Search Results (391)

The Sumapaz páramo, the most extensive continuous páramo complex on a global scale and a strategic component in the hydrological regulation of central Colombia, is undergoing a progressive ecohydrological degradation whose integrated characterization through multitemporal biophysical indicators remains limited. To address this gap, the present study examines the transformation dynamics of the system by articulating four analytical components: precipitation modeling based on IDEAM stations (1995–2025), thermal trend analysis from WorldClim grids (2000–2024), multitemporal spectral analysis of four normalized difference indices (NDVI, NDWI, NDSI, NBR) derived from Landsat imagery (2000–2025), and Corine Land Cover cartography (2000–2018). The findings reveal a spatial decoupling between the precipitation distribution, which tends to shift toward lower altitudinal belts, and the storage areas in peat and Andosols of the páramo core, with a consequent reduction in effective recharge regardless of the total precipitated volume. Paradoxically, an almost complete contraction of surfaces with a positive water signal coexists with the expansion of photosynthetic activity, a phenomenon attributable to processes of shrub encroachment, thermophilization, and nutrient enrichment rather than to a functional recovery of the ecosystem. The cartographic analysis, in turn, confirms the advance of agricultural and livestock uses over native regulating covers. The convergence of these vectors configures a multivectorial degradation scenario that escapes monitoring based on a single index and that demands management strategies oriented simultaneously toward anthropic pressure, the spatial redistribution of precipitation, and the implementation of integrated ecohydrological surveillance systems. Full article

Land Use and Land Cover (LULC) change is widely acknowledged as a pivotal driver of environmental change, exerting an escalating influence on surface hydrological processes. The accelerating pace of LULC alterations in response to burgeoning human populations underscores the pressing need for a comprehensive evaluation of their ramifications on surface runoff dynamics. This study investigates the impacts of LULC changes on flood behavior in a Mediterranean watershed in Crete, Greece (Geropotamos watershed). LULC data spanning the years 1990, 2006, and 2018 were procured from the European CORINE Land Cover database at a refined spatial resolution. The HEC-HMS hydrological model is employed to simulate peak discharge and associated hydrograph characteristics under varying recurrence intervals. Subsequently, selected river segments within the studied catchments undergo hydrodynamic flood modelling using the HEC-RAS hydraulic model. Flood depth maps are generated to illustrate the evolution of inundated areas relative to LULC change. The overarching objective of this research is to furnish a comprehensive understanding of how spatiotemporal variations in land use and land cover in-fluence flood characteristics, thereby facilitating informed decision making for sustainable planning. Full article

French coastal systems are characterized by strong environmental gradients and increasing anthropogenic pressures, resulting in rapid land cover transformations across coastal landscapes. This study investigates land cover dynamics along the northern, western, and southern French coasts using Sentinel-2 summer image time series acquired between 2015 and 2025. The research aims to identify the most dynamic coastal regions and determine where land cover transitions are most pronounced. A harmonized workflow was developed in GRASS GIS for preprocessing Sentinel imagery, generating seasonal composites, classifying land cover using a Random Forest (RF) supervised algorithm, and detecting changes through time. All imagery was processed using CORINE Land Cover (Level 1) classification nomenclature and projected to Lambert-93 (EPSG:2154). Comparative analyses were performed among the three coastal regions using statistical indicators of change intensity, persistence, and transition rates. The results reveal substantial regional differences in coastal dynamics, with the southern Mediterranean coast exhibiting the highest transformation rate (22.9% of total area changed, at 2.29% ${\mathrm{yr}}^{-1}$), followed by the northern English Channel coast (18.6%; 1.86% ${\mathrm{yr}}^{-1}$) and the western Atlantic coast (14.2%; 1.42% ${\mathrm{yr}}^{-1}$). Urbanization and natural vegetation loss were identified as dominant transition types across all regions. The study demonstrates the effectiveness of Sentinel-2 time series and open-source GRASS GIS methods for long-term coastal monitoring and provides a reproducible framework for large-scale assessments of coastal land cover dynamics in Europe. Full article

Background: The COVID-19 pandemic exposed critical gaps in pandemic preparedness and highlighted the need for vaccine platforms capable of rapid adaptation. Outer membrane vesicle (OMV)-based platforms utilizing vesicles derived from genetically detoxified Neisseria meningitidis serogroup B (Nm-nOMV) represent a promising plug-and-play approach. Methods: This Phase I, first-in-human, randomized, double-blind, placebo- and OMV-controlled trial, evaluated safety, tolerability, and immunogenicity of intranasally administered OMVs combined with SARS-CoV-2 Spike protein in healthy SARS-CoV-2 seropositive adults aged 18–55 years. Forty participants were enrolled across two cohorts: a low-dose cohort receiving 140 μg OMV/70 μg Spike (OMV + Spike, n = 13; OMV alone, n= 3; Placebo, n = 5) and a high-dose cohort receiving 280 μg of OMV/140 μg of Spike (OMV + Spike, n = 13; OMV alone, n = 3; Placebo, n = 3), administered on Days 1 and 22. Safety was assessed through adverse events, vital signs, laboratory parameters, ECG, and pulse oximetry. Immunogenicity was evaluated via systemic SARS-CoV-2 neutralizing antibodies, antigen-specific antibodies (IgG and IgA), and mucosal antibodies (IgA in nasal wash). Results: Intranasal administration of OMVs combined with SARS-CoV-2 Spike protein was safe, well-tolerated, and immunogenic. No serious adverse events were reported, and adverse events were predominantly mild and transient. Dose-dependent increases in systemic and mucosal immune responses were observed, with statistically significant enhanced serum IgG and nasal wash IgA antibodies in the high-dose group. Conclusions: The current clinical data confirm key aspects of the preclinical profile, which demonstrate the potential of the Nm-nOMV platform as a strong adjuvant for mucosal vaccines. These findings support the broader application of the Nm-nOMV vaccine platform in pandemic preparedness. Full article

This paper focuses on the analysis of long-term land surface temperature (LST) dynamics and land-use changes in the city of Košice, Slovakia, during the period 1985–2025. The analysis is based on multi-temporal Landsat satellite imagery processed within a geographic information system (GIS) environment. Non-parametric statistical methods, including the Mann–Kendall trend test and the Theil–Sen slope estimator, were applied at the pixel level to identify the direction, magnitude, and statistical significance of long-term trends. Land-use changes were evaluated using CORINE Land Cover data together with the NDVI and NDBI spectral indices. The results revealed a statistically significant increase in land surface temperature across almost the entire urban area, with the mean LST increasing by 5.83 °C between 1985 and 2025. The analysis also confirmed a strong positive correlation between built-up areas and LST values, whereas vegetation cover exhibited a significant cooling effect represented by a strong negative correlation with surface temperature. Spatial analysis identified pronounced warming hotspots concentrated mainly in industrial and newly urbanized areas, while vegetation-stabilized zones showed lower warming intensity or localized cooling trends. The findings highlight the dominant influence of urbanization processes on the city’s thermal regime and emphasize the importance of urban vegetation as a key adaptation element for mitigating the surface urban heat island effect. The study also illustrates the added value of integrating remote sensing data, GIS tools, and pixel-based trend analysis in the assessment of long-term changes in the urban thermal environment of medium-sized Central European cities. The results provide a spatial basis for climate adaptation planning and future assessments of urban thermal comfort and environmental quality. Full article

This study investigates the spatiotemporal dynamics of peri-urban expansion and land use transformation in Izmir, Türkiye, over 36 years (1986–2022) using an integrated GIS-based Multi-Criteria Decision Analysis (MCDA) framework. Multi-source datasets, including Landsat imagery, CORINE land cover (CLC) data, demographic statistics, and spatial variables (slope, transportation proximity, and distance to the city center), were combined to delineate urban, peri-urban, and rural zones. Results reveal a substantial percentage increase in urban areas from 2.8% in 1986 to 10.48% in 2022, corresponding to an expansion of approximately 7.6% (≈908.56 km²). In contrast, agricultural land declined by 5.8%, while forest areas experienced a more severe reduction of 19.1%, indicating significant environmental degradation. Population dynamics further support this transformation, with peri-urban districts exhibiting growth rates exceeding the metropolitan core average of 1.8% (1986–2010), followed by a relative slowdown to 0.5% after 2010, accompanied by outward migration-driven expansion. Spatial analysis demonstrates that peri-urban growth is strongly influenced by accessibility and topography, with development concentrated within 30–50 km of the city center and along major transportation corridors (500–1000 m buffers). Land Surface Temperature (LST) analysis indicates increasing urban heat island intensity, with surface temperatures ranging from 12 °C to 46 °C, particularly in densely built inner peri-urban zones. The MCDA-based classification identifies distinct inner and outer peri-urban belts, characterized by contrasting density, land use patterns, and environmental pressures. Overall, the findings highlight that Izmir’s peri-urbanization is a heterogeneous and rapidly evolving process driven by demographic, spatial, and policy-related factors. The study provides a replicable methodological framework and emphasizes the urgent need for integrated, sustainability-oriented planning strategies to mitigate ecological loss and uncontrolled urban sprawl. Full article

Flooding triggered by intense precipitation is a significant natural hazard affecting Mediterranean regions, where complex terrain, rapid hydrological response and increasing urbanization can amplify flood impacts. This study assesses flood susceptibility in two representative Mediterranean River catchments: the Koiliaris in Crete, Greece, and the Pediaios in Cyprus. A compact Flood Hazard Index (FHI) was developed by integrating the Topographic Wetness Index (TWI), Curve Number (CN), and R20 heavy rain frequency index, representing the principal geomorphological, hydrological and climatological controls of flood generation. Spatial datasets including EU-DEM elevation data, CORINE land cover, European soil databases, and Copernicus CERRA precipitation reanalysis were combined within a GIS-based multi-criteria framework using Analytic Hierarchy Process weighting. The resulting FHI maps identify high flood susceptibility along river corridors, low-lying accumulation zones, and urbanized areas. In the Koiliaris basin, 34% of the area fell within the high and very high susceptibility classes, mainly in downstream alluvial zones, whereas in the Pediaios basin, 29% of the area fell within the high and very high susceptibility classes, concentrated around the urbanized Nicosia corridor. The analysis of historical flood events provided a qualitative consistency assessment of the FHI patterns, acknowledging that the absence of spatially explicit flood-inundation footprints limits quantitative validation. Full article

Efficient hydrological-hydraulic analysis requires rapid, reproducible preparation of key GIS inputs. This paper presents two ArcGIS Pro-embedded Python tools that consolidate preprocessing into parameterized, single-run workflows. WATDYN derives hydrologically conditioned flow fields from a DEM and outputs sub-watershed polygons, a vector drainage network, and outlet/junction points. MRET generates a spatial Manning’s roughness coefficient (n) layer by mapping CORINE Land Cover 2018 classes to the literature-based values, producing a model-ready roughness raster with optional tabular export. In the Thessaly water district (EL08), Greece (813.71 km²), WATDYN produced 3249 stream/accumulation polylines and ~3100 sub-watersheds (threshold 5000) in ~2 min, while MRET generated the corresponding n raster in ~1 min. Full article

Climate change is progressively altering the thermal environment of European agriculture, with direct consequences for high-value perennial crops such as olive (Olea europaea L.) and grapevine (Vitis vinifera L.). Although the Growing Degree Days (GDD) index is widely applied to characterize crop thermal requirements, no systematic evidence exists on the actual GDD values accumulated at the locations where these crops are currently grown across Europe. This study introduces a “reverse agroclimatology” approach that anchors GDD calculations exclusively to olive grove and vineyard areas identified in the Corine Land Cover (CLC) dataset for five reference years (1990, 2000, 2006, 2012, and 2018), using ERA5-Land reanalysis daily temperature data as the climatological input. For each CLC reference year, GDD was computed for olive cultivation (T_base = 7 °C, January–May) and viticulture (T_base = 10 °C, April–October) exclusively over registered cultivation pixels, and per-country means were subjected to linear regression trend analysis (p < 0.05). For olive cultivation across 11 Mediterranean countries, statistically significant positive GDD trends were detected in 7 countries, with long-term (1985–2023) country means ranging from 476.2 GDD in France to 1214.3 in Cyprus, indicating that we can revise the known GDD thresholds. The first appearance of olive cultivation in Slovenia’s 2012 CLC dataset, with a median of 546.5 GDD, provides land use-mapped evidence of a spatial displacement of cultivation boundaries. For vineyard cultivation across 22 European countries, significant positive trends were identified in 18 countries, with warming rates reaching 19.25 GDD yr⁻¹ in Turkey, 15.83 GDD yr⁻¹ in Albania, and 14.89 GDD yr⁻¹ in Bosnia and Herzegovina. Mediterranean and Balkan vineyards already exceed the classical 2000 GDD threshold of viticultural suitability across all reference years. In contrast, central and northern European registered vineyards operate below it, though their warmest sites are increasingly approaching or crossing it in the most recent periods. The cultivation-anchored GDD framework, built on openly available data and a fully reproducible R-based pipeline, provides a practical and updatable tool for monitoring the evolving thermal conditions of European olive and wine production under ongoing climate change. Full article

This article seeks to examine the extent to which the spatial planning of Poland (expressed by coverage of municipalities by Local Spatial Management Plans) reduces uncontrolled land-use changes. In the context of increasing urbanization pressure, spatial planning is theoretically expected to optimize land development and enhance land-use stability. The research tests the hypothesis that a higher share of municipal area covered by Local Spatial Management Plans should be associated with fewer uncontrolled transformations. Land-use changes were identified using CORINE Land Cover (CLC) data, while information on Local Spatial Management Plans coverage was obtained from Statistics Poland. Land-use stability was quantified using the hemeroby index. GIS tools and Multiscale Geographically Weighted Regression were used to assess the relationship between Local Spatial Management Plans coverage and changes in the hemeroby index, as well as to examine the spatial variability of this relationship across municipalities. The results indicate that the influence of Local Spatial Management Plans coverage on land-use stability is spatially differentiated. In some regions, higher planning coverage corresponds with greater landscape stabilization, while in others, planning instruments appear insufficient to counteract urbanization pressures. The findings provide an empirical verification of land management effectiveness in Poland and highlight regional disparities in the capacity of spatial planning to mitigate uncontrolled land-use change. Full article

Mountain ecosystems are highly sensitive to climate change and require spatially explicit monitoring tools to support adaptive management. Within the framework of the Interreg-ALCOTRA “ACLIMO” project, this study investigates land cover dynamics in the Gesso Valley (Maritime Alps, Italy) over the period 2010–2021 using deep learning–based classification of high-resolution aerial orthophotos integrated with climate data analysis. Multi-temporal RGB and NIR imagery (2010, 2018, 2021) was classified using convolutional neural networks (U-Net and MMSegmentation) in ArcGIS Pro, with CORINE Land Cover datasets used for training. The best-performing model, based on CLC + Backbone 2018, achieved an overall accuracy of 82%, increasing to 87% after fine-tuning. Change detection revealed a general shift towards increased vegetation cover, while climate analysis based on regional weather stations (1990–2021) identified a warming trend of +0.4 °C/decade and recent drier conditions. Logistic regression highlighted significant associations between land cover transitions and climate anomalies, with temperature positively influencing change probability (OR = 1.40). The study demonstrates the potential of operational GIS-integrated deep learning workflows for climate change monitoring in complex alpine environments under real-world data constraints. Full article

In the Rhône-Mediterranean-Corsica (RMC) basin (130,000 km², 14 million inhabitants), groundwater intended for human consumption has been monitored for decades. These data, stored in the SISE-EAUX database, were cross-referenced with information from the CORINE Land Cover (CLC) database, which describes human land use, in order to identify potential relationships between pollutant pressure and water quality at the basin scale, as well as the mechanisms specific to each geographical area. Data processing was carried out in three stages. The 27,741 water samples from 2825 abstraction points were assigned to the 224 groundwater bodies (GWBs), and average values for each physicochemical and bacteriological parameter were calculated for each GWB. At the same time, the percentage of surface area covered by each land use type was also extracted at the scale of each GWB. This information was subjected to statistical processing, first separately and then jointly, using principal component analysis (PCA) and hierarchical clustering of parameters. A redundancy in the information carried by the quality parameters, previously observed at the scale of administrative regions (four to five times smaller), is confirmed at this new analysis scale, paving the way for data consolidation and a more synthetic representation. Fecal contamination primarily concerns areas with crystalline lithology and, secondarily, a few karst sectors, with other livestock farming regions being less contaminated. Higher nitrate concentrations are observed in cereal-growing regions and areas of intensive row cropping, while metal concentrations are lower in the drier Mediterranean climate zone than under the more humid continental climate. Structuring factors, notably altitude and climate, emerge at the RMC basin analysis scale, which was not the case at the scale of administrative regions. These structuring factors influence land use, soil type, and hydrological regimes alike, which explains the correlations between the information contained in the CLC and SISE-EAUX databases. 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

Soil erosion assessment in Southeast Europe’s mountainous regions often lacks systematic field validation, limiting confidence in model-based predictions. This study integrates the Erosion Potential Model (EPM) with remote sensing and field verification across 26,570 km² in the Federation of Bosnia and Herzegovina (FBiH) and Brčko District (BD). We developed a two-stage framework: initial GIS-based assessment using digital elevation models, soil maps, climate data, CORINE Land Cover, and Landsat imagery, followed by field calibration at 190 representative sites. Spectral indices (NDVI, BSI) provided dynamic corrections for vegetation cover and visible erosion features. Field validation significantly improved model performance; the erosion coefficient increased from Z = 0.21 to Z = 0.24, while discriminatory power improved AUC from 0.82 to 0.85, with corresponding gains in overall accuracy from 0.78 to 0.84 and F1-score from 0.78 to 0.85. The field-validated model estimated mean annual sediment production of 546.60 m³·km⁻²·year⁻¹, with total erosion material production of 14,074,940.2 m³·year⁻¹. Field calibration revealed substantial spatial redistribution, with medium-to-excessive erosion categories expanding by 30.37%, affecting 1319.12 km² requiring priority intervention. The Kappa coefficient (0.81) confirms high classification reliability. This field-validated framework enables evidence-based identification of degradation hotspots and provides actionable guidance for soil conservation planning in geomorphologically heterogeneous, data-limited regions. Full article

Urban districts along major rivers are undergoing rapid transformation, yet long-term evidence on how redevelopment reshapes land cover and vegetation structure remains limited in post-socialist cities. This study examines the spatio-temporal evolution of land use and land cover (LULC) and vegetation dynamics along the Sava River corridor in Belgrade from 1990 to 2024. CORINE Land Cover (CLC) datasets were combined with Landsat-derived NDVI and MSAVI time series, while high-resolution Esri Wayback imagery was used for visual interpretation and qualitative corroboration of the detected land-cover and vegetation patterns. Beyond conventional NDVI/LULC assessments, the study integrates multi-decadal spectral trends with functional vegetation structure classification to evaluate canopy continuity and ecological configuration under contrasting redevelopment models. Results reveal a pronounced divergence between the two riverbanks. The left bank (New Belgrade) maintains stable land-cover composition and consistently higher NDVI and MSAVI values, indicating preserved green infrastructure and sustained canopy continuity. In contrast, the right bank (Belgrade Waterfront) experienced substantial land-cover conversion after 2006, with a statistically significant decline in vegetation greenness (NDVI −0.020 dec⁻¹, p < 0.001) and a marked increase in impervious surfaces. MSAVI-based functional classes indicate a shift from mixed low vegetation to predominantly sealed land, while tree canopy remained persistently low throughout redevelopment. The findings demonstrate measurable ecological simplification and canopy loss, even where nominal green areas remain present. By providing a rare multi-decadal, spatially explicit comparison of two contrasting planning paradigms within the same river corridor, the study contributes new empirical evidence on how governance and redevelopment models shape riparian ecological trajectories and sustainable urbanism in post-socialist cities. Strengthening blue-green infrastructure and restoring native riparian vegetation are essential for enhancing climate resilience and ensuring long-term riverfront sustainability. Full article