Search Results (1,296)

Despite extensive global progress monitoring under the 2030 Agenda, existing Sustainable Development Goal (SDG) assessment frameworks remain structurally blind to within-country distributional disparities. This study addresses this gap by developing a methodologically transparent composite SDG index for multi-level governance assessment, applying it to 218 Nomenclature of Territorial Units for Statistics (NUTS 2) regions across the European Union over the period 2015–2022 (1744 region-year observations). In this context, the term “region-year observations” refers strictly to the balanced panel data structure, which is calculated by observing 218 distinct sub-national regions continuously over an 8-year period (218 regions × 8 years The index aggregates four dimensions—social, economic, educational, and institutional—using min-max normalization. The analysis yields three main results: (1) Spatial econometric analysis reveals strong, persistent positive spatial autocorrelation, with high-performing clusters concentrated in Northern and Western Europe and lagging clusters in Eastern and Southern peripheries. (2) A spatial error model identifies institutional governance quality as a consistent statistical predictor of sub-national SDG performance. The significance of the spatial error parameter (λ = 0.497) suggests that unobservable institutional and geographical common shocks systematically link neighboring regions. (3) Cluster analysis further distinguishes four regional archetypes: Disadvantaged, Leaders, Educated, and Transitional. These findings underscore the need for spatially aware SDG monitoring infrastructure and investment in institutional capacity as prerequisites for equitable governance, as integrating spatial dependencies is crucial to prevent national averages from masking severe regional developmental traps. Full article

This study analyzes domestic tourism mobility in Spain using aggregated and anonymized mobile phone data, with a particular focus on the outbound market of the municipality of Madrid and its territorial redistribution between September 2019 and September 2025. Using experimental statistics from the National Institute of Statistics (INE), a monthly series of origin–destination flows to all Spanish municipalities was constructed, harmonizing the municipal database and incorporating intensive indicators to improve inter-territorial comparability. The spatiotemporal dynamics were integrated into a Space–Time Cube (monthly resolution), and Emerging Hot Spot Analysis (EHSA) was applied to classify the persistence, intensification, or attenuation of high- and low-intensity clusters. Additionally, the grouping of time series allowed for the identification of seasonal patterns associated with coastal, urban, and nearby inland destinations. The results show: (i) a synchronous disruption in the spring of 2020 linked to COVID-19; (ii) a staggered recovery beginning in 2021, consolidating in 2023–2025; and (iii) a dual structural pattern, with a strong concentration of volumes in large urban and coastal hubs, along with high relative intensities in small municipalities in the ring surrounding Madrid. EHSA identifies intensifying hotspots in established coastal systems (Costa del Sol and Costa Blanca) and cooling or attenuated dynamics in parts of the inland region, consistent with the reconfiguration of the “tourism radius” following the pandemic. Limitations arising from statistical confidentiality and the representativeness of the source are discussed, and future research directions are proposed based on the integration of the information with expenditure and transportation data and on spatiotemporal modeling to support destination planning and management. Full article

Background/Objectives: Sarcopenia—the progressive loss of skeletal muscle mass and function—is a growing public health challenge in ageing populations. Island territories face compounded vulnerabilities due to distinct epidemiological and socio-economic profiles. This study examines sarcopenia risk prevalence among community-dwelling older adults in Tenerife (Canary Islands, Spain) and estimates the economic burden alongside the cost-effectiveness of evidence-based interventions. Methods: A cross-sectional study was conducted among 374 community-dwelling older adults (mean age 80.4 years, SD 4.8; 51.1% female) recruited from primary care health centres across three health zones in Tenerife. Participants were stratified into a control group without established chronic disease-related functional decline (Group 1; n = 274) and a case group with multimorbidity and functional limitations (Group 3; n = 100). Sarcopenia risk was assessed using the SARC-F questionnaire (threshold ≥ 4). A comprehensive geriatric battery—including the Barthel Index, FRAIL scale, MNA-SF, Pfeiffer test, SPPB, handgrip dynamometry, and IPAQ—characterised multidimensional vulnerability. Annual direct and indirect costs were estimated using unit costs from Spanish national health accounts, and intervention cost-effectiveness was modelled using published meta-analytic data. Results: Overall sarcopenia risk prevalence was 36.4% (n = 136; SARC-F ≥ 4), rising to 83.0% in the case group versus 19.3% in controls (OR ≈ 21.5, p < 0.001). Prevalence was 42.1% in males and 30.9% in females. Diabetes was independently associated with elevated risk (44.8% vs. 29.9%; OR 1.90, 95% CI 1.23–2.92; p = 0.003). Health Zone 1 exhibited the highest prevalence (63.0%) versus Zones 2 (23.5%) and 3 (32.8%). Multidimensional vulnerability was pervasive: 28.6% of participants were frail, 75.7% had nutritional compromise, 11.5% showed moderate cognitive impairment, and 89.8% reported low or no physical activity. The estimated annual socio-economic cost of sarcopenia in Tenerife is approximately EUR 88.9 million (Spain nationally: EUR 12.1 billion). Combined exercise–nutrition interventions yield cost-per-QALY ratios of EUR 3800–7000, far below Spain’s EUR 25,000/QALY threshold. Conclusions: Sarcopenia constitutes a major, multidimensionally compounded health burden in Tenerife’s older population, concentrated among frail, diabetic, nutritionally compromised, and physically inactive individuals. The economic case for universal SARC-F screening and multicomponent intervention is compelling, exceeding cost-effectiveness thresholds by a wide margin. Territorial disparities in burden call for equity-oriented, place-based resource allocation within the Canarian health system. Full article

Depopulation and structural demographic challenges affect social and territorial cohesion in Europe, a phenomenon that is particularly evident in rural municipalities in Spain, where the loss of the working-age population and the concentration of older adults threaten sustainability. This study analyzes the case of Pescueza (Cáceres, Spain) using a mixed-methods design that combines longitudinal demographic analysis (2000–2024) with a qualitative evaluation of the community project “Quédate con nosotr@s,” which focuses on comprehensive care and intergenerational participation. The results are critical regarding the demographic structure, with an aging index of 500% and dependency levels three times higher than the national average, although a slight demographic recovery linked to local initiatives is observed. This project has positive effects on social cohesion, community capital, and resilience in the face of demographic challenges, establishing itself as a replicable model for rural micro-territories. The study proposes a strategic framework based on the SWOT-CAME matrix and social sustainability indicators, aligned with the Sustainable Development Goals and European territorial cohesion policies. It concludes that social innovation, collaborative governance, and multilevel cooperation are key elements for addressing rural aging, and recommends public policies aimed at stable funding, inclusive digitalization, attracting young people, specialized training, and the creation of adapted infrastructure. Full article

Housing inequalities remain a major challenge for contemporary urban governance, as they combine economic, social, spatial, and demographic dynamics that are difficult to capture through single indicators. This paper develops a data-driven assessment of housing inequalities in Portugal between 2015 and 2025, drawing on official national and European statistics and applying a Business Intelligence (BI) and urban analytics framework oriented towards policy monitoring. Official data from Statistics Portugal and Eurostat are integrated through an analytical pipeline including automated extraction via public APIs, data enrichment, and visual analytics. The workflow follows a CRISP-DM-inspired structure, creating a set of normalized indicators to capture different dimensions of housing conditions. The results point to a structurally polarized housing market. Housing valuations increased across all regions, but at uneven rates, reinforcing territorial disparities rather than convergence. Metropolitan and tourism-oriented regions experienced faster appreciation and indirect effects, while year-over-year growth in completed dwellings slowed after 2021–2022, indicating an uneven supply response. Beyond its empirical findings, the primary contribution of this study lies in demonstrating how BI and data science methodologies can be operationalized to monitor housing inequalities using official statistics. The proposed framework is replicable and can be adapted to other territorial and policy contexts. Full article

Territorial inequalities in higher education systems remain a persistent challenge in highly centralized countries. In Chile, the concentration of academic resources and institutional capacities in the Metropolitan Region has historically shaped disparities in educational opportunities and outcomes. In this context, the National Diagnostic Assessment (END) serves as a standardized instrument designed to evaluate the achievement of professional standards in initial teacher education programs. This study aimed to identify and characterize the territorial patterns of achievement in disciplinary domains of the END assessment, examining whether significant differences between macrozones reflect structural inequalities in educational resources and institutional capacities. A quantitative approach was adopted using secondary data from the national open database of the Ministry of Education. Statistical analyses were conducted in R, applying Mann–Whitney U tests for independent comparisons between macrozones and Wilcoxon tests for paired comparisons between disciplinary topics. The results reveal a consistent territorial pattern in which the Metropolitan Region and the Central–North macrozone present the highest performance levels, while the Northern and Southern macrozones show comparatively lower averages. These findings suggest that territorial conditions and institutional resources may influence learning outcomes even within nationally standardized evaluation frameworks. Full article

The Carpathian Mountains are an important hotspot of European biodiversity, where geological history, climatic diversity, and altitudinal heterogeneity have determined a great diversity and endemism of vascular plants. The study was conducted in the national park of Piatra Craiului, a distinctive limestone massif in the Southern Carpathians. The dataset included 731 vascular plant species from the study area, of which 35 taxa are endemic to the Carpathians (of the 47 reported in this area), and 18 are classified as species of conservation interest in the Management Plan of the National Park (MP). The distribution of endemic species showed different habitat and altitudinal specificity across 15 vegetation types, including 14 Natura 2000 habitats and one outside the EUR 28 classification. The endemic species showed a bell-shaped altitudinal distribution, peaking at 1600–1700 m and concentrated in high-altitude open habitats rather than forested mid-elevations. The PCA separates endemic species along a main gradient from open, disturbed, light-rich habitats to stable, nutrient- and moisture-rich forest environments, and a secondary gradient related to temperature and soil reaction linked to altitude. Endemic species are predominantly associated with calcareous rocky and grassland habitats and are almost absent from mesophilic and hygrophilous habitats. A positive association between endemic species frequency and the total number of species of conservation interest per plot was detected. We concluded that species of conservation interest (such endemic species) are unevenly distributed among habitat types in the Carpathians, with the greatest diversity and abundance in subalpine rocky and grassland habitats, shaped by altitude and isolation. Although the threatened endemic species are not officially listed by national law, they are indirectly protected by management zonation. In Piatra Craiului the richest habitats in endemic species are included in the designated zones of the national park with the highest protection regime, according to the National Park’s Management Plan. Moreover, this territory is included in a Natura 2000 site (ROSAC0194 Piatra Craiului) ensuring an additional level of protection for the habitats where endemic species are found. Full article

Blue–green spaces serve as the core carriers of urban ecosystems, and their conservation and optimization have emerged as pivotal issues in territorial spatial planning and ecological governance. Taking Guilin, a national innovation demonstration zone for China’s Sustainable Development Agenda, as the study area, a deep learning-based DBDTAF-Net classification model is constructed using 2020 Sentinel-2 remote sensing imagery and AW3D30 Digital Surface Model (DSM) data. The model achieves a mean Intersection-over-Union (mIoU) of 86.05% on the test set and an IoU of 94.67% for rocky desertification areas. Based on the classification results, 21 derived indicators (including landscape patterns of BGSs) and six meteorological and topographic factors, alongside three core ecosystem service indicators—Aboveground Biomass (AGB), Net Primary Productivity (NPP), and soil conservation—are extracted to characterize their spatial patterns. The XGBoost-SHAP framework is employed to quantify the driving effects and threshold responses of BGS patterns on ecosystem services. The results indicate that (1) BGSs in Guilin display a spatial pattern of “green-dominated, blue-supplemented, generally contiguous yet locally fragmented,” and all three ecosystem services exhibit significant spatial clustering. (2) Landscape pattern factors of green spaces constitute the dominant influencing factors, with contribution rates ranging from 22.3% to 28.6%. Specifically, green space_COHESION demonstrates a stable linear positive effect. A green space ratio below 45% suppresses AGB, whereas exceeding 45% shifts to a positive effect and represents an efficient enhancement interval for NPP while exerting a continuously positive influence on soil conservation. A cultivated land proportion below 30% leads to a strongly increasing inhibitory effect on AGB and soil conservation, whereas its inhibition on NPP weakens beyond 20%. A construction land proportion exceeding 10% significantly suppresses NPP, and the inhibitory effect stabilizes above 20%. Green space patch density below 0.8 shows a pronounced negative effect, which diminishes above 0.8. Blue space factors exert relatively weak effects. (3) The ecosystem service supply capacity varies across functional zones in Guilin, with the ecological barrier zone performing the best, the modern agricultural zone performing moderately, and the six central urban districts of the Shanshui Metropolis Area exhibiting the lowest levels. This study provides a technical framework for high-precision extraction of urban BGSs and quantitative analysis of factors influencing ecosystem services, offers decision support for ecological conservation and restoration in Guilin, and furthermore proposes insights for the coordinated development of rational land resource utilization and ecosystem service enhancement in other karst cities. Full article

In many African nations, including Nigeria, groundwater remains the most readily available source of clean water. However, finding and developing these resources in heterogeneous terrain, such as the Federal Capital Territory (FCT), Abuja, is challenging due to the uneven distribution of the aquifers and complex geological settings. Using a GIS-based machine learning approach that incorporates surface and subsurface hydrogeological parameters, this study defines groundwater potential zones (GWPZ). Nine conditioning factors were derived from remote sensing, geophysical and climatic datasets. Aquifer thickness, depth to bedrock, geology, rainfall, slope, LULC, lineament density, drainage density and distance from river were among these variables. Three machine learning models: Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM) and Random Forest (RF) were trained and validated using 2410 borehole records (productive and abortive). Hold-out validation (80:20), 10-fold cross-validation, ROC-AUC, and confusion matrix were used to assess each model’s performance. The ensemble models outperformed the SVM, achieving higher predictive accuracy and better generalisation (XGBoost: 0.89, RF: 0.88 and SVM: 0.87). The generated maps categorised the study area into five GWPZs: very high, high, moderate, low and very low. These findings provide a scientific foundation for groundwater exploration and sustainable water resource management in the study area. Full article

This paper examines several trends in contemporary tourism: the broadening of the very notion of a “tourist destination”, alongside the growing importance of providing a diversified and territorially integrated supply; the opportunities that tourism may offer to some “marginal” areas; and the impact of the COVID-19 pandemic, which calls for a rethinking of more sustainable and responsible forms of travel, both for the environment and for the people encountered along the way. Tourism related to walking routes and trails appears to benefit from all of these trends, and indeed, this segment has shown clear growth in Italy. The paper then considers the potential and critical issues of this sector in Forlì-Cesena County, with a focus on the nine Apennine municipalities included in the National Strategy for Inner Areas (SNAI). Through an analysis of local tourism promotion websites, a secondary analysis of statistical data, and 19 questionnaire–interviews with local stakeholders, this study examines an area where tourism is growing but remains largely concentrated on the coast. Although the potential of walking routes is confirmed by the various itineraries crossing this area, their actual use and impact on local development still appear limited. Full article

The generation of reliable and up-to-date national land cover information is essential for environmental management, climate action, and territorial planning. In Colombia, the CORINE Land Cover Colombia (CLCC) framework has been the official reference for land cover monitoring since 2000, traditionally updated through expert-based Computer-Assisted PhotoInterpretation (CAPI) at a 1:100,000 scale. However, increasing demands for higher spatial resolution and more frequent temporal updates have made process optimization necessary, driving the incorporation of cloud-based processing and artificial intelligence (AI), including machine learning and deep learning algorithms. This study presents a semi-automated methodology for generating a new generation of harmonized CLCC-compatible raster land cover maps at a 1:50,000 scale—offering four times greater spatial detail than the official vector product—with the capacity for semi-automated annual updates. The approach combines legend harmonization from 55 to 23 classes, historical CORINE Land Cover (CLC) polygon-guided sample generation, spectral stability analysis, and regionalized classification across 190 homogeneous subregions, supported by a reproducible cloud-based architecture. National land cover maps were produced for 2020, 2022, and 2024 with thematic accuracies above 80% and Kappa coefficients up to 0.87, alongside change maps for the 2022–2024 period capturing key dynamics in agricultural frontier expansion, wetland variability, and urban expansion. The resulting products also provide structured inputs for expert-based CAPI workflows, supporting the continuous updating of the official 1:100,000 CLCC map. The results demonstrate the operational capacity of integrating AI, cloud computing, and expert knowledge to strengthen Colombia’s national land cover monitoring system. Full article

The Republic of Korea has implemented routine vaccination against foot-and-mouth disease virus (FMDV) in livestock using a bivalent vaccine comprising serotypes O and A following the massive FMD outbreak in 2010, while antigens for the remaining serotypes are maintained in overseas antigen banks. The recent geographic expansion of FMDV Southern African Territories 1 (SAT1) beyond Africa underscores the need for enhanced preparedness in previously unaffected regions. In this study, we evaluated the SAT1 BOT-R strain as a candidate vaccine seed for potential domestic vaccine production by optimizing antigen production conditions, assessing scalability, determining virus inactivation parameters, and examining immunogenicity in pigs. Optimal antigen yield was achieved at 20 h−24 h post infection with a multiplicity of infection of 0.005−0.01, with production remaining stable under mildly alkaline conditions. Antigen productivity was consistently maintained during scale-up from shake flasks to a bioreactor, yielding up to 9.5 μg/mL. Complete virus inactivation was achieved using binary ethylenimine at 2 mM for 24 h at 26 °C. Vaccines formulated from both flask- and bioreactor-derived antigens elicited comparable neutralizing antibody responses in pigs, reaching a median titer of 1:500 following booster immunization. Collectively, these findings demonstrate that the SAT1 BOT-R strain is a viable and scalable candidate for SAT1 antigen banking and future domestic vaccine production, providing a practical framework for strengthening national preparedness against potential incursions of FMDV SAT1. Full article

At the global level, as well as in Lithuania, the risks associated with climate change and other emerging threats—such as war, radiation, and pandemics—are increasing, and adequate preparedness is necessary to avoid their negative consequences. Despite international and other strategic efforts to assess emerging threats, preparedness to adapt to them and to mitigate their impacts remains insufficient. Considering the insufficient level of preparedness of the country’s cities to cope with these threats, this article introduces a new, sustainable element of urban structure—a comprehensive territorial structural unit capable of functioning under adverse and hazardous conditions. The formation of this new urban complex is based on three core sustainability principles—social, ecological, and economic—alongside international and national urban planning experience. The newly proposed sustainable urban structural complex consists of a group of blocks with diverse building types bounded perimetrically by urban public transport streets connecting the complex with other urban areas. For the functionality of the complex, a structural element—a green core—is envisaged in its central part, intended to serve residents through recreation, social interaction, civil security, and other functions. Due to its functional characteristics, structure, autonomy, capacity to integrate with other urban structures, and other properties, this urban complex closely resembles a biological cell; thus, for semantic clarity, it is termed an urbocell (urban cell). This urbocell is integrated into the urban fabric of residential districts and the entire city, forming a sustainable spatial and urban structure suitable for safe living, working, and recreation. The article models potential structural elements of the urbocell—namely, selected urban block morphotypes—using the computational tool Autodesk Forma, the results of which may support more informed urban planning decisions for developing a more sustainable and climate-resilient urban environment. Full article

The European “Twin Transition” paradigm assumes a synergy between digital transformation and environmental sustainability, yet empirical evidence remains mixed, particularly in transition economies. This study examines the relationship between digital human capital and circular economy performance in Southeastern Europe (Slovenia, Croatia, Bulgaria, Romania, and Serbia). The study applies a multilevel quantitative research design combining correlation analysis, linear regression, and spatial assessment to examine the relationship between digital human capital and circular economy performance. The results indicate a moderate relationship between digital competencies and recycling performance. At the same time, regional analysis reveals that higher digital capacity does not consistently correspond to higher circular outcomes. The findings also show that national-level indicators may mask substantial territorial disparities, suggesting that aggregate indicators may not fully capture regional variation. The effectiveness of the digital–circular relationship appears to depend on broader structural conditions, including institutional capacity and infrastructure. The study highlights the importance of spatial context in understanding the twin transition in Southeastern Europe. Full article

Recent discussions on the future of European Union governance highlight a growing emphasis on integrated policy frameworks that align agricultural, territorial, and socio-economic development objectives within unified strategic planning systems. One of the proposed innovations for the next EU programming period is the introduction of National and Regional Partnership Plans (NRPPs), which aim to coordinate several EU funding instruments within a single national planning framework. This article explores stakeholder perspectives on the development of integrated policy planning in this context. The analysis is guided by analytical propositions derived from the literature on policy integration and multi-level governance, focusing on how stakeholder interpretations influence strategic priority alignment, perceived policy trade-offs, and governance coordination capacity. The study is based on a qualitative focus group discussion involving policy stakeholders, researchers, and institutional representatives in Lithuania. Using thematic analysis, the study examines how stakeholders interpret integrated planning concepts, identify strategic priorities, and assess governance challenges associated with policy integration. The findings reveal three key issues shaping stakeholder perspectives. First, conceptual ambiguity surrounding strategic priorities such as competitiveness, regional vitality, and sustainability may complicate policy coordination. Second, perceived conflicts between economic competitiveness and environmental sustainability may be less pronounced than often assumed. Third, the implementation of integrated policy frameworks requires stronger governance capacity, including improved cross-ministerial coordination and shared monitoring systems. The article contributes to research on policy integration and multi-level governance by providing empirical evidence on how policy actors interpret integrated strategic planning frameworks and how these interpretations shape perceptions of governance capacity, policy trade-offs, and stakeholder participation in EU funding reforms. Full article