Urban Sprawl Inside and Outside Natura 2000 Sites (SPAs) in Mediterranean EU States: The Case of Cyprus
Abstract
1. Introduction
- Extent of Urbanization: Urban cover within Natura 2000 sites is significantly lower than outside, yet the growth rate of urbanization within these sites is slightly higher, indicating an incipient sprawl into protected areas [10]. This sprawl is particularly pronounced in areas surrounded by densely populated urban clusters [10].
- Impact on Biodiversity: Urban sprawl leads to habitat fragmentation and loss, which are detrimental to the species and ecosystems that Natura 2000 sites aim to protect [17]. The spread of urban areas increases landscape fragmentation and the spread of invasive species, further threatening biodiversity [18].
- Socio-Economic Drivers: Factors such as population density, road and railway density, and economic development are significant drivers of urban sprawl [18]. These factors contribute to the pressure on Natura 2000 sites as urban areas expand to accommodate growing populations and infrastructure needs.
- Urban Planning and Management: Implementing sustainable urban growth management practices can help mitigate the effects of urban sprawl. This includes the use of geographic information systems and remote sensing for environmental monitoring, as well as the enforcement of planning policies [19].
- Conservation Strategies: The mitigation hierarchy approach, which involves avoiding, reducing, and offsetting negative impacts, is crucial for maintaining habitat connectivity and preventing biodiversity loss [20]. Spatial graph analysis can aid in identifying and prioritizing actions needed to maintain connectivity in urban landscapes [20].
- Strengthening enforcement through increased inspection capacity, deterrent penalties, timely prosecution of violations, and avoidance of repeated legalization or amnesty schemes;
- Improving planning integration, including mandatory consideration of Natura 2000 objectives in local plans, establishment of buffer zones, connectivity-oriented spatial planning, and enhanced regional coordination;
- Enhancing monitoring by deploying systematic high-resolution observation, early detection mechanisms, public reporting tools, and regular compliance audits;
- Targeted spatial interventions, prioritizing small and peri-urban Natura 2000 sites at higher risk, enforcing strict no-build zones in critical areas, restoring degraded habitats, and applying compensatory measures where impacts are unavoidable;
- Governance reform, aimed at better integration between conservation and planning authorities, strengthening local administrative capacity, improving stakeholder engagement, and ensuring transparency in decision-making.
- Urban Sprawl Theory: We utilize high-resolution data to redefine sprawl not just as an expansion of urban boundaries, but as a fragmented, pervasive encroachment into rurality.
- Efficacy Assessment Theory: We assess the “protective shield” of Natura 2000 (SPAs) by measuring building density as a proxy for conservation success or failure, testing whether legal designation translates into physical exclusion of development.
- Policy Implementation Theory: We examine the “implementation gap” between the social intent of the “memonomeni katoikia” (isolated housing) policy and its actual spatial outcome, identifying how institutional loopholes facilitate luxury-driven sprawl.
2. Materials and Methods
3. Results
3.1. Isolated Housing and Other Built Premises Within SPAs
3.2. Results of Urban Sprawl at the Country Level per Planning Zone (1993–2022)
3.3. District Comparison of Isolated Houses for the Years 1993–2022
4. Discussion
5. Conclusions
- Implementing stricter legal measures and financial instruments to curb the exploitation of planning loopholes and the abolition or strict tightening of isolated housing policy, which essentially is a planning distortion policy that appeases and facilitates urban sprawl.
- Standardizing high-resolution, building-level mapping across the EU to ensure precise cross-border monitoring, thus overcoming existing limitations and underestimation of urban sprawl.
- Conducting site-specific analyses within the Natura 2000 network to understand localized patterns at the site level.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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| Region | Key Findings | Citation |
|---|---|---|
| Famagusta, Cyprus | Loss of fertile land, habitat fragmentation, increased greenhouse gas emissions | [12,21] |
| Nicosia, Cyprus | Scattered housing growth in buffer zone, environmental vulnerability due to climate change | [22] |
| Cyprus | Land use change, environmental threats, loss of agricultural land, fragmentation | [23] |
| Austria | Loss of forest and agricultural land to settlement expansion | [24] |
| Mediterranean Region | Soil degradation, biodiversity loss, water resource degradation, increased emissions | [25,26] |
| EU level | Urban sprawl in Natura 2000 network, Land transformation | [10] |
| EU level | Land lost to artificial surfaces, land imperviousness inside and outside Natura 2000 sites | [9] |
| Country | Common Term/Framing (Indicative) | Characteristic Pattern (as Reported in Literature) |
|---|---|---|
| Spain | “Urbanización” | Coastal resort/second-home enclaves; pressure on protected landscapes [31]. |
| Italy | “Abusivismo edilizio” | Persistent illegal/unauthorized coastal construction; enforcement/regularization tensions [32]. |
| Greece | Unregulated expansion/coastal artificialization | Tourism- and second-home-driven sprawl, including island contexts; continued impervious expansion in coastal Natura 2000 areas [28,33]. |
| France | Mitage/dispersed development | Dispersed coastal/rural development; governance barriers in protected coastal systems [29]. |
| Portugal | Dispersed settlement (limited evidence in supplied sources) | General recognition in governance debates, but limited Natura-specific quantitative evidence in reviewed material [30]. |
| Geography/Case | What Is Measured | Key Finding (as Reported) | Main Implication |
|---|---|---|---|
| Europe-wide Natura 2000 (pan-European) | Urban cover and growth rates using consistent datasets | Urban cover is lower inside Natura 2000 than outside, but growth rates are slightly higher—suggesting incipient sprawl into protected areas [10]. | Designation reduces absolute urbanization but does not eliminate development pressure. |
| Spain (Madrid region protected areas) | Land-use scenarios/modelling of built-up growth | Built-up expansion continues within protected areas; scenario modelling indicates substantial future land take under baseline trends [27]. | Protected status alone may be insufficient under strong metropolitan pressure. |
| Greece (Mediterranean coast) | Impervious land expansion in coastal settings | Continued impervious surface expansion in coastal Natura 2000 areas, associated with renewed development cycles [28]. | Soil sealing and hydrological impacts can accumulate inside/near Natura sites. |
| Greece (infrastructure–Natura overlap) | Land artificialization linked to wind-energy siting | Substantial artificialization risk from spatial planning shortcomings where projects overlap Natura 2000 areas [34]. | Large projects can create step changes in land take when planning integration is weak. |
| Italy (Sardinia, terrestrial Natura 2000) | Rural Buildings Fragmentation Index + mesh density | Rural buildings contribute measurably to fragmentation; relationships vary across landscape units [35]. | Low-density structures can be important fragmentation drivers even without “urban fabric” expansion |
| Italy (detection methods) | AI-driven detection of unauthorized buildings | Evidence of emerging technical approaches to identify unauthorized buildings in fragile territories [36]. | Monitoring capacity is expanding, but institutional uptake remains uneven. |
| Data Source/Technique | Description | Citation |
|---|---|---|
| High-Resolution Orthophotos | Used for detailed habitat mapping and updating of Natura 2000 habitat maps in Cyprus. | [48,49] |
| Sentinel-2 Data | Provides multispectral data for habitat classification and monitoring, with applications in NaturaSat software (V2.1.7). | [50,51] |
| Random Forest Classification | Achieves high accuracy (91–94%) in habitat mapping using Sentinel-2 and topographical data. | [49] |
| Object-Based Image Analysis (OBIA) | Effective for high-resolution orthophotos, enabling detailed land cover classification. | [52,53] |
| Drone Orthomosaic Images | Acquired at 1 m resolution, useful for small-scale features like Ecological Focus Areas. | [49] |
| NaturaSat Software | Utilizes semi-automatic segmentation and deep learning for habitat identification and monitoring. | [51] |
| LiDAR Data | Enhances habitat mapping with structural diversity indices, improving conservation status assessment. | [54] |
| N = 32 | Year | Mean | Std. Deviation | 95% Confidence Interval for the Mean | Max | |
|---|---|---|---|---|---|---|
| Lower Bound | Upper Bound | |||||
| Number of isolated houses | 1993 | 10.66 | 31.39 | −0.66 | 21.97 | 146.00 |
| 2008 | 32.16 | 49.34 | 14.37 | 49.94 | 229.00 | |
| 2022 | 48.63 | 64.99 | 25.19 | 72.06 | 268.00 | |
| Number of warehouses & auxiliary buildings | 1993 | 19.19 | 24.67 | 10.29 | 28.08 | 102.00 |
| 2008 | 56.81 | 52.30 | 37.95 | 75.67 | 211.00 | |
| 2022 | 65.41 | 60.50 | 43.59 | 87.22 | 233.00 | |
| Total number of building premises | 1993 | 29.84 | 53.23 | 10.65 | 49.03 | 248.00 |
| 2008 | 88.97 | 89.69 | 56.63 | 121.31 | 332.00 | |
| 2022 | 114.03 | 111.94 | 73.67 | 154.39 | 381.00 | |
| Density of isolated houses | 1993 | 0.51 | 1.40 | 0.00 | 1.01 | 6.79 |
| 2008 | 2.10 | 3.73 | 0.75 | 3.44 | 14.77 | |
| 2022 | 2.79 | 4.58 | 1.14 | 4.44 | 21.43 | |
| Density of warehouses & auxiliary buildings | 1993 | 1.04 | 1.49 | 0.50 | 1.58 | 5.38 |
| 2008 | 3.59 | 5.48 | 1.61 | 5.56 | 24.26 | |
| 2022 | 3.52 | 5.45 | 1.56 | 5.49 | 25.85 | |
| Total density of built premises | 1993 | 1.54 | 2.61 | 0.60 | 2.49 | 12.18 |
| 2008 | 5.68 | 8.21 | 2.72 | 8.64 | 31.82 | |
| 2022 | 6.31 | 8.32 | 3.31 | 9.31 | 31.82 | |
| Year | % Increase/Year | |||||
|---|---|---|---|---|---|---|
| 1993 | 2008 | 2022 | Increase (%) 1993–2008 | Increase (%) 2008–2022 | Increase (%) 1993–2022 | |
| Number of isolated houses within SPA sites | 341 | 1029 | 1556 | 201.76% | 51% | 356% |
| Other types of building premises (warehouses & auxiliary buildings) within SPA sites | 614 | 1818 | 2093 | 196.09% | 15% | 241% |
| Total number of building premises (isolated houses and warehouses & auxiliary buildings) within SPA sites | 955 | 2847 | 3649 | 198% | 28% | 282% |
| N = 32, K = 3 | F (2, 93) | p-Value |
|---|---|---|
| Number of isolated houses | 4.55 | 0.013 * |
| Number of warehouses & auxiliary buildings | 8.28 | 0.001 * |
| Total number of built premises | 7.66 | 0.001 * |
| Density of isolated houses | 3.56 | 0.032 * |
| Density of warehouses & auxiliary buildings | 3.27 | 0.042 * |
| Total density of built premises | 4.49 | 0.014 * |
| N = 32 Dependent Variable | (I) Year | (J) Year | Mean Difference (I − J) | p-Value | 95% Confidence Interval | |
|---|---|---|---|---|---|---|
| Lower Bound | Upper Bound | |||||
| Number of households | 1993 | 2008 | −21.50 | 0.21 | −51.56 | 8.56 |
| 2022 | −37.97 | 0.01 * | −68.02 | −7.91 | ||
| 2008 | 1993 | 21.50 | 0.21 | −8.56 | 51.56 | |
| 2022 | −16.47 | 0.40 | −46.52 | 13.59 | ||
| 2022 | 1993 | 37.97 | 0.01 * | 7.91 | 68.02 | |
| 2008 | 16.47 | 0.40 | −13.59 | 46.52 | ||
| Numbers of warehouses | 1993 | 2008 | −37.63 | 0.01 * | −66.40 | −8.85 |
| 2022 | −46.22 | 0.001 * | −74.99 | −17.45 | ||
| 2008 | 1993 | 37.63 | 0.01 * | 8.85 | 66.40 | |
| 2022 | −8.59 | 0.76 | −37.37 | 20.18 | ||
| 2022 | 1993 | 46.22 | 0.001 * | 17.45 | 74.99 | |
| 2008 | 8.59 | 0.76 | −20.18 | 37.37 | ||
| Total number of premises | 1993 | 2008 | −59.13 | 0.02 * | −111.72 | −6.53 |
| 2022 | −84.19 | 0.001 * | −136.79 | −31.59 | ||
| 2008 | 1993 | 59.13 | 0.02 * | 6.53 | 111.72 | |
| 2022 | −25.06 | 0.50 | −77.66 | 27.54 | ||
| 2022 | 1993 | 84.19 | 0.001 * | 31.59 | 136.79 | |
| 2008 | 25.06 | 0.50 | −27.54 | 77.66 | ||
| Density for houses | 1993 | 2008 | −1.59 | 0.17 | −3.68 | 0.50 |
| 2022 | −2.28 | 0.03 * | −4.37 | −0.19 | ||
| 2008 | 1993 | 1.59 | 0.17 | −0.50 | 3.68 | |
| 2022 | −0.69 | 0.71 | −2.78 | 1.40 | ||
| 2022 | 1993 | 2.28 | 0.03 * | 0.19 | 4.37 | |
| 2008 | 0.69 | 0.71 | −1.40 | 2.78 | ||
| Density for warehouses | 1993 | 2008 | −2.55 | 0.07 * | −5.25 | 0.16 |
| 2022 | −2.48 | 0.08 * | −5.19 | 0.22 | ||
| 2008 | 1993 | 2.55 | 0.07 * | −0.16 | 5.25 | |
| 2022 | 0.07 | 1.00 | −2.64 | 2.77 | ||
| 2022 | 1993 | 2.48 | 0.08 * | −0.22 | 5.19 | |
| 2008 | −0.07 | 1.00 | −2.77 | 2.64 | ||
| Density for total premises | 1993 | 2008 | −4.14 | 0.049 * | −8.26 | −0.02 |
| 2022 | −4.77 | 0.02 * | −8.88 | −0.65 | ||
| 2008 | 1993 | 4.14 | 0.049 * | 0.02 | 8.26 | |
| 2022 | −0.63 | 0.93 | −4.74 | 3.49 | ||
| 2022 | 1993 | 4.77 | 0.02 * | 0.65 | 8.88 | |
| 2008 | 0.63 | 0.93 | −3.49 | 4.74 | ||
| Type of Planning Zone | Number of Isolated Houses (1993) | Number of Isolated Houses (2008) | Number of Isolated Houses (2022) | % Increase (1993–2008) | % Increase (2008–2022) | % Increase (1993–2022) | % of Total Houses (1993) | % of Total Houses (2008) | % of Total Houses (2022) |
|---|---|---|---|---|---|---|---|---|---|
| Γ (1, 2, 3, Γα) | 1111 | 3371 | 7430 | 203.42% | 120.41% | 568.77% | 45.53% | 51.70% | 58.78% |
| Z1 | 494 | 1497 | 2659 | 203.04% | 77.62% | 438.26% | 20.25% | 22.96% | 21.04% |
| Z2 | 49 | 21 | 39 | −57.14% | 85.71% | −20.41% | 2.01% | 0.32% | 0.31% |
| Z3 | 143 | 236 | 382 | 65.03% | 61.86% | 167.13% | 5.86% | 3.62% | 3.02% |
| Z3-ΠΠ | 16 | 23 | 49 | 43.75% | 113.04% | 206.25% | 0.66% | 0.35% | 0.39% |
| Z4-ΠΚΦ | 61 | 66 | 75 | 8.20% | 13.64% | 22.95% | 2.50% | 1.01% | 0.59% |
| AZ | 141 | 235 | 267 | 66.67% | 13.62% | 89.36% | 5.78% | 3.60% | 2.11% |
| Other | 425 | 1071 | 1739 | 152.00% | 62.37% | 309.18% | 17.42% | 16.43% | 13.76% |
| Total | 2440 | 6520 | 12,640 | 167.21% | 93.87% | 418.03% | 100.00% | 100.00% | 100.00% |
| District | Number of Houses (1993) | Number of Houses (2008) | Number of Houses (2022) | % Increase (1993–2008) | % Increase (2008–2022) | % Increase (1993–2022) | % of Total Houses (1993) | % of Total Houses (2008) | % of Total Houses (2022) |
|---|---|---|---|---|---|---|---|---|---|
| Nicosia | 885 | 1406 | 2395 | 58.87% | 70.34% | 170.62% | 36.27% | 21.56% | 18.95% |
| Limassol | 668 | 1732 | 3289 | 159.28% | 89.90% | 392.37% | 27.38% | 26.56% | 26.02% |
| Larnaca | 442 | 1111 | 2264 | 151.36% | 103.78% | 412.22% | 18.11% | 17.04% | 17.91% |
| Ammachostos | 82 | 237 | 1116 | 189.02% | 370.89% | 1260.98% | 3.36% | 3.63% | 8.83% |
| Paphos | 363 | 2034 | 3576 | 460.33% | 75.81% | 885.12% | 14.88% | 31.20% | 28.29% |
| Total | 2440 | 6520 | 12,640 | 167.21% | 93.87% | 418.03% | 100.00% | 100.00% | 100.00% |
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Panayides, P.; Panayi, P.; Tziraki, M.; Mavrikiou, P.; Ioannou, B. Urban Sprawl Inside and Outside Natura 2000 Sites (SPAs) in Mediterranean EU States: The Case of Cyprus. Land 2026, 15, 481. https://doi.org/10.3390/land15030481
Panayides P, Panayi P, Tziraki M, Mavrikiou P, Ioannou B. Urban Sprawl Inside and Outside Natura 2000 Sites (SPAs) in Mediterranean EU States: The Case of Cyprus. Land. 2026; 15(3):481. https://doi.org/10.3390/land15030481
Chicago/Turabian StylePanayides, Panicos, Panicos Panayi, Maria Tziraki, Petroula Mavrikiou, and Byron Ioannou. 2026. "Urban Sprawl Inside and Outside Natura 2000 Sites (SPAs) in Mediterranean EU States: The Case of Cyprus" Land 15, no. 3: 481. https://doi.org/10.3390/land15030481
APA StylePanayides, P., Panayi, P., Tziraki, M., Mavrikiou, P., & Ioannou, B. (2026). Urban Sprawl Inside and Outside Natura 2000 Sites (SPAs) in Mediterranean EU States: The Case of Cyprus. Land, 15(3), 481. https://doi.org/10.3390/land15030481

