondary and tertiary sectors. Settlements such as Raškovci and Dragalovci exhibit a stronger industrial orientation, which can be explained by the presence of coal exploitation in these areas. The settlement of Stanari stands out in particular, as it was positioned in 2013 along the axis between the secondary and tertiary sectors, with minimal employment in the primary sector.

Figure 4

Ternary triangle of the functional orientation of the settlement network in 1971 (a) and 2013 (b).

This structure indicates the development of industrial, mining, and service functions. The functional transformation of the settlement network during the observed period points to a process of deagrarianization, i.e., a declining role of agriculture within the overall economic structure. The results indicate that the diversification of traditional rural economies has been driven by an increase in the share of service-sector activities, as well as energy production – both of which represent ongoing trends in rural areas of Central and Eastern Europe [13]. An example of this broader trend of economic restructuring from agriculture to mining is found in the town of Boddington, Australia [10] which illustrates the shift observed in many rural communities worldwide. The study by Kerker and Vogel [15] highlights new functions of rural areas in Germany, including, among others, the function of energy production. A similar pattern of functional transformation toward deagrarianization within the settlement network has been observed in Serbia as well [20,21,29,32,34,42,44].

In order to determine the impact of mining activities and surface exploitation on parts of the settlement network, and in accordance with the previously described methodology, the functional type of each individual settlement was identified for the years 1971 and 2013. Two functional typologies were applied: the first, developed by Tošić [38], classifies settlements based on sectoral dominance (≥60%) in the employment structure into nine types (Figure 3a); the second, developed by Grčić [24], classifies settlements based on the share of the primary sector in employment, resulting in 11 settlement types (Figure 3b). According to Tošić’s typology, in 1971 the entire settlement network exhibited an agricultural character (Figure 5a), with the exception of the settlement of Stanari, which, although still agricultural, was classified as an agro-industrial settlement due to its modified structure. According to the same typology, the settlement network in 2013 displayed a more complex functional structure (Figure 5b). All settlements, except for Cvrtkovci, underwent changes in their functional type, to varying degrees. Settlements located in the immediate exploitation zone (0–1,500 m), whose territory overlaps with the active surface mine, were classified as industrial settlements. Settlements within the medium-distance zone from current surface mining (1,501–3,000 m) were reclassified into transitional types – such as industrial-agricultural, industrial-service, or service-industrial settlements – except for Cvrtkovci, which retained the agricultural type. The most distant settlements from the current exploitation area (>3,000 m) were functionally transformed into transitional types, most often industrial-agricultural or agro-industrial. The settlements of Osredak, Jelanjska, and Ostružnja Gornja could not be precisely assigned to any single category from the typology, as their employment structures reflected relatively balanced shares across all three sectors. However, these settlements recorded higher proportions of employment in the secondary and tertiary sectors, indicating a departure from their 1971 agricultural orientation.

Figure 5

Functional typology of settlements in the municipality of Stanari according to Tošić's methodology from 1999 [37] in 1971 (a) and 2013 (b).

On the other hand, according to Grčić’s typology, the functional structure of the settlement network in 1971 was entirely agrarian in character, with over 60% of the population employed in the primary sector (Figure 6a). More than half of the settlements in the network were classified as highly agricultural, while the remaining settlements exhibited modified agricultural functional types. Settlements located in the most distant zone from the area of current exploitation (Jelanjska, Mitrovići, Cerovica, Radnja Donja, and Brestovo) showed a distinctly agrarian character, whereas those situated closer to the mining zone were categorized as modified agricultural types. According to the same typology, the functional structure of the settlement network in 2013 became significantly more complex (Figure 6b). Only three settlements retained to some extent their former 1971 functional character – Brestovo (which shifted from a highly agricultural type to a moderately agricultural type), Mitrovići (also from highly to moderately agricultural), and Cvrtkovci (from highly agricultural to predominantly agricultural type). All other settlements in the network underwent a functional transformation. Settlements in the immediate vicinity of surface mining activities (0–1,500 m) transitioned into industrial types, with the most notable example being Raškovci, which shifted from a predominantly agricultural type in 1971 to a moderately industrial type in 2013. This settlement is the most affected by surface coal mining, with 46.37% of its territory under exploitation (Table 1). The population of settlements closest to the exploitation area moved away from employment in the primary sector and reoriented toward the secondary sector, indicating an intensive process of deagrarianization. Settlements located in zones further away from the mine (1,501–3,000 m and >3,000 m) show varying patterns of functional transformation, with a general tendency to abandon agricultural activities in favor of secondary or tertiary sector employment. These more distant zones also include the few settlements that experienced minimal functional transformation – namely, Brestovo, Mitrovići, and Cvrtkovci. The presence of coal exploitation has had a significant impact on the transformation of the functional structure of settlements, with the most pronounced changes occurring in those nearest to the surface mine. The spatial decline in influence reveals a clear gradient in the process of deagrarianization and a gradual industrialization of the affected areas.

Figure 6

Functional typology of settlements in the municipality of Stanari according to Grčić's methodology from 1999 [23] in 1971 (a) and 2013 (b).

4.2 Hierarchy shifts in the settlement network

In accordance with the previously described methodology, centrality was analyzed in order to gain insight into the hierarchical relationships within the settlement network during the observed period (Figure 7). In 1971, the centrality values (C) for most settlements were close to 1 or negative, indicating that these settlements lacked characteristics of centrality and had little to no central function. The settlements that stood out with high centrality values were Stanari (69.56) and Osredak (42.50), indicating the development of tertiary–quaternary sector activities in settlements located near the former mining site. The structure of centrality in the network exhibited a polarized character, with a pronounced hierarchy dominated by only two settlements. By 2013, centrality values increased in most settlements, suggesting a greater dispersion of tertiary–quaternary activities throughout the settlement network. However, despite the overall increase, centrality values were not positive in all settlements. The most significant decline in centrality and the lowest recorded value was observed in Cvrtkovci (–32.80). The most intensive increase and the highest positive centrality values were registered in the settlements of Lјeb (25.28) and Ostružnja Donja (13.05). Although Stanari – the central settlement – maintained a positive centrality value (25.19), it experienced a noticeable decline. These findings indicate that service functions are increasingly developing outside the central settlement, contributing to a reduction in hierarchical imbalance within the network.

Figure 7

C index scores for settlements in Stanari municipality in 1971 and 2013.

The analysis of the graphical interpretation of centrality provides insight into the position of each settlement within the network hierarchy, as well as changes in their relative position during the observed period (Figure 8). In 1971, most settlements occupied a low position in the hierarchy in terms of both the relative share of employment in the tertiary–quaternary sector compared to total municipal employment (X-axis) and the relative share of employment in the tertiary–quaternary sector compared to total employment in that sector at the municipal level (Y-axis) (Figure 8a). The settlement of Stanari stood out with a particularly high position relative to other settlements, suggesting that it already performed the role of a central settlement prior to the onset of intensive surface mining. Osredak also occupied a high position, but with lower values along the X-axis, implying a degree of specialization in the tertiary–quaternary sector, yet lacking a strong economic base. The hierarchy within the settlement network based on centrality in 2013 exhibited a more balanced character compared to 1971 (Figure 8b). In most settlements, the number of people employed in the tertiary–quaternary sector increased relative to the total employment in the municipality. Furthermore, there was a shift in the position of certain settlements in terms of the share of employment in the tertiary–quaternary sector relative to the total employment in this sector at the municipal level (Y-axis); these include Lјeb, Raškovci, Cvrtkovci, and Dragalovci. A significant shift in the hierarchical structure occurred in the settlements of Ostružnja Donja and Cerovica, indicating a diversification of functions and a strengthening of the economic base in these settlements. The settlement of Stanari continues to occupy the highest position in the hierarchy, thereby retaining its role as the central settlement.

Figure 8

Settlement hierarchy according to centrality in 1971 (a) and 2013 (b).

The settlements that experienced a shift in their position within the settlement network hierarchy also changed their functional type from agricultural to various forms of industrial type. For this reason, it is important to analyze employment patterns in the secondary sector as well. Using the same methodology applied for calculating centrality (i.e., the concentration of employment in the tertiary–quaternary sector), the significance of secondary sector activities (SSA) was calculated. In 1971, the settlements with the highest SSA values were Ostružnja Donja (55.88) and Stanari (48.98), indicating their importance in terms of secondary sector employment (Figure 9). Relatively high SSA values were also recorded in the settlements of Lјeb (30.15) and Raškovci (29.01). In other settlements, the SSA values were not significant. By 2013, evident changes occurred in employment within the secondary sector (Figure 9). In Stanari, although the SSA value remained positive (12.21), a significant decrease was observed. In contrast, other settlements experienced an increase in SSA, indicating moderate industrial activity. Dragalovci recorded a substantial increase in SSA (from –27.17 to 25.56), pointing to a strengthening of the role of SSA. Notably, in 2013, the construction of the TPP began in this settlement. The plant’s location corresponds to the area showing the greatest positive change in SSA, suggesting a direct impact of this economic facility on the transformation of the local functional structure through the pronounced concentration of labor.

Figure 9

SSA index scores for settlements in Stanari municipality in 1971 and 2013.

The hierarchy within the settlement network based on SSA in 1971 was relatively balanced (Figure 10a). The settlements that occupied dominant positions within the network hierarchy were Stanari, Ostružnja Donja, and Cerovica. In other settlements, both the size of the economic base (X-axis) and the share of employment in SSA relative to total employment in that sector at the municipal level (Y-axis) were considerably lower. Settlements that exhibited a relatively higher concentration of employment in SSA included Raškovci, Lјeb, and Jelanjska. By 2013, the SSA-based hierarchy within the settlement network showed clear positional shifts among settlements (Figure 10b). Growth was observed both in terms of the strengthening of the economic base (Y-axis) and the increased share of employment in SSA (X-axis). There were also notable changes in the relative positions of individual settlements within the network. In addition to settlements that were already highly positioned in 1971, Raškovci and Dragalovci joined the group of settlements with high SSA values, indicating the development of SSA in these areas. Other settlements that had been marginalized in terms of SSA in 1971 now show moderate upward movement in the hierarchy, pointing to a gradual establishment of spatial balance and the decentralization of secondary sector functions within the settlement network.

Figure 10

Settlement hierarchy according to SSA in 1971 (a) and 2013 (b).

Within the scope of further analysis, the results of the SMA index within the structure of the secondary sector stand out, as they allow for the assessment of the impact of mining on the economic base of settlements and their position within the network hierarchy. In 1971, the highest SMA values were recorded in the settlements of Ostružnja Donja (54.06), Stanari (43.43), and Raškovci (23.84) (Figure 11). Other settlements displayed lower or negative SMA values, indicating that mining and related industries had a strong influence on only a few settlements. The SMA values for 2013 (Figure 11) show that the settlements which played a leading role in 1971 largely retained their position, although the SMA values declined in Stanari and Ostružnja Donja. However, the SMA value increased in the settlement of Raškovci (35.30), positioning it as the most significant settlement within the network in terms of the role of mining and associated activities. Some settlements that had low SMA values in 1971 experienced a slight increase, while others continued to record negative values. These results point to a partial decentralization of mining and industrial activities within the settlement network.

Figure 11

SMA index scores for settlements in Stanari municipality in 1971 and 2013.

The settlement network hierarchy based on SMA in 1971 reveals a clear dominance of two settlements – Ostružnja Donja and Stanari (Figure 12a). These two settlements stood out with the highest significance of mining activities, both in terms of the share of mining-related employment in total local employment (X-axis), and in terms of their contribution to overall municipal employment in the mining sector (Y-axis). Their position in the diagram (Figure 12a) indicates a high level of specialization and concentration of labor in mining and industrial activities. Raškovci also displayed a relatively prominent position within the hierarchy, although considerably lower than the two leading settlements. Other settlements such as Ostružnja Gornja, Cerovica, Lјeb, Jelanjska, Osredak, and Radnja Donja were positioned in the lower portion of the graph, with low values on both axes, suggesting a marginal role of mining activities in their economic structure. At the lowest positions in the settlement hierarchy were Brestovo, Dragalovci, Mitrovići, and Cvrtkovci, indicating a complete absence of mining activities in their economies. By 2013 (Figure 12b), significant changes occurred in the SMA-based hierarchy. Although Stanari and Ostružnja Donja retained their leading positions, the gap between them narrowed, suggesting a reduced difference in the intensity of mining and industrial activities between these key settlements. Raškovci showed a clear upward shift on both axes, thus joining the group of mining-significant settlements. Settlements that had played a marginal role in mining in 1971 now show moderate growth, although they still occupy lower positions in the hierarchy. Increases in both X and Y-axis values are evident in settlements such as Ostružnja Gornja, Cerovica, and Cvrtkovci, indicating a mild decentralization of mining functions. Nevertheless, the majority of settlements – including Brestovo, Mitrovići, and Dragalovci – maintain low values, reflecting the limited spatial extent of mining and industrial activities. Overall, the SMA-based hierarchy in 2013 exhibits a softer polarization compared to 1971, but two dominant mining centers – Stanari and Ostružnja Donja – continue to prevail. The repositioning of other settlements within the network indicates a gradual upward movement in the hierarchy with respect to mining activity.

Figure 12

Settlement hierarchy according to SMA in 1971 (a) and 2013 (b).

Overall, the results highlight the far-reaching impacts of coal mining on the functional and hierarchical structure of settlements within the municipality. Beyond economic restructuring and changes in employment patterns, these processes have triggered complex demographic, spatial, and environmental transformations.

In the context of ongoing and future coal exploitation, the application of sustainability principles is crucial for establishing a balance between economic development, environmental protection, and social welfare. While coal mining is an important driver of local economic growth and employment, it also brings significant challenges in terms of land degradation, loss of agricultural function, and population displacement [1]. These aspects become particularly prominent when considering the future functional transformation of the settlement network, which will be directly shaped by the continuation and expansion of mining activities in the coming period.

4.3 Future functional transformation

By comparing the functional typology of the settlement network with the spatial extent of the designated mining concession area, it is possible to identify settlements that are likely to undergo a functional transformation as a result of future coal exploitation. Analysis of the approved concession field reveals that mining activities will continue in settlements where exploitation is already underway and will expand to include additional settlements to varying degrees. Three groups of settlements can be distinguished based on the percentage of their territory projected to be affected by future exploitation: the first group will not be affected; the second group will be affected up to 30%; and the third group will be affected by more than 60%, with some exceeding 80%. Settlements that will not be affected by mining activities (Table 1, Figure 1) include Brestovo, Mitrovići, Radnja Donja, and Cvrtkovci. It can be concluded that these settlements are unlikely to experience significant changes in their functional types and that coal exploitation will not directly impact their functional structure. However, due to their relative proximity to the mining zone, indirect impacts are possible – particularly with regard to migration flows, labor redistribution, and the potential for the development of service or auxiliary activities. In this regard, moderate increases in the values of indicators C, SSA, and SMA may occur, potentially resulting in a slight upward shift of these settlements within the hierarchical structure of the settlement network. New settlements projected to be partially included in future surface mining – up to 30% of their territory – include Jelanjska, Lјeb, Stanari, and Cerovica, along with Dragalovci, where exploitation is already taking place. It is expected that mining activities will influence the functional types of these settlements to varying extents, depending on the speed and direction of expansion. In terms of indicators, an increase in SSA is anticipated, particularly in those settlements with an already established industrial base. Likewise, the SMA indicator is expected to rise as a result of direct engagement in mining and industrial activities. The C indicator may also increase if the development of service functions accompanies industrial growth. However, if service sectors are neglected, a stagnation or even decline in centrality could occur. These settlements will therefore be subject to varying degrees of functional transformation, influencing their position within the settlement network. The group of settlements projected to be affected by more than 60% includes those where mining is already active – Raškovci and Ostružnja Donja – as well as Osredak and Ostružnja Gornja, where mining has not yet started (expected to exceed 80% of the territory). Given the nature of surface mining, this group is likely to undergo a complete functional transformation and experience significant population displacement, which may ultimately result in demographic destabilization and the loss of both function and centrality. A considerable increase in the SMA indicator is expected due to the intensification of mining and industrial activity. However, if service and support functions collapse, the values of the C and SSA indicators may stagnate or decline. Moreover, a decline in the hierarchical structure of the network is possible if these settlements are reduced to purely technical exploitation zones without stable tertiary sector functions. The realization of the projected mining scenario, in line with the approved concession area (Table 1, Figure 1), will lead to complex functional and hierarchical changes across the settlement network. Given the spatial effects and dynamics of surface mining, as well as the extended time required for land reclamation, a shift of the demographic and economic base toward the northern part of the municipality can be anticipated. Settlements not affected by mining may become relocation destinations for populations displaced through expropriation of land and property. This scenario is also envisioned in the current spatial plan of the municipality [85] and could be implemented through the targeted relocation of residents to other settlements within the municipal settlement network.

4.4 Residents’ perceptions of relocation and employment change

In order to estimate the potential spatial patterns of future population relocation, responses from local residents who participated in the survey were analyzed. The first step in the survey involved examining the relationship between place of residence and the decision to relocate under different coal exploitation scenarios in the municipality. The analysis included 260 respondents (99.6%), while one response was missing (0.4%). A cross-tabulation and Chi-square test were conducted. The results of the cross-tabulation indicate that residents of certain settlements exhibited distinct patterns in their relocation decisions, depending on the scenario (continuation or permanent cessation of coal exploitation). The highest number of respondents who stated that they would not leave their settlement under either scenario came from Stanari (n = 62), accounting for 42.8% of all respondents in this category. Conversely, respondents from Ostružnja Gornja were more likely to relocate only in the event of a permanent cessation of mining activities (27.3% of that category). Similarly, residents of Ostružnja Donja and Cvrtkovci showed a greater tendency to relocate in both scenarios, suggesting a higher sensitivity of certain settlements to the continuation or termination of mining activities. The Chi-square test revealed a statistically significant association between place of residence and the decision to relocate (χ ² = 82.998; df = 48; p = 0.001). Given that 80% of the cells in the table had an expected frequency of less than 5, a Monte Carlo simulation with 10,000 samples was performed, confirming statistical significance (p = 0.008; 99% CI: 0.006–0.011). This indicates that the decision to potentially relocate is significantly influenced by the place of residence. Although the likelihood ratio was at the threshold of significance (p = 0.057), the Monte Carlo estimate in this case also confirmed statistical significance (p = 0.030). Fisher’s Exact Test yielded a p-value close to the conventional significance threshold (p = 0.053). The linear-by-linear association test did not show a significant relationship (p = 0.576), which is expected given the categorical nature of the variables. These findings suggest that respondents’ spatial affiliation (i.e., the specific settlement in which they reside) influences their perceptions of the future under different exploitation scenarios. This may reflect varying degrees of exposure to the negative effects of coal exploitation, the duration of mining activity in certain settlements, and the degree of local economic dependence on mining-related employment.

Relocation from the current place of residence entails not only a shift in the demographic structure, but also a transformation of the economic base. To estimate the potential spatial pattern of changes in the economic base – i.e., the functional type – an analysis was conducted to examine the relationship between the place of residence and the intended employment solution after potential relocation. A total of 255 respondents with valid responses were included in the analysis. The potential association between these two variables was examined using the Chi-square test of independence. The results of the cross-tabulation revealed significant differences among settlements in terms of respondents’ preferred employment solutions. In the settlement of Stanari, the highest number of respondents stated they would seek new employment in the new place of residence (n = 26; 47.3%). Settlements such as Ostružnja Donja and Lјeb recorded a relatively higher percentage of respondents who would look for new employment after relocating, while settlements like Osredak and Mitrovići showed an increased share of “no answer” responses. The Chi-square test confirmed a statistically significant association between place of residence and employment solution (χ ² = 60.221; df = 36; p = 0.007). Given that 76.9% of cells had an expected frequency below 5, the results were additionally verified using a Monte Carlo simulation with 10,000 replications. The resulting p-value (p = 0.012; 99% CI: 0.010–0.015) confirmed the statistical significance of the findings. The likelihood ratio test also showed significance (p = 0.033), while Fisher’s Exact Test was on the threshold of statistical significance (p = 0.050). The linear-by-linear association test did not show a significant relationship (p = 0.898), indicating that there is no gradual or predictable trend between settlements and employment choices. Rather, differences in responses occur without a clear pattern and independent of one another. These findings suggest that the place of residence significantly influences how respondents perceive their employment future in the context of potential relocation – whether by retaining their current job or seeking new employment. Spatial affiliation plays an important role in shaping decisions related to the economic stability of the population within the zone affected by coal exploitation.

In order to explore spatial differences in relocation intentions and potential employment changes, a summary analysis was conducted of respondents who expressed both a willingness to relocate under any scenario and to change jobs following relocation. Responses concerning relocation intentions were classified into four categories: very low willingness to relocate (0–25.1% of respondents willing to relocate), low to moderate willingness (25.1–41.0%), moderate willingness (41.0–61.0%), and high willingness to relocate (>61.0%) (Figure 13a). Very low willingness to relocate was recorded in the settlements of Brestovo, Mitrovići, and Osredak. On the other hand, settlements whose populations showed high willingness to relocate under at least one exploitation scenario include Jelanjska (64.3%) and Raškovci (76.9%), where surface coal mining is currently ongoing. In the settlement of Stanari, the central settlement of the municipality, 43.6% of respondents indicated willingness to relocate under one of the scenarios. The survey results point to dynamic changes in the demographic base across the settlement network. Only three settlements are likely to maintain demographic stability without migration caused by surface mining, while in all other settlements, mass outmigration may occur – including the settlement of Stanari, which serves as the central settlement of the municipality, where a moderate level of willingness to relocate was recorded (Figure 13a).

Figure 13

Attitudes of the local population in the settlements of Stanari municipality regarding willingness to relocate (a) and change employment (b).

Regarding respondents’ attitudes toward changing employment after relocation, the choice of this response implies not only the departure from current employment but may also reflect the potential loss of the settlement’s existing employment function. Responses regarding willingness to change employment were classified into four categories: no change (0% of respondents who would change jobs), very low willingness to change jobs (0.01–15.0% of respondents who would change jobs), moderate willingness to change jobs (15.01–31.0% of respondents who would change jobs), and high willingness to change jobs (>30.01% of respondents who would change jobs) (Figure 13b). Survey results indicate a high willingness to change employment in the settlements of Raškovci (41.7%) and Ostružnja Donja (36.8%). In this context, settlements with a higher proportion of residents expressing an intention to change employment may be exposed to processes of functional destabilization, which could have potential consequences for the sustainability of their existing functional structure. A scenario of potential functional transformation caused by employment change following relocation is also anticipated in settlements with a moderate level of willingness to change employment, including Lјeb (26.7%), Jelanjska (21.4%), and the Stanari (24.1%), central settlement of municipality (Figure 13b).

Relocation will be inevitable in settlements located within the boundaries of the approved exploitation field. The displacement caused by mining activities, in addition to requiring the development of exit strategies for relocation and employment, may also lead to psychological challenges among the local population [86,87]. Physical displacement, relocation, and resettlement have been recognized as processes carrying substantial risks for communities directly affected by mining operations [88]. Given the complexity of mining-induced processes, future research should focus on exploring local residents’ perceptions of quality of life in the immediate vicinity of mining activities, as well as their relocation strategies. In their study of the relationship between households, livelihoods, and resettlement caused by mining, Adam et al. [89] emphasized the importance of policy-makers ensuring transparency in handling the material aspects of resettlement and highlight the value of household-level research. The results of such studies can provide decision-makers with valuable guidance for aligning mining operations – imperative as an economic driver – with the needs of the local population. Research on mining-induced resettlement in Sierra Leone also underscores the necessity of developing legal frameworks that ensure alternative sources of livelihood for displaced persons [54]. Additionally, educating residents of mining communities about relocation-related legal provisions is essential [57]. The implementation of targeted strategies can help prevent homelessness and unemployment [56], and contribute to the establishment of mechanisms for long-term demographic stability and a balanced functional structure within the settlement network.