Search Results (231)

Accurate land cover mapping is a fundamental tool for environmental management and ecosystem monitoring. This study presents a comparative evaluation of four deep learning architectures, namely a Convolutional Neural Network (CNN), UNet++, ConvNeXt and Vision Transformer (ViT), for land cover classification into five primary classes: water, cropland, forest, low/natural vegetation and built-up. The broader Lake Kerkini basin was selected as the primary training and evaluation area. The multispectral input data were generated through Google Earth Engine and consisted of multi-seasonal Sentinel-2 composite mosaics for the 2021 mapping year, covering winter, spring, summer and autumn. To obtain a more reliable performance estimate and mitigate the effects of spatial autocorrelation, a four-fold spatial cross-validation approach was implemented. Under this spatial validation framework, the convolution-based architectures achieved the strongest performance. CNN obtained the highest numerical fold-mean performance, with an overall accuracy of 81.53% and a macro-averaged F1 score (Macro-F1) of 80.09%, followed closely by UNet++ and ConvNeXt. Non-parametric repeated-measures statistical testing indicated a significant overall architecture effect, with CNN, UNet++ and ConvNeXt showing broadly comparable fold-level Macro-F1 performance, while the tested ViT configuration trained from scratch ranked last across all spatial folds. Regional transferability was further evaluated in the nearby independent Lake Doirani region, where the convolutional architectures, particularly CNN and UNet++, showed strong agreement with the WorldCover-derived reference labels without fine-tuning. Finally, feature-importance analysis indicated that specific spectral-seasonal channels, especially the Blue band (B2) in winter and the Short-Wave Infrared band (B12) in summer, were consistently influential in the models’ predictions. Overall, under the tested 2021 Mediterranean case-study conditions, the results highlight the importance of spatially rigorous validation and show that the evaluated convolution-based configurations achieved stronger performance than the tested ViT configuration trained from scratch. Full article

Flowering time is a key adaptive trait in common vetch (Vicia sativa L.), influencing crop adaptation, yield potential, and forage quality. Despite its importance, the genetic basis of flowering in this species remains poorly understood. In this study, we analyzed the genetic architecture of flowering-related traits in an F_2:3 population under field conditions over two consecutive growing seasons. Four traits were evaluated using thermal time expressed as growing degree days (GDDs), and quantitative trait loci (QTL) analysis was conducted using a high-density genetic map derived from DArTSeq markers. The linkage map comprised 419 unique positions across six linkage groups, spanning 1728.5 cM. Ten QTLs associated with flowering traits were identified on chromosomes 2, 3, 4, and 6. Five QTLs were consistent across seasons, defining three major genomic regions controlling flowering. Additional season-specific QTLs suggested environmental effects on flowering responses. In silico analysis identified three candidate genes (VsFTc, VsFTa, and VsLFY) within flanking markers for stable QTL. This is the first report of QTLs for flowering in common vetch and provides targets for marker-assisted breeding to improve adaptation and resilience. Full article

Improving the energy performance of historical buildings is a key challenge for decarbonising the European built environment. In the Mediterranean context, retrofit design is especially complex because interventions must reduce heating and cooling demand while preserving architectural and cultural values. Although research on this topic has grown, available evidence remains fragmented, with studies often focused on individual case studies and isolated retrofit packages. This review systematises the literature on energy retrofit interventions for historical buildings in the European Mediterranean region by linking retrofit measures, energy outcomes and conservation constraints. A PRISMA-based workflow was used to select articles published between 2010 and 2025 from Scopus and Web of Science. The results show a predominance of envelope-based measures, often combined with HVAC improvements. Passive–active packages achieve the highest reported reductions, up to 87% for heating and 75% for cooling. Conservation constraints do not necessarily prevent energy improvement, but they influence the admissibility, location and invasiveness of retrofit measures. Overall, the evidence indicates that energy retrofit of Mediterranean historical buildings should focus on heating reduction, cooling resilience and hygrothermal safety. The review provides a framework for identifying compatible retrofit pathways according to the architectural and material transformability of historical buildings. Full article

Residential buildings have been responsible for the increasing percentage of final energy consumption in Libya, which is mainly due to the cooling of buildings in hot arid climatic conditions, but there is still a constant discrepancy between the projected and actual energy performance. This review critically synthesises the available literature to find out the knowledge gaps underlying residential energy overconsumption, and it concentrates on the systemic loss of contact between the architectural design intent, material and envelope performance, construction execution, and occupant behaviour throughout the building lifecycle. The literature employed to complete the study is peer-reviewed journals, conference papers, and technical reports concerning Libya and similar hot-arid and Mediterranean settings, which are arranged into four overlapping areas, namely, design practices, materials and construction quality, regulatory enforcement, and occupant energy use patterns. The results show that the cumulative and reinforcing inefficiencies are caused by the lack of adoption of climate-sensitive designs, inattentive view of thermal material properties, ineffective control over the quality of construction, ineffective regulation enforcement, and neglect of the occupant behaviour in performance analysis, which contribute to the increase in cooling loads and expansion of the performance gap. Building a coherent conceptual structure using disjointed evidence, the review offers recommendations that can be applied in practice by architects, engineers, policymakers and housing stakeholders, highlighting the importance of lifecycle-based design methodologies, improved governance and performance energy strategies with behavioural elements in Libyan residential buildings. Full article

In this study, daily reference evapotranspiration (ET₀) values for the period 2025–2030 for Lake Burdur, located in the Mediterranean climate zone and within the Burdur closed basin, were estimated using nested architecture focused on high accuracy. The ET₀ target corresponds to the FAO-56 Penman–Monteith reference evapotranspiration variable provided by the Open-Meteo Historical Weather API, and it is treated throughout as a standardized measure of atmospheric evaporative demand rather than as actual lake-surface evaporation or basin water loss. For this purpose, daily mean air temperature, relative humidity, shortwave surface radiation, and evapotranspiration data for the period 1984–2024 were obtained from the Open-Meteo platform. In the first stage of the study (Model 1), separate SARIMAX (statistical), XGBoost (machine learning), and LSTM (deep learning) models were applied for temperature, relative humidity, and radiation series; the model with the highest validation mean for each variable was selected. Accordingly, LSTM (Mean $R^2$ = 0.967) was determined to be the most successful model for temperature, SARIMA(X) (Mean $R^2$ = 0.812) for relative humidity, and XGBoost (Mean $R^2$ = 0.845) for the radiation variable, which is non-linear, has strong autocorrelation, and exhibits distinct seasonality. In the second stage (Model 2), these best climate predictions were used as independent variables for evapotranspiration, and LSTM provided the highest success for evapotranspiration (Mean $R^2$ = 0.941). Trend analyses revealed that the increase in temperature and evapotranspiration and the decrease in relative humidity observed in the past period will continue in the near future. The uncertainty analysis conducted using the Monte Carlo/resampling approach on historical data showed that the 95% prediction intervals largely protected the upward trend in evapotranspiration against random fluctuations. These intervals reflect residual-based uncertainty under the fitted model rather than the full predictive uncertainty of future basin evapotranspiration. The findings indicate that designing model selection appropriate to the structure of the variables within a nested prediction framework significantly improves forecast accuracy and can provide a viable decision support input for sustainable water management in Mediterranean basins experiencing water scarcity. Full article

Wildfires are a growing threat in Mediterranean regions where climate variability and land-use practices increase vulnerability to fire risk. Developing effective prediction models is essential for robust wildfire management, particularly in such data-scarce environments. Focusing on data-scarce Mediterranean environments, with reference to environmental conditions observed in Morocco, this review presents prediction models across three methodological categories: spatial risk mapping, temporal forecasting, and fire spread simulation, alongside the satellite data products that support their deployment. Each category is assessed in terms of predictive performance, data requirements, and adaptability to low-resource environments. XGBoost showed strong applicability in data-scarce Mediterranean contexts, while ARIMA was validated for forecasting fire-relevant time series under limited data resources. Freely accessible MODIS-derived products represent a significant asset to the region. Based on this synthesis, a hybrid XGBoost-ARIMA framework incorporating MODIS-derived inputs and SHAP-based interpretability is proposed as a promising candidate architecture to be validated after further investigation. The findings aim to support researchers, land managers, and policymakers in strengthening local wildfire prevention and mitigation efforts by aligning model capabilities with regional data and environmental constraints. Full article

The climate crisis, housing precarity, and the loss of everyday architectural heritage are converging challenges in Mediterranean cities. This article investigates the adaptive reuse of early twentieth-century adobe refugee dwellings in Nea Ionia and Kaisariani, neighborhoods of Attica, Greece, as an integrated social, environmental, and cultural strategy. Historical documentation, urban-morphological analysis, field observations, building survey data, material assessment, and design-based microclimatic analysis were combined to evaluate compatible restoration and bioclimatic upgrades as alternatives to demolition and conventional energy retrofit practices, with the main aim of preserving an important part of Greek history and architecture. The study develops a replicable qualitative assessment framework that identifies how existing adobe envelopes, compact layouts, courtyards, thresholds, vegetated pergolas, and low-water evaporative cooling may support low-carbon housing reuse. The results clarify the current preservation conditions and reuse potential of the selected case-study fragments, showing that adobe dwellings can preserve embodied material value, retain thermal mass and hygroscopic regulation, and support social housing when repaired with compatible, low-impact techniques. The article argues that the reuse of adobe refugee dwellings can function as a distributed urban strategy for housing provision, heritage continuity, and microclimatic adaptation. Its main contribution is a transferable analytical framework for assessing overlooked earthen housing stocks in dense Mediterranean contexts. The study argues that adaptive reuse can serve simultaneously as a means of social housing, a mechanism for optimizing the microclimate, and a means of preserving the tangible and intangible heritage of Greek adobe buildings that have been standing for over 100 years. This position extends circular construction debates by prioritizing non-demolition and direct reuse while preserving an important period of history. Full article

This study evaluates the performance of LiDAR sensing and UAV photogrammetry for three-dimensional canopy reconstruction and structural parameter estimation in precision agriculture under Mediterranean conditions. Experiments were conducted in Sicily, Italy, on Moringa oleifera Lam. and Ficus macrophylla subsp. columnaris, representing contrasting canopy architectures. LiDAR and UAV photogrammetric data were used to generate canopy models and estimate canopy height, canopy volume, and vegetation density distribution. A voxel-based approach was applied to LiDAR-derived point clouds to quantify internal canopy structure and vegetation density within the canopy volume. Accuracy was assessed by comparing remote sensing-derived canopy metrics with ground-truth field measurements. LiDAR outperformed UAV photogrammetry in canopy height estimation, achieving lower RMSE values than UAV-derived models (0.19–0.21 m vs. 0.52–0.60 m), corresponding to an approximate error reduction of 60–65%. LiDAR also provided more accurate canopy volume estimation, with lower relative errors than UAV photogrammetry (3.5–4.2% vs. 13.7–16.1%). The voxel-based LiDAR approach enabled the quantification of vegetation density distribution within the canopy volume, showing higher sensitivity to internal canopy layers compared with UAV photogrammetry, particularly in the structurally complex Ficus macrophylla canopy. UAV photogrammetry provided reliable estimates of the external canopy surface but underestimated structural parameters in dense vegetation due to canopy occlusion and limited penetration into inner canopy layers. Differences between the two methods were more pronounced in Ficus macrophylla than in Moringa oleifera, confirming the strong influence of canopy complexity on sensing performance. These findings demonstrate that LiDAR-derived structural and voxel-based metrics can improve canopy characterization and support precision agriculture applications such as biomass estimation, irrigation planning, yield prediction, and canopy management in Mediterranean cropping systems. Full article

Small Mediterranean coastal lagoons are sensitive sedimentary environments where basin morphology, hydrodynamic processes, and inherited coastal structures interact to control sediment dispersal. This study investigates modern sedimentary patterns in Lake Porto Vecchio, a shallow coastal brackish pond within the Oliveri–Tindari lagoon system (NE Sicily, Italy), by integrating grain-size statistical and petrographic analyses, and morpho-bathymetric data. A total of 115 surface sediment samples were collected from the coastal pond’s shallow bottom, shoreline, adjacent beach, and shallow marine sector. Grain-size distributions were analyzed using mechanical sieving and laser diffraction, and textural parameters were calculated following Folk and Ward’s formula. Results reveal a well-defined spatial organization of siliciclastic sediments characterized by a grain-size gradient from gravelly coarse-grained sands along the shallow marginal platform to fine-grained sands and silts toward the deeper central basin. This pattern reflects a progressive decrease in hydrodynamic energy from the lagoon margins toward the basin depocenter. A partially lithified beachrock belt forms a shallow platform controlling sedimentation, trapping coarse sediments along the margins while promoting the accumulation of finer fractions in the inner basin. Grain-size discrimination diagrams further distinguish lagoonal sediments from adjacent marine deposits, highlighting the effectiveness of classical statistical approaches in reconstructing modern sedimentary processes. These results support a conceptual model in which inherited beachrock platforms act as key morphological control on sediment architecture in microtidal coastal lakes. Lake Porto Vecchio, therefore, represents a useful modern analog for interpreting similar lagoonal deposits preserved in the Quaternary sedimentary record. Full article

Although livestock buildings constitute a widespread and structurally significant component of the rural landscape, they are, in most cases, characterised by construction configurations primarily driven by production requirements. Such an approach rarely results from a conscious design process capable of integrating architectural criteria with the environmental context in which these structures are embedded. Within this framework, the prevailing construction model—based on prefabricated steel systems and sandwich panels—prioritises rapid execution, standardisation, and cost efficiency, while relegating aspects such as environmental quality, material circularity, and landscape integration to a marginal role. Against this background, the present study investigates the possibility of redefining this paradigm through a technological substitution grounded in the principles of bio-based construction, technological design, and circular economy. To this end, a timber-based architectural solution for poultry houses is developed and adopted as an experimental case study to assess environmental and economic performance through an integrated methodology combining Life Cycle Assessment (LCA) and Construction Cost Analysis. The evaluation is conducted comparatively against a conventional steel-based system, maintaining consistent geometric and functional parameters, within the climatic context of the Italian Mediterranean and in accordance with EN 15978 and EN 15804+A2 standards, over a 30-year reference period. The results indicate a significant reduction in environmental impacts for the timber-based solution, with a decrease in Global Warming Potential of approximately 29%, reaching values close to 50% when accounting for biogenic carbon storage. From an economic perspective, the alternative solution entails an increase in initial costs of approximately 20%, primarily associated with the adoption of a high-performance building envelope. Overall, the study demonstrates how architectural technological design, when supported by quantitative assessment tools, can operate as an effective driver for the ecological transition of rural productive landscapes. Full article

Background/Objectives: Accurate post-mortem interval (PMI) estimation becomes increasingly difficult when bodies decompose under extreme heat. Hyperthermal Mediterranean environments accelerate soft-tissue degradation, induce early mummification, and distort classical thanatological indicators, often resulting in substantial PMI overestimation. This study analyzes three forensic cases affected by climate-driven decomposition anomalies and presents a climate-adaptive, AI-assisted diagnostic framework applied uniformly across all cases to improve PMI interpretation. Methods: A retrospective case series analysis was conducted on three individuals recovered during summer heatwaves. Crime scene investigation, post-mortem computed tomography (PMCT), autopsy, and genetic identification were integrated with 5–15-year meteorological datasets. Classical PMI estimations were compared with circumstantial data. A multimodal AI model, incorporating environmental features, decomposition morphology, and microenvironmental modifiers, was operationalized for each case using a hybrid Random Forest–LSTM architecture. Engineered indices included Accumulated Degree Days (ADD), a Decomposition Index, and climate-stress metrics (Thermal Load Index, Desiccation Pressure Factor, Microenvironmental Distortion Coefficient). Quantile regression provided calibrated prediction intervals. Results: Morphological assessments overestimated PMI in every case, suggesting intervals of 1–6 months despite true PMIs of approximately 20 days (Cases 1–2) or 36–48 h (Case 3). The AI model yielded conceptual outputs more consistent with verified PMIs, ~21 days (Case 1), ~23 days (Case 2), and ~42 h (Case 3), each accompanied by 50% and 90% prediction intervals. Explainability analyses identified thermal load, desiccation pressure, and microenvironmental distortion, particularly insulation in Case 3, as dominant drivers. Conclusions: Extreme heat fundamentally alters decomposition trajectories, rendering classical PMI methods unreliable. Applying a climate-aware, AI-assisted diagnostic framework across all three cases improved interpretability, providing uncertainty-aware estimates aligned with true PMIs. The AI framework is presented as a conceptual, non-trained, proof-of-concept system, and reported outputs represent operational demonstrations rather than validated predictions, offering a promising foundation for next-generation PMI diagnostics in hyperthermal forensic settings. Full article

Climate warming in Mediterranean vineyards accelerates grape ripening and increases the incidence of sunburn and berry shriveling, leading to imbalances in grape composition and wine quality. This study evaluated the combined effects of a non-positioned training system (asymmetric sprawl) and foliar application of kaolin particle film on vine microclimate, agronomic performance and wine aroma profile in a Syrah cv. vineyard under warm conditions. Vine canopy temperature was monitored by UAV thermography at veraison and harvest, while grape damage, yield components and vegetative balance were assessed at harvest. Wines obtained from each treatment were analysed for chemical composition, volatile compounds and sensory attributes. Kaolin application significantly reduced canopy temperature, particularly under water-limited conditions at veraison (up to 1.9 °C), and the combination with sprawl training decreased the proportion of sunburnt and shrivelled clusters. These microclimatic modifications were associated with higher ethanol content, improved colour intensity and increased total polyphenol index in wines. The combined strategy also enhanced the concentration of key aroma compounds, especially terpenes and fruity esters, resulting in higher values of citrus, floral and fruity aromatic series. Sensory evaluation confirmed a better overall appreciation of wines produced from vines managed with both practices. Overall, the integration of canopy architecture modification and reflective particle film represents an effective strategy to mitigate heat stress effects in warm viticultural regions, improving grape physiological performance and contributing to the preservation of wine aromatic quality under climate change scenarios. Full article

Traditional food systems have historically sustained nutrient adequacy under conditions of environmental variability and limited food diversity, yet their underlying nutritional mechanisms remain insufficiently integrated into contemporary nutrition science. This article attempts to provide a conceptual synthesis of how traditional dietary practices may function as informal nutrient optimization strategies. Drawing on evidence from nutrition science, food chemistry, and human physiology, it examines how food processing techniques (e.g., fermentation, soaking, germination, and thermal treatment), food pairing, and structural properties of foods influence nutrient bioavailability, absorption, and metabolic responses. Across diverse dietary contexts—including Mediterranean, agrarian cereal–legume, and East Asian-type patterns—recurring mechanisms emerge that can boost mineral solubility, improve protein digestibility and amino acid balance, facilitate vitamin absorption, and modulate glycemic responses. These effects are mediated not only by nutrient content but by interactions within the food structure and at the meal level. The synthesis supports a reframing of traditional diets as functional nutritional architectures in which processing and dietary configuration may enhance nutrient utilization efficiency. From this perspective, nutrient adequacy arises from coordinated structural features rather than from maximal nutrient density alone. The findings can be influential in contemporary nutrition research and policy, highlighting the need to move beyond reductionist intake-based models toward integrated approaches that account for bioavailability, metabolic handling, and dietary context. Several transferable principles of nutrient optimization are proposed, offering a framework for designing nutritionally efficient and resilient diets in modern settings. Full article

One-way joist slab floor systems are commonly favored in modern residential building applications due to their efficiency in architectural and structural design processes. However, a significant number of such buildings experienced heavy damage or collapse mechanisms during the catastrophic earthquakes in Türkiye since they are more vulnerable due to some uncertainties in the design and construction stages. In this regard, although well-known seismic codes such as Eurocode, IBC, and ASCE do not impose additional requirements for the design of structural systems with joist slabs, the seismic codes of some Mediterranean basin countries regulate the ductility levels, use of shear walls, and member/system-based specific requirements. In the present study, the impact of shear wall quantity on the seismic behavior of reinforced concrete buildings with one-way joist slabs was investigated in five-story structural systems, which were basically similar in terms of the slab properties and layout but have different overturning moment ratios (α_M = 0.75, 0.60, 0.45, 0). In this context, a total of 88 bi-directional nonlinear time history analyses were conducted on four structural systems, which were highly representative of buildings in the earthquake zones of Türkiye, under real earthquake ground motions. Hence, the seismic behavior demands—including story displacement, inter-story drift and plastic deformations, distributions of plastic hinges, and member-based performance levels—were discussed by the overturning moment ratio that is directly associated with the shear wall quantity in the system. It can be concluded that when these buildings are jointly designed with the shear walls and frames of a high ductility level—through the capacity design principles—the stipulated performance objective can be successfully achieved. While the shear wall quantities ranging from 0.45 to 0.75 did not have a significant impact on the member-based damage across all floors, the frame-only system was found to be inadequate for controlling the lateral deformations due to insufficient stiffness under design-based seismic events. Full article

Croatia hosts one of the most intensive recreational boating activities in the Mediterranean, with over 134,600 registered vessels along 5835 km of Adriatic coastline. This paper presents an AI-driven simulation framework for evaluating electrification pathways for the Croatian recreational vessel fleet. A key contribution is the explicit treatment of the AIS data gap: recreational vessels in Croatia are not required to carry AIS transponders, so synthetic operational profiles calibrated from manufacturer specifications and verified economic data are used instead. Six machine learning architectures are compared for vessel energy demand forecasting, with a proposed Transformer-based model achieving the best simulated performance. Fleet-weighted Monte Carlo simulation across three electrification scenarios suggests that an AI-optimised hybrid configuration can, subject to use intensity, reduce per-vessel CO₂ emissions by up to 56.8% relative to conventional engines. Techno-economic analysis shows payback periods ranging from over 15 years for low-use private owners to 7–9 years for charter operators, supporting targeted incentive design. The framework is intended to be transferable to other Mediterranean coastal regions facing comparable data and operational constraints. Full article