Land use dynamics and urban development suitability: A geospatial analysis of Romania’s most urbanized county

Land use dynamics and urban development suitability: A geospatial analysis of Romania’s most urbanized county | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Land use dynamics and urban development suitability: A geospatial analysis of Romania’s most urbanized county Cristina Elena Mihalache, Monica Dumitrașcu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6892590/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Apr, 2026 Read the published version in Environmental Modeling & Assessment → Version 1 posted 11 You are reading this latest preprint version Abstract Land use and land cover changes in Constanța County are linked to socio-economic and political transformations, particularly during two key periods: the transition period (1990–2003), marked by a shift from a centralized economy to a market-oriented system, and the post-transition period (2003-present), characterized by continued economic growth and urban expansion. These transformations align with broader trends in post-socialist and rapidly urbanizing regions, where economic restructuring often precipitates the large-scale conversion of agricultural land into built-up areas. This study employs CORINE Land Cover datasets to assess nearly 30 years of land use and land cover changes. Given the observed trends of increasing artificial surfaces and the decline of forest and semi-natural areas, a suitability analysis was conducted to deliver a spatially explicit evaluation of areas with potential for urban expansion. The integration of spatial, contextual, and environmental variables in the suitability analysis clearly demonstrated that cities situated in immediate proximity to the coastline possess a markedly low potential for further urban expansion. Situated along the Black Sea coast, Constanța is the most urbanized county in Romania. It serves as a representative case for examining urbanization dynamics in coastal regions worldwide. In these areas, proximity to the sea accelerates urban growth, while also increasing vulnerability to environmental degradation. These findings provide valuable insights for other coastal cities facing similar development pressures, emphasizing the need for careful balancing of urban growth with environmental protection. This approach supports informed planning, particularly in regions undergoing accelerated land use transformations, a pattern common in fast-growing urban areas globally. Urbanization Urban Land Use Suitability Land Use Change Urban Planning Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Land use and land cover (LULC) dynamics have remained a focal point of scientific research for their role in forming the foundation for understanding surface cover and human utilization of lands. Even with their extensive study, LULC still remains fundamental in devising sustainable planning frameworks, as they underpin policies concerned with environmental monitoring and resource management [ 1 ]. The identification of LULC patterns is of vital importance in the activities of conservation and resource mitigation, as they can enlighten how landscapes evolve under human influence. Global studies conducted between 1960–2019 have shown that about 32% of the global land surface was affected by land use changes [ 2 ]. Recent studies conducted in the last 30 years have documented an acceleration process of LULC change with an average annual rate of 0.36% [ 3 ] The pattern of evolution in LULC is often portrayed in the landscape of regions and, therefore, carries a representational relationship with significant environmental features. On one hand, there is the demand of society for resources and space; on the other hand, there is an Earth that can support these demands only up to a point. Besides this, extensive and intensive use of land beyond the limits of sustainability, together with extreme degradation of landscapes and ecosystems, leads to considerable and often irreversible environmental changes. To achieve sustainable land resource use, the first step is to understand the historical condition, status, and patterns of change in land use [ 4 ]. Furthermore, it is relevant to explore the key drivers of the LULC changes. Over time, scientists have demonstrated that the increase in population, urbanization, and the demand for residential space puts an immense amount of pressure on agricultural land and natural resources [ 5 ] with significant implications for climate change and biodiversity [ 6 ], [ 7 ], [ 8 ], [ 9 ], [ 10 ], [ 11 ]. Additionally, political factors and legislative measures are key drivers influencing land use and cover changes [ 12 ], [ 13 ]. In the context of Romania, studies have shown that these socio-economic and political drivers have played a crucial role in the evolution of LULC over time [ 14 ], [ 15 ], [ 16 ], [ 17 ], [ 18 ], [ 19 ], [ 20 ], [ 21 ], [ 22 ]. In pre-modern times, traditional agriculture was the main source of income for the local population. The land was mainly used for growing crops and raising livestock, reflecting a predominantly rural economy. During this period, communities were made up of small villages and the inhabitants depended on the natural resources of the region for their livelihood [ 23 ]. Constanța County is an important industrial hub, owing to its strategic location on the border between Romania and Bulgaria, with direct access to the Black Sea. Also, here is the most important coastal tourist area of ​​Romania as well as the largest port of Romania on the Black Sea. Consequently, the region has seen the development of numerous factories and industrial facilities, particularly in sectors such as metal processing, electrical and electronic equipment manufacturing, and textiles, among others. This industrial development has had a significant impact on the county’s economy, generating an increase in jobs and an improvement in living standards. However, it has also contributed to the reduction of natural and agricultural land and the expansion of built-up areas, with effects on the environment and quality of life. The period after the fall of communism has been described by specialists as being divided into two phases: the transition period (1990–2003) and the post-transition period (2003 to the present), each exhibiting different patterns of changes [ 16 ], [ 17 ]. The transition period was marked by a lack of organizational structure, particularly characterized by significant transformations in the agricultural sector. These changes were primarily driven by the shift from cooperative to private ownership, alongside the full restitution of agricultural and forest lands to their former owners. As a result, the agricultural sector became a key driver of land use changes, significantly influenced by a series of legislative measures, including Decree Law 42/1990 , Land Law 18/1991 , which was later complemented by Law 169/1997 , as well as Law 1/2000 and Law 247/2005 . The post-communist period, characterized by economic transformation and the shift to a market economy, also led to a substantial increase in demand for land for residential, commercial, and industrial development [ 16 ], [ 17 ]. The post-transition period is mainly defined by Romania's accession to the European Union (EU) in 2007, which can be further divided into two phases: the pre-EU accession period (2003–2007) and the post-EU accession period (2007-present) [ 17 ]. Romania's accession to the EU resulted in significant changes in land use at the national level. In response, the country was mandated to adopt and enforce a comprehensive set of environmental protection regulations and standards. These regulations aimed not only to improve land quality but also to prevent soil degradation and preserve vital ecosystems such as wetlands and forests, thereby influencing land management practices across the country. In addition, EU integration has facilitated Romania's access to external investment opportunities and expanded funding possibilities for rural and agricultural development projects. This has contributed to the modernization and optimization of land use, and to the development of the country's infrastructure and economy. These transformations were accompanied by the adoption of stringent environmental protection regulations designed to mitigate the impact of infrastructure development on the natural landscape. This study aims to (1) analyze spatiotemporal LULC changes over nearly three decades in relation to political and legislative transitions, and (2) assess urban development potential through a suitability analysis that integrates spatial and contextual variables. By linking land use change and urbanization patterns to broader urban development processes, the study demonstrates how spatially explicit data can inform decision-making in complex and dynamic urban environments. While grounded in the case of Constanța County, this approach holds broader applicability for rapidly developing regions worldwide, particularly those facing similar socio-economic and environmental pressures. The findings underscore the importance of data-driven planning strategies that balance urban growth with ecological sustainability and efficient land resource management. 2. Materials and methods 2.1 Study area Constanța County, located in the southeastern part of Romania, is the most urbanized county in the country, according to the latest census conducted in 2021 [ 24 ]. It ranks as the eighth-largest county in Romania, with a total area of 7,071 km². Geographically, the most important feature is related to the Romanian Black Sea coast, which provides the eastern border of the county for a length of approximately 115 km. This is also linked to the high degree of urbanization, the most important coastal tourist resorts having city status. The western border is formed by the Danube River (which forms the boundary between Constanța and the counties of Călărași, Ialomița, and Brăila), while in the south it is the national border with Bulgaria and in the north with Tulcea County, which also includes the Danube Delta (Fig. 1 A). From an administrative perspective, Constanța County comprises 3 municipalities, 9 towns, 58 communes, and 189 villages. Key urban centers include Constanța, Mangalia, Medgidia, Năvodari (ports and resorts on the Black Sea), and Cernavodă (port on the Danube) (Fig. 1 B). Constanța County is predominantly characterized by plateau terrain, with generally low elevations mostly below 200 m, occasionally reaching up to 250 m in the northern part. On its eastern side, the county borders the Black Sea coastline, where the littoral area is extensively used by the tourists. Moreover, Constanța County contains more than 20% of Romania's protected natural areas and nature reserves, amounting to a total of 12,753 ha. The county also comprises 29 Special Protection Areas (SPAs) designated for bird conservation and 30 Sites of Community Importance (SCIs), both integral components of the European Natura 2000 ecological network (European Commission, 2024). Areas covered by forest vegetation occupy relatively limited extents within Constanța County. In contrast, the county encompasses over 700,000 ha of agricultural land, approximately 80% of which is arable. 2.2 Data and methodology for LULC analysis To achieve the objectives of this study, a GIS-based analysis was conducted using geospatial datasets. The analysis began with the examination LULC, a method widely recognized as one of the most efficient and straightforward approaches for assessing the extent of urbanization [ 25 ]. The CORINE Land Cover (CLC) database, with an estimated spatial accuracy of approximately 100 meters and a minimum mapping unit of 25 hectares (Copernicus Land Monitoring Service), includes all land cover types, with no separate categories for unclassified land [ 26 ]. It has been extensively used in scientific studies to analyze LULC changes across various regions, including applications in monitoring environmental changes [ 16 ], [ 20 ], [ 27 ] urban development [ 28 ], climate change assessments [ 29 ] and landscape fragmentation analysis [ 30 ]. Given that the CLC nomenclature is structured into three levels of detail, with the most detailed level comprising 44 distinct classes, the data were reclassified to facilitate a more streamlined analysis. Specifically, the Level 1 classification, which provides a generalized categorization, was utilized and the CLC classes were aggregated into four broad categories: artificial surfaces, agricultural areas, forests and semi-natural areas, and water bodies (Table 1). To maintain a focus on terrestrial land cover changes, water courses and water bodies were merged into a single category. This approach has been widely adopted in previous studies [ 31 ], [ 32 ], [ 33 ]. Tabel 1 - Reclassification of the CLC classes used in this study No. CLC Level 1 Description 1 Artificial surfaces Built-up areas such as urban environments, industrial, commercial, and transport units, and other human-made structures. 2 Agricultural land Land used for farming, including arable land, pastures, orchards, and vineyards. 3 Forest and semi-natural areas Natural and semi-natural landscapes such as forests, woodlands, shrublands, and other vegetation types not intensively managed for agriculture or urban development. 4 Water bodies Surface water areas, including lakes, rivers, ponds, and reservoirs. 2.3 Data and methodology for urban suitability analysis The second part of this study focuses on a suitability analysis to evaluate the potential for sustainable urban development in Constanța County. Land use suitability analysis is a GIS-based spatial modelling application used to identify the most suitable land uses based on predictive factors [ 34 ]. Over time, researchers have applied land use suitability analysis in various fields, including agriculture [ 35 ], environmental impact assessment [ 36 ] and spatial planning [ 37 ]. Land suitability analysis is a process that evaluates the physical, social, and economic characteristics of an area to determine its appropriateness for a specific land use. By identifying opportunities and constraints, such analyses support informed decisions regarding where certain activities can be optimally implemented, considering the land's inherent capabilities and limitations [ 38 ], [ 39 ]. The process involves the standardization, weighting, and integration of raster data to generate a final suitability score. In this study, six factors were considered for the suitability analysis of sustainable urban development: land cover and land use data, topographic data, population density, tree cover, protected natural areas, and road proximity (Fig. 2 A - F). The selection of these factors was informed by previous literature [ 33 ], [ 40 ], [ 41 ], [ 42 ], [ 43 ], [ 44 ], [ 45 ] and tailored to the specific characteristics of the study area. Table 2 provides an overview of the data utilized in the study along with their respective sources. Table 2 Data used for suitability analysis Data Data source Link Data Source Land Use and Land Cover 2018 CORINE Land Cover - Copernicus Land Monitoring Service https://land.copernicus.eu/en/products/corine-land-cover/clc2018 Digital Elevation Model Shuttle Radar Topography Mission (SRTM) - United States Geological Survey https://earthexplorer.usgs.gov/ Population Density World Pop https://www.worldpop.org/ Tree Cover Density 2018 Copernicus Land Monitoring Service https://land.copernicus.eu/en/products/high-resolution-layer-tree-cover-density Protected natural areas Ministry of Environment, Waters and Forests of Romania https://www.mmediu.ro/categorie/date-gis/205 Main Road Accessibility Open Street Map https://www.openstreetmap.org The CLC dataset was standardized by assigning a suitability score on a scale from 1 (least suitable) to 5 (most suitable), based on its relevance to urbanization. Therefore, a high suitability score (value 5) was assigned to open space areas, such as “Green Urban Areas” and “Complex Cultivation Patterns”. A moderate suitability score (value 3) was assigned to the “Agricultural class”, while a low suitability score (value 1) was given to “Water Bodies”, “Forest and Semi-natural Areas”, “Artificial Surfaces”, and “Industrial, Commercial, and Transport Units” [ 46 ]. Appendix A provides a detailed breakdown of the suitability scores for all CLC classes. Regarding topographic factors, the slope data was derived from the 30m × 30m SRTM DEM. A 20% slope threshold is widely recognized as a key criterion for assessing land suitability for urban expansion, with areas exhibiting slopes below this value being considered more suitable for development [ 46 ], [ 47 ], [ 48 ], [ 49 ], [ 50 ], [ 51 ]. Accordingly, the standardized classification of slope data is presented in Table 3 , emphasizing the role of relatively flat terrain in supporting sustainable urban growth [ 52 ]. Table 3 – Slope suitability values Slope Range (%) Suitability Level Suitability Score 0–5 Highest suitability 5 5–10 High suitability 4 10–15 Moderate suitability 3 15–20 Low suitability 2 > 20 Lowest suitability 1 Urban development is closely linked to population growth[ 45 ] As urban area expand, population density serves as a key indicator of both urban development[ 53 ] and settlement patterns [ 54 ], reflecting the distribution and concentration of inhabitants within a given area. The population density standardization was based on three categories: low, medium, and high densities, determined by the number of inhabitants per square kilometer. The suitability scores assigned ranged from low for areas with high population density, which face limitations in available space for expansion, to high scores for low-density areas, which provide greater potential for development (Table 4). Tabel 4 - Standardization of population density categories for land suitability analysis Population Density Density Range Suitability score High Over 500 inhabitants/km² Low Medium Between 100 and 500 inhabitants/km² Intermediate Low Below 100 inhabitants/km² High To ensure sustainable urban development and minimize environmental impact, it is essential to prioritize the preservation of natural resources, such as green areas [ 55 ] [ 56 ]. In alignment with this principle, the “Tree Cover Density” layer was standardized, with areas of dense vegetation assigned lower suitability scores for urban expansion, while areas with sparse vegetation received higher scores, as these areas are more suitable for development. This approach reflects the importance of protecting areas with dense vegetation and promotes the transformation of lands with reduced vegetation cover, in accordance with Romanian legislation for the protection of the environment and green spaces in urban areas. As a sub-criterion within the ecological and environmental factors, the map of protected areas was included in the suitability analysis to regulate urban development in areas of significant ecological value. In this regard, protected natural areas, as designated by the Ministry of Environment, Waters, and Forests of Romania, were classified as prohibited zones for urban expansion. These areas, which hold both national and international significance, are part of the Natura 2000 protected areas network, comprising “Sites of Community Importance (SCI)” and “Special Protection Areas (SPA)”. The preservation of these areas is essential for maintaining biodiversity and ecosystem integrity, in accordance with legal frameworks designed to protect natural habitats and species. Road proximity plays an important role in urban development, being closely linked to economic growth [ 57 ] and contributing to the enhancement of residents' quality of life through better accessibility to essential services [ 46 ] [ 58 ] [ 59 ]. To land connectivity assessment, a threshold of 800 meters was established for proximity to major and local roads. Areas within this 800-meter range were classified as more suitable for sustainable urban development, benefiting from enhanced connectivity to infrastructure and facilitating the efficient utilization of existing resources [ 46 ], [ 56 ]. In contrast, areas located more than 800 meters from roads were considered less suitable due to limited accessibility and weaker integration within the broader urban structure. 3. Results 3.1. Spatiotemporal evolution of LULC areas Figure 3 presents the maps of aggregated LULC classes (artificial surfaces, agricultural areas, forests and semi-natural areas, and water bodies) highlighting the spatial distribution of land cover across Constanța County. Agricultural land emerges as the dominant category accounted for 80% of the total land area in the county, followed by water bodies at 8%, and artificial surfaces and forest and semi-natural areas, each representing 6%. The temporal analysis of CLC data highlights significant land cover transformations, with a particular emphasis on the expansion of artificial surfaces and shifts in agricultural, forested, and semi-natural areas (Fig. 4 ). Notably, artificial surfaces increased steadily by approximately 1,808 hectares between 1990 and 2006, rising from 43,694.99 ha in 1990 to a peak of 45,503.88 ha in 2006. The period between 1990 and 2006 experienced the most significant land cover changes, notably the expansion of built-up areas. This trend is closely associated with the fall of the communist regime in 1990 and the subsequent socio-political transformations accompanying the transition to a market economy. All of this generated a significant increase in land demand for the development of residential, commercial, and industrial spaces, thus giving rise to the suburbanization process [ 60 ], [ 61 ]. This phenomenon was characterized by the redistribution of population and economic activities toward peri-urban areas, significantly driving urban expansion [ 62 ]. The evolution of agricultural surfaces exhibits a fluctuating trend. Between 1990 and 2000, agricultural areas experienced a significant decline of approximately 2,668 ha. Researchers attributed this decrease primarily to the redistribution of land among various land use categories, in line with the broader trend of suburbanization [ 17 ]. Although the population's enthusiasm was significant following the restoration of property rights in the 1990s, this decline observed between 1990 and 2000 can largely be attributed to the inability of many small farmers to adapt to the new market demands, which forced them to abandon agricultural activities [ 63 ], [ 64 ], [ 65 ], [ 66 ], [ 67 ], [ 68 ], [ 69 ], [ 70 ]. The transition from the large collective farms of the communist period to private ownership often led to a return to traditional agricultural practices [ 63 ], [ 66 ], [ 67 ], [ 68 ], [ 70 ] and to an excessive fragmentation of land plots [ 16 ], [ 65 ], [ 71 ], [ 72 ]. Between 2000 and 2006, during Romania's pre-accession period to the European Union, the implementation of the Common Agricultural Policies was linked to an increase in cultivated areas of approximately 5,903 ha, signalling a recovery of the agricultural sector amid the emergence of agricultural associations or land sales to agricultural investors. Additionally, in the period leading up to Romania's accession to the European Union in 2007, the country benefited from pre-accession funds and programs. This support contributed to the reintroduction of agricultural land into production, and the increase in agricultural areas observed between 2000 and 2006 can be attributed to these measures. This period, characterized as the pre-accession phase to the European Union, marked by access to various funds aimed at rehabilitating the agricultural sector, was crucial for modernizing agriculture. In this context, the Special Accession Program for Agriculture and Rural Development (SAPARD) played a key role by supporting rural development and modernizing agriculture, thereby facilitating the reintegration of agricultural land into productive use. Forests and semi-natural areas experienced a significant decline after 2000, reflecting increasing anthropogenic pressure on natural ecosystems but also the lack of adequate legislation to protect them after the change in land ownership. These decreases amounted to approximately 10,547 ha between 2000 and 2006. The area of forests and semi-natural lands continued to remain at lower levels in 2012 (41,286.618 ha) and 2018 (41,288.153 ha). This reduction can be attributed to urbanization, industrialization, as well as deforestation activities and the conversion of forested areas into agricultural or built-up land [ 16 ]. 3.2 LULC class conversion patterns Between 1990 and 2000, a total of 35 LULC classes conversions were identified, involving 12 distinct LULC classes (Fig. 5 ). These changes reflect the socio-economic shifts associated with the post-communist transition period. Of the total conversions, 18 involved a complete change from one LULC category to another, while the remaining 17 represented changes within the same category. Notably, 15 out of the 18 cross-category conversions consisted of the transformation of agricultural land into artificial surfaces. These changes were predominantly concentrated in the coastal region, particularly in and around Constanța City. However, smaller fragmented conversions were observed within urban areas, indicating a lack of uniformity or large-scale. A comprehensive explanation of the class conversions for the 1990–2000 period is provided in Appendix B, detailing the transitions between LULC classes. Between 2000 and 2006, the rate of LULC conversions declined, with a total of 19 recorded changes involving 10 LULC classes, primarily from the " Forest and Semi-Natural Areas " and " Agricultural Areas " categories (Fig. 6 ). Of these, 8 were intra-category changes, while the remaining 11 represented inter-category transformations, all resulting in the expansion of artificial surfaces. Notably, 9 of the 11 inter-category conversions resulted from the transformation of agricultural land, primarily within Constanța City and the town of Năvodari, two important urban centers in the county located in the coastal zone. The other 2 conversions involved the transition of forest and semi-natural areas into artificial land, both located in Constanța City. A detailed account of these conversions during the 2000–2006 period is provided in Appendix C, outlining the transitions between LULC classes. 3.3. Urban land use suitability analysis The weight values used in the suitability analysis have been normalized and are presented in Table 5. While all these factors contribute to the analysis, land cover, accessibility, and slope characteristics are the most critical for urban development and sustainability [ 46 ], [ 49 ]. In line with this, the weight assigned to " Land Use and Land Cover " (0.30) is the highest, reflecting its crucial role in determining land suitability. " Slope " (0.20) and " Main Road Accessibility " (0.15) also significantly influence development feasibility. " Tree Cover Density " (0.15) is relevant but less influential compared to land cover. Meanwhile, " Protected Areas " (0.10) and " Population Density " (0.10) exert the least impact, functioning more as constraints than primary suitability determinants. Tabel 5 - Weighted criteria. Criteria LULC Slope Tree Cover Density Protected Natural Area Population Density Main Road Accessibility Weight 0.30 0.20 0.15 0.10 0.10 0.15 The generated suitability map (Fig. 7 ) shows the suitability degrees for urban development, ranging from low to high. Areas of low suitability (depicted in red) are primarily constrained by environmental and land use factors that limit urban expansion. These include protected natural areas, densely vegetated regions, and highly urbanized zones with significant population density. Notably, areas of low suitability are predominantly found along the Black Sea coast, where several of the county’s most prominent cities and tourism-oriented localities are situated. These areas have experienced extensive urbanization in recent years and are characterized by high population density. Areas of high and moderate suitability predominantly comprise agricultural land, regions with sparse or minimal vegetation, and low-density populated areas. The classification of suitability values into five categories (Fig. 8 ) reveals that lands with very low and low suitability represent nearly one-third of Constanța County’s total area, covering 69,895.111 ha (10%) and 133,931.898 ha (19%), respectively. Moderate suitability areas extend across approximately 176,858.060 ha (25%). High suitability land constitutes the largest share, with around 225,502.448 ha (32%), followed by very high suitability areas, which cover 101,212.057 ha (14%). The quantitative breakdown of each suitability class is detailed in Table 6. Tabel 6 - Distribution of land suitability classes for urban development Suitability Class Area (hectares) Area (%) Very Low Suitability 69,895.111 10% Low Suitability 133,931.898 19% Moderate Suitability 176,858.06 25% High Suitability 225,502.448 32% Very High Suitability 101,212.057 14% In summary, the suitability analysis highlights a predominance of land with suitable conditions for urban development, with 46% of the county's territory falling into the high and very high suitability classes, predominantly located in the inland areas. In contrast, 29% of the land is classified as having low or very low suitability. Notably, these less suitable areas are primarily concentrated along the coastal zone, where the spatial model indicates increasingly limited potential for further urban expansion. 4. Discussions Findings from this research show that the land use dynamics identified through the CLC analysis in Constanța County are consistent with broader frameworks of land transitions in post-socialist countries [ 14 ], [ 22 ], [ 73 ], [ 74 ]. The most substantial changes were observed between 1990 and 2006, aligning with what the literature defines as the transition and post-transition phases, periods marked by the collapse of the centralized economy and Romania’s gradual integration into the European Union. These changes support existing models that link land use patterns to political and institutional transformations. In the early 1990s, agricultural land use was strongly influenced by the Agricultural Reform, which dismantled collective farms and promoted land restitution, leading to fragmented ownership and fluctuating land use. While the first half of the decade (1990–1995) showed renewed interest in agricultural practices, the second half (1995–2000) was characterized by instability due to structural weaknesses and the lack of supportive infrastructure. The expansion of agricultural land during 2000–2006 as identified through CLC data, coincides with Romania’s EU accession preparations, confirming studies that highlight how accession-related policies stimulated rural development and land consolidation [ 16 ], [ 19 ], [ 75 ]. The objective of this paper has been to understand how the dynamics of urbanization in Constanța County intersect with land use transformations, development pressures, and planning constraints in a post-socialist context. The study results revealed a continuous expansion of artificial surfaces, accompanied by a reduction in green areas and agricultural land, highlighting the increasing pressures of urbanization and reflecting patterns consistent with post-socialist urban growth models documented across Eastern Europe [ 14 ], [ 73 ], [ 76 ], [ 77 ]. The continuous trend of urbanization has influenced the development of Constanța County, which, according to the 2021 Census, is now recognized as the most urbanized county in Romania. This rapid urbanization, however, has raised questions about land use management and the long-term sustainability of urban expansion. Although land use change and urbanization have been extensively studied across various contexts in Romania [ 17 ], [ 18 ], [ 60 ], [ 61 ], [ 78 ], [ 79 ], this study contributes to the existing body of research by emphasizing the value of suitability analysis in assessing the long-term sustainability of urban expansion. It specifically examines how urban growth aligns with sustainable land use principles, while also considering the lasting influence of political decisions on urbanization patterns during the post-socialist period. When considered alongside the findings of the suitability analysis, which identified a substantial share of land with high development potential, it becomes clear that significant spatial opportunities for future urban expansion still exist. These findings underscore an important point: extensive urbanization does not necessarily imply a lack of development potential. In line with this, the suitability analysis conducted for Constanța County revealed that a significant portion of the agricultural land, despite its current non-urban designation, was classified as highly or very highly suitable for urban development. Similar patterns have been observed in other regions, as reported by Al-Ghorayeb [ 46 ], where over 64% of agricultural land was classified as highly or very highly suitable for sustainable urban development, emphasizing the capacity of agricultural areas to support future urban expansion. From a sustainability perspective, this raises critical questions about how such land is managed, and whether future urban expansion can be strategically planned to minimize ecological disruption and preserve essential ecosystem services. This concern becomes particularly relevant when examining the land-use suitability map, which identified significant areas along the Black Sea coast, particularly near Constanța city (the county capital), and some of the most sought-after tourist cities, such as Năvodari, Eforie, and Mangalia, as unsuitable for further urban expansion. These zones coincide with densely built-up regions characterized by artificial surfaces, high population density, and tourism-driven land use. The low suitability scores in these coastal zones can be attributed to limited land availability, environmental constraints, and increasing urban sprawl pressure from the real estate developers that have increasingly expressed a preference for constructing and developing new urban zones along the coastal lines. Similar patterns were observed in other regions, such as Lebanon [ 46 ]where urban expansion tends to be a contiguous extension of prior agglomerations, these areas on the coast attract developers due to their proximity to existing urban agglomerations. This contiguity to established cities enhances their attractiveness for new residents and companies, making them ideal candidates for development, despite the limitations posed by environmental and spatial factors. Al-Ghorayeb [ 46 ], noted that such trends of development along coastal areas are often driven by established infrastructure, population growth, and economic activity, further emphasizing the need for a balanced approach to managing these spaces. While the findings of this study provide valuable insights into land-use dynamics in Constanța County, certain limitations must be acknowledged. These limitations include the subjectivity involved in perceiving and evaluating the severity of land-use restrictions during the suitability analysis. According to Luan [ 49 ], this directly influences the extent to which land is considered suitable for urban development. Additionally, the accuracy of the results depends on the reliability of the input datasets and the appropriateness of the assigned weights in the multi-criteria analysis. Temporal resolution and thematic detail of the CLC dataset may also limit the detection of finer-scale land use changes. The findings of this study have direct implications for urban planning policies and sustainable land-use management strategies in Constanța County. By identifying spatial patterns of land-use suitability, the analysis provides valuable evidence to inform policy decisions that aim to balance development needs with environmental protection. The results demonstrate that GIS-based suitability analysis can serve as a strategic planning tool, helping policymakers and urban planners direct future growth toward areas with high development potential while avoiding ecologically sensitive or low-suitability zones. To promote sustainable development in the region, the findings of this study suggest that urban expansion should be prioritized in areas identified as highly suitable, particularly those with existing infrastructure, lower population density, and minimal environmental constraints. Moreover, according to Al-Ghorayeb [ 46 ], to ensure sustainability, new urban agglomerations should be located within 700 meters of existing urban areas, promoting contiguous development and limiting unnecessary land fragmentation. Conversely, areas identified as having low suitability, such as those with high population density, high urbanization levels (as indicated by CLC LULC classes), and significant environmental constraints, should be designated for conservation or subjected to further study before any development is considered. Further research is recommended to refine and expand the current suitability analysis by incorporating additional land-use types and higher-resolution datasets, particularly at the city scale. In the case of Constanța municipality, future studies could benefit from using very high-resolution satellite imagery or detailed cadastral data to capture finer spatial variations and better reflect the complexity of urban environments. Moreover, exploring different types of suitability models, such as those tailored for green infrastructure or agricultural preservation, could provide more targeted support for specific planning objectives. Collaborations with local municipalities are also encouraged to ensure that GIS-based tools are effectively integrated into planning practices, enabling data-driven decisions that respond to both development pressures and sustainability goals. Furthermore, it is recommended that the involvement of city residents in planning and governance processes be prioritized to ensure more inclusive and sustainable urban development. This is particularly important in regions experiencing rapid urban growth, often driven by external investments and tourism-related expansion. As highlighted in existing literature [ 80 ], [ 81 ] inclusive and participatory planning approaches play a crucial role in addressing development challenges while fostering community engagement and ownership of urban space. 5. Conclusions This study aimed to analyze the land use dynamics in Constanța County using CLC data and suitability analysis, with a focus on understanding the spatial patterns of urbanization and their potential for sustainable development. The key objectives were to identify the most significant land use changes and evaluate the suitability of land for future urban development. The analysis revealed that the most significant land use changes occurred between 1990 and 2006, with a notable increase in artificial surfaces and a decrease in forested areas. Agricultural land initially declined during the early transition period but experienced a partial recovery in the years preceding Romania’s EU accession. These trends highlight the complex relationship between urban expansion and land use dynamics, shaped by distinct socio-economic phases. The suitability analysis further highlighted that although there is adequate land available for urban expansion, the areas with low and very low suitability are concentrated near existing built-up zones, particularly along the Black Sea coast. This suggests that urban growth in these areas could lead to significant environmental pressures, reducing the sustainability of development in the region. The findings contribute to the broader understanding of LULC transitions in post-socialist countries, particularly in the context of rapid urbanization and the challenges of balancing development with environmental preservation. This research demonstrates the value of integrated CLC data and GIS-based suitability analysis as tools for supporting sustainable urban planning decisions. It also underscores the importance of considering both ecological and developmental factors when planning for future growth. In practice, the findings of this study can support urban planning strategies by guiding decision-makers in identifying areas suitable for expansion without compromising environmental integrity. Specifically, areas identified as highly suitable for urban development should be prioritized, while regions with high environmental sensitivity should be preserved or subjected to further evaluation, in line with the need for comprehensive land management policies that foster sustainable growth. Overall, this research contributes to a deeper understanding of land use dynamics in Constanța County and provides a solid foundation for making informed decisions about sustainable urban development in the region. Declarations Author Contribution C.E.M. and M.D. contributed to the conceptualization, methodology, validation, formal analysis, investigation, and resources. C.E.M. was responsible for data curation, original draft preparation, and figure/table preparation. Both authors contributed to the review and editing of the manuscript. M.D. supervised the research. All authors have read and agreed to the published version of the manuscript. Acknowledgement The author gratefully acknowledges the support provided by the Department of Geography at The Pennsylvania State University during the Fulbright Visiting Scholar Program, which facilitated access to valuable academic resources and expert guidance throughout the research process. References Gao, L., & Bryan, B. A. (2017). Finding pathways to national-scale land-sector sustainability. Nature, 544(7649), 217–222. https://doi.org/10.1038/nature21694 Winkler, K., Fuchs, R., Rounsevell, M., & Herold, M. (2021). Global land use changes are four times greater than previously estimated. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6892590","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486444782,"identity":"339921d8-8dd8-4ef4-8d11-ef0dd65f9bd6","order_by":0,"name":"Cristina Elena Mihalache","email":"data:image/png;base64,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","orcid":"","institution":"Romanian Academy","correspondingAuthor":true,"prefix":"","firstName":"Cristina","middleName":"Elena","lastName":"Mihalache","suffix":""},{"id":486444783,"identity":"85894a04-ee0e-4a69-a47b-cddebf4b60d2","order_by":1,"name":"Monica Dumitrașcu","email":"","orcid":"","institution":"Romanian Academy","correspondingAuthor":false,"prefix":"","firstName":"Monica","middleName":"","lastName":"Dumitrașcu","suffix":""}],"badges":[],"createdAt":"2025-06-14 07:53:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6892590/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6892590/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10666-026-10117-6","type":"published","date":"2026-04-11T15:58:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87367217,"identity":"3d90623e-ca56-4501-9cd3-8116522f49e8","added_by":"auto","created_at":"2025-07-23 06:44:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":745102,"visible":true,"origin":"","legend":"\u003cp\u003eA. Location map of the study area, B. Principal cities in Constanța County\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/f246d177bea2d0e59ee0aeb7.png"},{"id":87366116,"identity":"4ad78aac-c54d-4c3a-a4a6-a6202901ce58","added_by":"auto","created_at":"2025-07-23 06:36:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":952704,"visible":true,"origin":"","legend":"\u003cp\u003eFactors used in suitability analysis: A) Land Use Land Cover, B) Slope, C) Population Density, D) Tree Cover Density, E) Protected Natural Area, F) Main Roads\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/71f708604f73bcb287f3b98b.png"},{"id":87366119,"identity":"f1d303a0-e2f6-496b-af88-c9ddbe7a7ea9","added_by":"auto","created_at":"2025-07-23 06:36:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":604974,"visible":true,"origin":"","legend":"\u003cp\u003eRegrouped CLC classes for Constanța County\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/b746d6b7b9863a9e6b1015e1.png"},{"id":87366112,"identity":"55ca2644-bfa7-4efa-99b6-ea572fef7e85","added_by":"auto","created_at":"2025-07-23 06:36:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48231,"visible":true,"origin":"","legend":"\u003cp\u003eArea evolution of CLC classes in Constanța County (1990–2018)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/4d06da44fb812d354d1cc50f.png"},{"id":87367218,"identity":"9d5d587e-3b40-4de7-9de8-dc06610c9819","added_by":"auto","created_at":"2025-07-23 06:44:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":419399,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of LULC classes involved in conversions between 1990 and 2000 in Constanța County\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/8f8c88c64082babd0b5b27a9.png"},{"id":87366123,"identity":"59637ed6-5f3f-4b77-8ca0-e9aae94d441b","added_by":"auto","created_at":"2025-07-23 06:36:43","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":456575,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of LULC classes involved in conversions between 2000 and 2006 in Constanța County\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/00601ff45fb185da3bc4f231.png"},{"id":87367219,"identity":"b69780e1-82f3-4920-8994-543636453862","added_by":"auto","created_at":"2025-07-23 06:44:43","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1184851,"visible":true,"origin":"","legend":"\u003cp\u003eUrban land suitability map for Constanța County\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/51a22de4814b8474d063a2b7.png"},{"id":87366122,"identity":"2d402636-6943-4d43-add1-81c907b4779d","added_by":"auto","created_at":"2025-07-23 06:36:43","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1000453,"visible":true,"origin":"","legend":"\u003cp\u003eLand Suitability Classification Map for Constanța County\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/4d19024caa56cc6c47d31264.png"},{"id":106808913,"identity":"3a7caab4-0df3-4a5c-8842-9e7b2472e67e","added_by":"auto","created_at":"2026-04-13 16:05:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5630876,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/963ebe36-43a9-447d-a72a-27eaace96806.pdf"},{"id":87367216,"identity":"6751b7f8-78f4-46b3-9320-4c9e613bc63f","added_by":"auto","created_at":"2025-07-23 06:44:42","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":24343,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptSupplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6892590/v1/f0dce6dc83a96f259c703dfb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Land use dynamics and urban development suitability: A geospatial analysis of Romania’s most urbanized county","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLand use and land cover (LULC) dynamics have remained a focal point of scientific research for their role in forming the foundation for understanding surface cover and human utilization of lands. Even with their extensive study, LULC still remains fundamental in devising sustainable planning frameworks, as they underpin policies concerned with environmental monitoring and resource management [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe identification of LULC patterns is of vital importance in the activities of conservation and resource mitigation, as they can enlighten how landscapes evolve under human influence. Global studies conducted between 1960\u0026ndash;2019 have shown that about 32% of the global land surface was affected by land use changes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Recent studies conducted in the last 30 years have documented an acceleration process of LULC change with an average annual rate of 0.36% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eThe pattern of evolution in LULC is often portrayed in the landscape of regions and, therefore, carries a representational relationship with significant environmental features. On one hand, there is the demand of society for resources and space; on the other hand, there is an Earth that can support these demands only up to a point. Besides this, extensive and intensive use of land beyond the limits of sustainability, together with extreme degradation of landscapes and ecosystems, leads to considerable and often irreversible environmental changes. To achieve sustainable land resource use, the first step is to understand the historical condition, status, and patterns of change in land use [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Furthermore, it is relevant to explore the key drivers of the LULC changes. Over time, scientists have demonstrated that the increase in population, urbanization, and the demand for residential space puts an immense amount of pressure on agricultural land and natural resources [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] with significant implications for climate change and biodiversity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAdditionally, political factors and legislative measures are key drivers influencing land use and cover changes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In the context of Romania, studies have shown that these socio-economic and political drivers have played a crucial role in the evolution of LULC over time [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn pre-modern times, traditional agriculture was the main source of income for the local population. The land was mainly used for growing crops and raising livestock, reflecting a predominantly rural economy. During this period, communities were made up of small villages and the inhabitants depended on the natural resources of the region for their livelihood [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConstanța County is an important industrial hub, owing to its strategic location on the border between Romania and Bulgaria, with direct access to the Black Sea. Also, here is the most important coastal tourist area of ​​Romania as well as the largest port of Romania on the Black Sea. Consequently, the region has seen the development of numerous factories and industrial facilities, particularly in sectors such as metal processing, electrical and electronic equipment manufacturing, and textiles, among others. This industrial development has had a significant impact on the county\u0026rsquo;s economy, generating an increase in jobs and an improvement in living standards. However, it has also contributed to the reduction of natural and agricultural land and the expansion of built-up areas, with effects on the environment and quality of life.\u003c/p\u003e\u003cp\u003eThe period after the fall of communism has been described by specialists as being divided into two phases: the transition period (1990\u0026ndash;2003) and the post-transition period (2003 to the present), each exhibiting different patterns of changes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe transition period was marked by a lack of organizational structure, particularly characterized by significant transformations in the agricultural sector. These changes were primarily driven by the shift from cooperative to private ownership, alongside the full restitution of agricultural and forest lands to their former owners. As a result, the agricultural sector became a key driver of land use changes, significantly influenced by a series of legislative measures, including \u003cem\u003eDecree Law 42/1990\u003c/em\u003e, \u003cem\u003eLand Law 18/1991\u003c/em\u003e, which was later complemented by \u003cem\u003eLaw 169/1997\u003c/em\u003e, as well as \u003cem\u003eLaw 1/2000\u003c/em\u003e and \u003cem\u003eLaw 247/2005\u003c/em\u003e. The post-communist period, characterized by economic transformation and the shift to a market economy, also led to a substantial increase in demand for land for residential, commercial, and industrial development [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe post-transition period is mainly defined by Romania's accession to the European Union (EU) in 2007, which can be further divided into two phases: the pre-EU accession period (2003\u0026ndash;2007) and the post-EU accession period (2007-present) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRomania's accession to the EU resulted in significant changes in land use at the national level. In response, the country was mandated to adopt and enforce a comprehensive set of environmental protection regulations and standards. These regulations aimed not only to improve land quality but also to prevent soil degradation and preserve vital ecosystems such as wetlands and forests, thereby influencing land management practices across the country. In addition, EU integration has facilitated Romania's access to external investment opportunities and expanded funding possibilities for rural and agricultural development projects. This has contributed to the modernization and optimization of land use, and to the development of the country's infrastructure and economy. These transformations were accompanied by the adoption of stringent environmental protection regulations designed to mitigate the impact of infrastructure development on the natural landscape.\u003c/p\u003e\u003cp\u003eThis study aims to (1) analyze spatiotemporal LULC changes over nearly three decades in relation to political and legislative transitions, and (2) assess urban development potential through a suitability analysis that integrates spatial and contextual variables.\u003c/p\u003e\u003cp\u003eBy linking land use change and urbanization patterns to broader urban development processes, the study demonstrates how spatially explicit data can inform decision-making in complex and dynamic urban environments. While grounded in the case of Constanța County, this approach holds broader applicability for rapidly developing regions worldwide, particularly those facing similar socio-economic and environmental pressures. The findings underscore the importance of data-driven planning strategies that balance urban growth with ecological sustainability and efficient land resource management.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study area\u003c/h2\u003e\u003cp\u003eConstanța County, located in the southeastern part of Romania, is the most urbanized county in the country, according to the latest census conducted in 2021 [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. It ranks as the eighth-largest county in Romania, with a total area of 7,071 km\u0026sup2;. Geographically, the most important feature is related to the Romanian Black Sea coast, which provides the eastern border of the county for a length of approximately 115 km. This is also linked to the high degree of urbanization, the most important coastal tourist resorts having city status. The western border is formed by the Danube River (which forms the boundary between Constanța and the counties of Călărași, Ialomița, and Brăila), while in the south it is the national border with Bulgaria and in the north with Tulcea County, which also includes the Danube Delta (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003eFrom an administrative perspective, Constanța County comprises 3 municipalities, 9 towns, 58 communes, and 189 villages. Key urban centers include Constanța, Mangalia, Medgidia, Năvodari (ports and resorts on the Black Sea), and Cernavodă (port on the Danube) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eConstanța County is predominantly characterized by plateau terrain, with generally low elevations mostly below 200 m, occasionally reaching up to 250 m in the northern part. On its eastern side, the county borders the Black Sea coastline, where the littoral area is extensively used by the tourists. Moreover, Constanța County contains more than 20% of Romania's protected natural areas and nature reserves, amounting to a total of 12,753 ha. The county also comprises 29 Special Protection Areas (SPAs) designated for bird conservation and 30 Sites of Community Importance (SCIs), both integral components of the European Natura 2000 ecological network (European Commission, 2024). Areas covered by forest vegetation occupy relatively limited extents within Constanța County. In contrast, the county encompasses over 700,000 ha of agricultural land, approximately 80% of which is arable.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Data and methodology for LULC analysis\u003c/h2\u003e\u003cp\u003eTo achieve the objectives of this study, a GIS-based analysis was conducted using geospatial datasets. The analysis began with the examination LULC, a method widely recognized as one of the most efficient and straightforward approaches for assessing the extent of urbanization [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe CORINE Land Cover (CLC) database, with an estimated spatial accuracy of approximately 100 meters and a minimum mapping unit of 25 hectares (Copernicus Land Monitoring Service), includes all land cover types, with no separate categories for unclassified land [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. It has been extensively used in scientific studies to analyze LULC changes across various regions, including applications in monitoring environmental changes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] urban development [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], climate change assessments [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and landscape fragmentation analysis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven that the CLC nomenclature is structured into three levels of detail, with the most detailed level comprising 44 distinct classes, the data were reclassified to facilitate a more streamlined analysis. Specifically, the Level 1 classification, which provides a generalized categorization, was utilized and the CLC classes were aggregated into four broad categories: artificial surfaces, agricultural areas, forests and semi-natural areas, and water bodies (Table\u0026nbsp;1). To maintain a focus on terrestrial land cover changes, water courses and water bodies were merged into a single category. This approach has been widely adopted in previous studies [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTabel 1 - Reclassification of the CLC classes used in this study\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCLC Level 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eArtificial surfaces\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBuilt-up areas such as urban environments, industrial, commercial, and transport units, and other human-made structures.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgricultural land\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLand used for farming, including arable land, pastures, orchards, and vineyards.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForest and semi-natural areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNatural and semi-natural landscapes such as forests, woodlands, shrublands, and other vegetation types not intensively managed for agriculture or urban development.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWater bodies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurface water areas, including lakes, rivers, ponds, and reservoirs.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Data and methodology for urban suitability analysis\u003c/h2\u003e\u003cp\u003eThe second part of this study focuses on a suitability analysis to evaluate the potential for sustainable urban development in Constanța County. Land use suitability analysis is a GIS-based spatial modelling application used to identify the most suitable land uses based on predictive factors [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Over time, researchers have applied land use suitability analysis in various fields, including agriculture [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], environmental impact assessment [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and spatial planning [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eLand suitability analysis is a process that evaluates the physical, social, and economic characteristics of an area to determine its appropriateness for a specific land use. By identifying opportunities and constraints, such analyses support informed decisions regarding where certain activities can be optimally implemented, considering the land's inherent capabilities and limitations [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The process involves the standardization, weighting, and integration of raster data to generate a final suitability score.\u003c/p\u003e\u003cp\u003eIn this study, six factors were considered for the suitability analysis of sustainable urban development: land cover and land use data, topographic data, population density, tree cover, protected natural areas, and road proximity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA - F).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe selection of these factors was informed by previous literature [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] and tailored to the specific characteristics of the study area. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides an overview of the data utilized in the study along with their respective sources.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eData used for suitability analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eData\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eData source\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLink Data Source\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLand Use and Land Cover 2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCORINE Land Cover - Copernicus Land Monitoring Service\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://land.copernicus.eu/en/products/corine-land-cover/clc2018\u003c/span\u003e\u003cspan address=\"https://land.copernicus.eu/en/products/corine-land-cover/clc2018\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDigital Elevation Model\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eShuttle Radar Topography Mission (SRTM) - United States Geological Survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://earthexplorer.usgs.gov/\u003c/span\u003e\u003cspan address=\"https://earthexplorer.usgs.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePopulation Density\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWorld Pop\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.worldpop.org/\u003c/span\u003e\u003cspan address=\"https://www.worldpop.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTree Cover Density 2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCopernicus Land Monitoring Service\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://land.copernicus.eu/en/products/high-resolution-layer-tree-cover-density\u003c/span\u003e\u003cspan address=\"https://land.copernicus.eu/en/products/high-resolution-layer-tree-cover-density\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtected natural areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMinistry of Environment, Waters and Forests of Romania\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mmediu.ro/categorie/date-gis/205\u003c/span\u003e\u003cspan address=\"https://www.mmediu.ro/categorie/date-gis/205\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMain Road Accessibility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOpen Street Map\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.openstreetmap.org\u003c/span\u003e\u003cspan address=\"https://www.openstreetmap.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe CLC dataset was standardized by assigning a suitability score on a scale from 1 (least suitable) to 5 (most suitable), based on its relevance to urbanization. Therefore, a high suitability score (value 5) was assigned to open space areas, such as \u0026ldquo;Green Urban Areas\u0026rdquo; and \u0026ldquo;Complex Cultivation Patterns\u0026rdquo;. A moderate suitability score (value 3) was assigned to the \u0026ldquo;Agricultural class\u0026rdquo;, while a low suitability score (value 1) was given to \u0026ldquo;Water Bodies\u0026rdquo;, \u0026ldquo;Forest and Semi-natural Areas\u0026rdquo;, \u0026ldquo;Artificial Surfaces\u0026rdquo;, and \u0026ldquo;Industrial, Commercial, and Transport Units\u0026rdquo; [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Appendix A provides a detailed breakdown of the suitability scores for all CLC classes.\u003c/p\u003e\u003cp\u003eRegarding topographic factors, the slope data was derived from the 30m \u0026times; 30m SRTM DEM. A 20% slope threshold is widely recognized as a key criterion for assessing land suitability for urban expansion, with areas exhibiting slopes below this value being considered more suitable for development [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Accordingly, the standardized classification of slope data is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e, emphasizing the role of relatively flat terrain in supporting sustainable urban growth [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u0026ndash; Slope suitability values\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSlope Range (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuitability Level\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSuitability Score\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u0026ndash;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHighest suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u0026ndash;15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLowest suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eUrban development is closely linked to population growth[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] As urban area expand, population density serves as a key indicator of both urban development[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and settlement patterns [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], reflecting the distribution and concentration of inhabitants within a given area. The population density standardization was based on three categories: low, medium, and high densities, determined by the number of inhabitants per square kilometer. The suitability scores assigned ranged from low for areas with high population density, which face limitations in available space for expansion, to high scores for low-density areas, which provide greater potential for development (Table\u0026nbsp;4).\u003c/p\u003e\u003cp\u003eTabel 4 - Standardization of population density categories for land suitability analysis\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePopulation Density\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDensity Range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSuitability score\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOver 500 inhabitants/km\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBetween 100 and 500 inhabitants/km\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIntermediate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBelow 100 inhabitants/km\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo ensure sustainable urban development and minimize environmental impact, it is essential to prioritize the preservation of natural resources, such as green areas [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In alignment with this principle, the \u0026ldquo;Tree Cover Density\u0026rdquo; layer was standardized, with areas of dense vegetation assigned lower suitability scores for urban expansion, while areas with sparse vegetation received higher scores, as these areas are more suitable for development. This approach reflects the importance of protecting areas with dense vegetation and promotes the transformation of lands with reduced vegetation cover, in accordance with Romanian legislation for the protection of the environment and green spaces in urban areas.\u003c/p\u003e\u003cp\u003eAs a sub-criterion within the ecological and environmental factors, the map of protected areas was included in the suitability analysis to regulate urban development in areas of significant ecological value. In this regard, protected natural areas, as designated by the Ministry of Environment, Waters, and Forests of Romania, were classified as prohibited zones for urban expansion. These areas, which hold both national and international significance, are part of the Natura 2000 protected areas network, comprising \u0026ldquo;Sites of Community Importance (SCI)\u0026rdquo; and \u0026ldquo;Special Protection Areas (SPA)\u0026rdquo;. The preservation of these areas is essential for maintaining biodiversity and ecosystem integrity, in accordance with legal frameworks designed to protect natural habitats and species.\u003c/p\u003e\u003cp\u003eRoad proximity plays an important role in urban development, being closely linked to economic growth [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] and contributing to the enhancement of residents' quality of life through better accessibility to essential services [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. To land connectivity assessment, a threshold of 800 meters was established for proximity to major and local roads. Areas within this 800-meter range were classified as more suitable for sustainable urban development, benefiting from enhanced connectivity to infrastructure and facilitating the efficient utilization of existing resources [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In contrast, areas located more than 800 meters from roads were considered less suitable due to limited accessibility and weaker integration within the broader urban structure.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Spatiotemporal evolution of LULC areas\u003c/h2\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the maps of aggregated LULC classes (artificial surfaces, agricultural areas, forests and semi-natural areas, and water bodies) highlighting the spatial distribution of land cover across Constanța County. Agricultural land emerges as the dominant category accounted for 80% of the total land area in the county, followed by water bodies at 8%, and artificial surfaces and forest and semi-natural areas, each representing 6%.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe temporal analysis of CLC data highlights significant land cover transformations, with a particular emphasis on the expansion of artificial surfaces and shifts in agricultural, forested, and semi-natural areas (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Notably, artificial surfaces increased steadily by approximately 1,808 hectares between 1990 and 2006, rising from 43,694.99 ha in 1990 to a peak of 45,503.88 ha in 2006.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe period between 1990 and 2006 experienced the most significant land cover changes, notably the expansion of built-up areas. This trend is closely associated with the fall of the communist regime in 1990 and the subsequent socio-political transformations accompanying the transition to a market economy. All of this generated a significant increase in land demand for the development of residential, commercial, and industrial spaces, thus giving rise to the suburbanization process [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. This phenomenon was characterized by the redistribution of population and economic activities toward peri-urban areas, significantly driving urban expansion [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe evolution of agricultural surfaces exhibits a fluctuating trend. Between 1990 and 2000, agricultural areas experienced a significant decline of approximately 2,668 ha. Researchers attributed this decrease primarily to the redistribution of land among various land use categories, in line with the broader trend of suburbanization [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough the population's enthusiasm was significant following the restoration of property rights in the 1990s, this decline observed between 1990 and 2000 can largely be attributed to the inability of many small farmers to adapt to the new market demands, which forced them to abandon agricultural activities [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e], [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe transition from the large collective farms of the communist period to private ownership often led to a return to traditional agricultural practices [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] and to an excessive fragmentation of land plots [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBetween 2000 and 2006, during Romania's pre-accession period to the European Union, the implementation of the Common Agricultural Policies was linked to an increase in cultivated areas of approximately 5,903 ha, signalling a recovery of the agricultural sector amid the emergence of agricultural associations or land sales to agricultural investors. Additionally, in the period leading up to Romania's accession to the European Union in 2007, the country benefited from pre-accession funds and programs. This support contributed to the reintroduction of agricultural land into production, and the increase in agricultural areas observed between 2000 and 2006 can be attributed to these measures. This period, characterized as the pre-accession phase to the European Union, marked by access to various funds aimed at rehabilitating the agricultural sector, was crucial for modernizing agriculture. In this context, the Special Accession Program for Agriculture and Rural Development (SAPARD) played a key role by supporting rural development and modernizing agriculture, thereby facilitating the reintegration of agricultural land into productive use.\u003c/p\u003e\u003cp\u003eForests and semi-natural areas experienced a significant decline after 2000, reflecting increasing anthropogenic pressure on natural ecosystems but also the lack of adequate legislation to protect them after the change in land ownership. These decreases amounted to approximately 10,547 ha between 2000 and 2006. The area of forests and semi-natural lands continued to remain at lower levels in 2012 (41,286.618 ha) and 2018 (41,288.153 ha). This reduction can be attributed to urbanization, industrialization, as well as deforestation activities and the conversion of forested areas into agricultural or built-up land [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.2 LULC class conversion patterns\u003c/h2\u003e\u003cp\u003eBetween 1990 and 2000, a total of 35 LULC classes conversions were identified, involving 12 distinct LULC classes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These changes reflect the socio-economic shifts associated with the post-communist transition period. Of the total conversions, 18 involved a complete change from one LULC category to another, while the remaining 17 represented changes within the same category.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNotably, 15 out of the 18 cross-category conversions consisted of the transformation of agricultural land into artificial surfaces. These changes were predominantly concentrated in the coastal region, particularly in and around Constanța City. However, smaller fragmented conversions were observed within urban areas, indicating a lack of uniformity or large-scale. A comprehensive explanation of the class conversions for the 1990\u0026ndash;2000 period is provided in Appendix B, detailing the transitions between LULC classes.\u003c/p\u003e\u003cp\u003eBetween 2000 and 2006, the rate of LULC conversions declined, with a total of 19 recorded changes involving 10 LULC classes, primarily from the \"\u003cem\u003eForest and Semi-Natural Areas\u003c/em\u003e\" and \"\u003cem\u003eAgricultural Areas\u003c/em\u003e\" categories (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Of these, 8 were intra-category changes, while the remaining 11 represented inter-category transformations, all resulting in the expansion of artificial surfaces. Notably, 9 of the 11 inter-category conversions resulted from the transformation of agricultural land, primarily within Constanța City and the town of Năvodari, two important urban centers in the county located in the coastal zone. The other 2 conversions involved the transition of forest and semi-natural areas into artificial land, both located in Constanța City. A detailed account of these conversions during the 2000\u0026ndash;2006 period is provided in Appendix C, outlining the transitions between LULC classes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Urban land use suitability analysis\u003c/h2\u003e\u003cp\u003eThe weight values used in the suitability analysis have been normalized and are presented in Table\u0026nbsp;5. While all these factors contribute to the analysis, land cover, accessibility, and slope characteristics are the most critical for urban development and sustainability [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In line with this, the weight assigned to \"\u003cem\u003eLand Use and Land Cover\u003c/em\u003e\" (0.30) is the highest, reflecting its crucial role in determining land suitability. \"\u003cem\u003eSlope\u003c/em\u003e\" (0.20) and \"\u003cem\u003eMain Road Accessibility\u003c/em\u003e\" (0.15) also significantly influence development feasibility. \"\u003cem\u003eTree Cover Density\u003c/em\u003e\" (0.15) is relevant but less influential compared to land cover. Meanwhile, \"\u003cem\u003eProtected Areas\u003c/em\u003e\" (0.10) and \"\u003cem\u003ePopulation Density\u003c/em\u003e\" (0.10) exert the least impact, functioning more as constraints than primary suitability determinants.\u003c/p\u003e\u003cp\u003eTabel 5 - Weighted criteria.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCriteria\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLULC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSlope\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTree Cover Density\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eProtected Natural Area\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePopulation Density\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMain Road Accessibility\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe generated suitability map (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) shows the suitability degrees for urban development, ranging from low to high. Areas of low suitability (depicted in red) are primarily constrained by environmental and land use factors that limit urban expansion. These include protected natural areas, densely vegetated regions, and highly urbanized zones with significant population density. Notably, areas of low suitability are predominantly found along the Black Sea coast, where several of the county\u0026rsquo;s most prominent cities and tourism-oriented localities are situated. These areas have experienced extensive urbanization in recent years and are characterized by high population density. Areas of high and moderate suitability predominantly comprise agricultural land, regions with sparse or minimal vegetation, and low-density populated areas.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe classification of suitability values into five categories (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) reveals that lands with very low and low suitability represent nearly one-third of Constanța County\u0026rsquo;s total area, covering 69,895.111 ha (10%) and 133,931.898 ha (19%), respectively. Moderate suitability areas extend across approximately 176,858.060 ha (25%). High suitability land constitutes the largest share, with around 225,502.448 ha (32%), followed by very high suitability areas, which cover 101,212.057 ha (14%).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe quantitative breakdown of each suitability class is detailed in Table\u0026nbsp;6.\u003c/p\u003e\u003cp\u003eTabel 6 - Distribution of land suitability classes for urban development\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSuitability Class\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eArea (hectares)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArea (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVery Low Suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e69,895.111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow Suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e133,931.898\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate Suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e176,858.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh Suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e225,502.448\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVery High Suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e101,212.057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn summary, the suitability analysis highlights a predominance of land with suitable conditions for urban development, with 46% of the county's territory falling into the high and very high suitability classes, predominantly located in the inland areas. In contrast, 29% of the land is classified as having low or very low suitability. Notably, these less suitable areas are primarily concentrated along the coastal zone, where the spatial model indicates increasingly limited potential for further urban expansion.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussions","content":"\u003cp\u003eFindings from this research show that the land use dynamics identified through the CLC analysis in Constanța County are consistent with broader frameworks of land transitions in post-socialist countries [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. The most substantial changes were observed between 1990 and 2006, aligning with what the literature defines as the transition and post-transition phases, periods marked by the collapse of the centralized economy and Romania\u0026rsquo;s gradual integration into the European Union. These changes support existing models that link land use patterns to political and institutional transformations. In the early 1990s, agricultural land use was strongly influenced by the Agricultural Reform, which dismantled collective farms and promoted land restitution, leading to fragmented ownership and fluctuating land use. While the first half of the decade (1990\u0026ndash;1995) showed renewed interest in agricultural practices, the second half (1995\u0026ndash;2000) was characterized by instability due to structural weaknesses and the lack of supportive infrastructure. The expansion of agricultural land during 2000\u0026ndash;2006 as identified through CLC data, coincides with Romania\u0026rsquo;s EU accession preparations, confirming studies that highlight how accession-related policies stimulated rural development and land consolidation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe objective of this paper has been to understand how the dynamics of urbanization in Constanța County intersect with land use transformations, development pressures, and planning constraints in a post-socialist context.\u003c/p\u003e\u003cp\u003eThe study results revealed a continuous expansion of artificial surfaces, accompanied by a reduction in green areas and agricultural land, highlighting the increasing pressures of urbanization and reflecting patterns consistent with post-socialist urban growth models documented across Eastern Europe [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e], [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe continuous trend of urbanization has influenced the development of Constanța County, which, according to the 2021 Census, is now recognized as the most urbanized county in Romania. This rapid urbanization, however, has raised questions about land use management and the long-term sustainability of urban expansion.\u003c/p\u003e\u003cp\u003eAlthough land use change and urbanization have been extensively studied across various contexts in Romania [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e], [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e], this study contributes to the existing body of research by emphasizing the value of suitability analysis in assessing the long-term sustainability of urban expansion. It specifically examines how urban growth aligns with sustainable land use principles, while also considering the lasting influence of political decisions on urbanization patterns during the post-socialist period.\u003c/p\u003e\u003cp\u003eWhen considered alongside the findings of the suitability analysis, which identified a substantial share of land with high development potential, it becomes clear that significant spatial opportunities for future urban expansion still exist. These findings underscore an important point: extensive urbanization does not necessarily imply a lack of development potential.\u003c/p\u003e\u003cp\u003eIn line with this, the suitability analysis conducted for Constanța County revealed that a significant portion of the agricultural land, despite its current non-urban designation, was classified as highly or very highly suitable for urban development. Similar patterns have been observed in other regions, as reported by Al-Ghorayeb [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], where over 64% of agricultural land was classified as highly or very highly suitable for sustainable urban development, emphasizing the capacity of agricultural areas to support future urban expansion.\u003c/p\u003e\u003cp\u003eFrom a sustainability perspective, this raises critical questions about how such land is managed, and whether future urban expansion can be strategically planned to minimize ecological disruption and preserve essential ecosystem services.\u003c/p\u003e\u003cp\u003eThis concern becomes particularly relevant when examining the land-use suitability map, which identified significant areas along the Black Sea coast, particularly near Constanța city (the county capital), and some of the most sought-after tourist cities, such as Năvodari, Eforie, and Mangalia, as unsuitable for further urban expansion.\u003c/p\u003e\u003cp\u003eThese zones coincide with densely built-up regions characterized by artificial surfaces, high population density, and tourism-driven land use. The low suitability scores in these coastal zones can be attributed to limited land availability, environmental constraints, and increasing urban sprawl pressure from the real estate developers that have increasingly expressed a preference for constructing and developing new urban zones along the coastal lines. Similar patterns were observed in other regions, such as Lebanon [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]where urban expansion tends to be a contiguous extension of prior agglomerations, these areas on the coast attract developers due to their proximity to existing urban agglomerations. This contiguity to established cities enhances their attractiveness for new residents and companies, making them ideal candidates for development, despite the limitations posed by environmental and spatial factors. Al-Ghorayeb [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], noted that such trends of development along coastal areas are often driven by established infrastructure, population growth, and economic activity, further emphasizing the need for a balanced approach to managing these spaces.\u003c/p\u003e\u003cp\u003eWhile the findings of this study provide valuable insights into land-use dynamics in Constanța County, certain limitations must be acknowledged. These limitations include the subjectivity involved in perceiving and evaluating the severity of land-use restrictions during the suitability analysis. According to Luan [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], this directly influences the extent to which land is considered suitable for urban development.\u003c/p\u003e\u003cp\u003eAdditionally, the accuracy of the results depends on the reliability of the input datasets and the appropriateness of the assigned weights in the multi-criteria analysis. Temporal resolution and thematic detail of the CLC dataset may also limit the detection of finer-scale land use changes.\u003c/p\u003e\u003cp\u003eThe findings of this study have direct implications for urban planning policies and sustainable land-use management strategies in Constanța County. By identifying spatial patterns of land-use suitability, the analysis provides valuable evidence to inform policy decisions that aim to balance development needs with environmental protection. The results demonstrate that GIS-based suitability analysis can serve as a strategic planning tool, helping policymakers and urban planners direct future growth toward areas with high development potential while avoiding ecologically sensitive or low-suitability zones.\u003c/p\u003e\u003cp\u003eTo promote sustainable development in the region, the findings of this study suggest that urban expansion should be prioritized in areas identified as highly suitable, particularly those with existing infrastructure, lower population density, and minimal environmental constraints. Moreover, according to Al-Ghorayeb [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], to ensure sustainability, new urban agglomerations should be located within 700 meters of existing urban areas, promoting contiguous development and limiting unnecessary land fragmentation.\u003c/p\u003e\u003cp\u003eConversely, areas identified as having low suitability, such as those with high population density, high urbanization levels (as indicated by CLC LULC classes), and significant environmental constraints, should be designated for conservation or subjected to further study before any development is considered.\u003c/p\u003e\u003cp\u003eFurther research is recommended to refine and expand the current suitability analysis by incorporating additional land-use types and higher-resolution datasets, particularly at the city scale. In the case of Constanța municipality, future studies could benefit from using very high-resolution satellite imagery or detailed cadastral data to capture finer spatial variations and better reflect the complexity of urban environments. Moreover, exploring different types of suitability models, such as those tailored for green infrastructure or agricultural preservation, could provide more targeted support for specific planning objectives. Collaborations with local municipalities are also encouraged to ensure that GIS-based tools are effectively integrated into planning practices, enabling data-driven decisions that respond to both development pressures and sustainability goals. Furthermore, it is recommended that the involvement of city residents in planning and governance processes be prioritized to ensure more inclusive and sustainable urban development. This is particularly important in regions experiencing rapid urban growth, often driven by external investments and tourism-related expansion. As highlighted in existing literature [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e], [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e] inclusive and participatory planning approaches play a crucial role in addressing development challenges while fostering community engagement and ownership of urban space.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study aimed to analyze the land use dynamics in Constanța County using CLC data and suitability analysis, with a focus on understanding the spatial patterns of urbanization and their potential for sustainable development. The key objectives were to identify the most significant land use changes and evaluate the suitability of land for future urban development.\u003c/p\u003e\u003cp\u003eThe analysis revealed that the most significant land use changes occurred between 1990 and 2006, with a notable increase in artificial surfaces and a decrease in forested areas. Agricultural land initially declined during the early transition period but experienced a partial recovery in the years preceding Romania\u0026rsquo;s EU accession. These trends highlight the complex relationship between urban expansion and land use dynamics, shaped by distinct socio-economic phases. The suitability analysis further highlighted that although there is adequate land available for urban expansion, the areas with low and very low suitability are concentrated near existing built-up zones, particularly along the Black Sea coast. This suggests that urban growth in these areas could lead to significant environmental pressures, reducing the sustainability of development in the region.\u003c/p\u003e\u003cp\u003eThe findings contribute to the broader understanding of LULC transitions in post-socialist countries, particularly in the context of rapid urbanization and the challenges of balancing development with environmental preservation. This research demonstrates the value of integrated CLC data and GIS-based suitability analysis as tools for supporting sustainable urban planning decisions. It also underscores the importance of considering both ecological and developmental factors when planning for future growth.\u003c/p\u003e\u003cp\u003eIn practice, the findings of this study can support urban planning strategies by guiding decision-makers in identifying areas suitable for expansion without compromising environmental integrity. Specifically, areas identified as highly suitable for urban development should be prioritized, while regions with high environmental sensitivity should be preserved or subjected to further evaluation, in line with the need for comprehensive land management policies that foster sustainable growth.\u003c/p\u003e\u003cp\u003eOverall, this research contributes to a deeper understanding of land use dynamics in Constanța County and provides a solid foundation for making informed decisions about sustainable urban development in the region.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.E.M. and M.D. contributed to the conceptualization, methodology, validation, formal analysis, investigation, and resources. C.E.M. was responsible for data curation, original draft preparation, and figure/table preparation. Both authors contributed to the review and editing of the manuscript. M.D. supervised the research. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe author gratefully acknowledges the support provided by the Department of Geography at The Pennsylvania State University during the Fulbright Visiting Scholar Program, which facilitated access to valuable academic resources and expert guidance throughout the research process.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGao, L., \u0026amp; Bryan, B. A. (2017). Finding pathways to national-scale land-sector sustainability. \u003cem\u003eNature, 544(7649),\u003c/em\u003e 217\u0026ndash;222. https://doi.org/10.1038/nature21694 \u003c/li\u003e\n\u003cli\u003eWinkler, K., Fuchs, R., Rounsevell, M., \u0026amp; Herold, M. (2021). 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Lumen.\u003c/li\u003e\n\u003cli\u003eAligică, P. D., \u0026amp; Dabu, A. (2003). Land Reform and Agricultural Reform Policies in Romania\u0026rsquo;s Transition to the Market Economy: Overview and Assessment. \u003cem\u003eEastern European Economics, 41(5),\u003c/em\u003e 49\u0026ndash;69.\u003c/li\u003e\n\u003cli\u003eDijk, T. van. (2003). Scenarios of Central European land fragmentation. \u003cem\u003eLand Use Policy, 20(2),\u003c/em\u003e 149\u0026ndash;158. https://doi.org/10.1016/S0264-8377(02)00082-0 \u003c/li\u003e\n\u003cli\u003eGeorgeta Vidican. (2009). Assessing land reallocation decisions during transition in Romania. \u003cem\u003eLand Use Policy, 26(4),\u003c/em\u003e 1080\u0026ndash;1089.\u003c/li\u003e\n\u003cli\u003eSabates-Wheeler, R. (2001). Land Reform and Farm Choice in Romania\u003cem\u003e. Problems of post-communism, 48(4),\u003c/em\u003e 27\u0026ndash;37. https://doi.org/10.1080/10758216.2001.11655940 \u003c/li\u003e\n\u003cli\u003eSwinnen, J. F. 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Accessed January 10, 2025.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-modeling-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"enmo","sideBox":"Learn more about [Environmental Modeling \u0026 Assessment](https://www.springer.com/journal/10666)","snPcode":"10666","submissionUrl":"https://submission.nature.com/new-submission/10666/3","title":"Environmental Modeling \u0026 Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Urbanization, Urban Land Use Suitability, Land Use Change, Urban Planning","lastPublishedDoi":"10.21203/rs.3.rs-6892590/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6892590/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLand use and land cover changes in Constanța County are linked to socio-economic and political transformations, particularly during two key periods: the transition period (1990\u0026ndash;2003), marked by a shift from a centralized economy to a market-oriented system, and the post-transition period (2003-present), characterized by continued economic growth and urban expansion. These transformations align with broader trends in post-socialist and rapidly urbanizing regions, where economic restructuring often precipitates the large-scale conversion of agricultural land into built-up areas.\u003c/p\u003e\u003cp\u003eThis study employs CORINE Land Cover datasets to assess nearly 30 years of land use and land cover changes. Given the observed trends of increasing artificial surfaces and the decline of forest and semi-natural areas, a suitability analysis was conducted to deliver a spatially explicit evaluation of areas with potential for urban expansion.\u003c/p\u003e\u003cp\u003eThe integration of spatial, contextual, and environmental variables in the suitability analysis clearly demonstrated that cities situated in immediate proximity to the coastline possess a markedly low potential for further urban expansion.\u003c/p\u003e\u003cp\u003eSituated along the Black Sea coast, Constanța is the most urbanized county in Romania. It serves as a representative case for examining urbanization dynamics in coastal regions worldwide. In these areas, proximity to the sea accelerates urban growth, while also increasing vulnerability to environmental degradation. These findings provide valuable insights for other coastal cities facing similar development pressures, emphasizing the need for careful balancing of urban growth with environmental protection. This approach supports informed planning, particularly in regions undergoing accelerated land use transformations, a pattern common in fast-growing urban areas globally.\u003c/p\u003e","manuscriptTitle":"Land use dynamics and urban development suitability: A geospatial analysis of Romania’s most urbanized county","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 06:36:38","doi":"10.21203/rs.3.rs-6892590/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-18T08:14:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-09T16:23:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-03T23:02:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"287829931234534689413672447025790866769","date":"2025-09-22T07:25:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"140758174692562395642214112978663897761","date":"2025-09-19T10:40:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-08T12:05:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"182977324231940164255894598341466060446","date":"2025-08-14T10:57:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-16T15:12:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-11T02:42:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-26T16:30:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Modeling \u0026 Assessment","date":"2025-06-14T07:51:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-modeling-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"enmo","sideBox":"Learn more about [Environmental Modeling \u0026 Assessment](https://www.springer.com/journal/10666)","snPcode":"10666","submissionUrl":"https://submission.nature.com/new-submission/10666/3","title":"Environmental Modeling \u0026 Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e03c378f-babc-4074-a027-52fab67e8605","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:01:37+00:00","versionOfRecord":{"articleIdentity":"rs-6892590","link":"https://doi.org/10.1007/s10666-026-10117-6","journal":{"identity":"environmental-modeling-and-assessment","isVorOnly":false,"title":"Environmental Modeling \u0026 Assessment"},"publishedOn":"2026-04-11 15:58:28","publishedOnDateReadable":"April 11th, 2026"},"versionCreatedAt":"2025-07-23 06:36:38","video":"","vorDoi":"10.1007/s10666-026-10117-6","vorDoiUrl":"https://doi.org/10.1007/s10666-026-10117-6","workflowStages":[]},"version":"v1","identity":"rs-6892590","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6892590","identity":"rs-6892590","version":["v1"]},"buildId":"YNXEClSfUDGFtmkgMcPST","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}