Search Results (535)

Soil erosion in arid watersheds poses a significant threat to land productivity, water resources, and long-term sustainability, necessitating spatially explicit and data-driven prioritization frameworks for targeted conservation. This study developed an integrated GIS-based multi-criteria decision-making (MCDM) framework to assess soil erosion susceptibility and prioritize twelve sub-basins (SB) of the Wadi Numan basin (683 km²), Makkah Region, Saudi Arabia. Morphometric analysis was conducted using sixteen parameters derived from a 10 m Digital Elevation Model (DEM), and Land Use/Land Cover (LULC) data were obtained from the Esri Sentinel-2 10 m dataset. Four MCDM techniques—additive ratio assessment (ARAS), complex proportional assessment (COPRAS), multi-objective optimization by ratio analysis (MOORA), and technique for order preference by similarity to ideal solution (TOPSIS)—were applied under the criteria importance through inter-criteria correlation (CRITIC) objective weighting, and their consistency was evaluated using the Spearman correlation coefficient test (SCCT) and the Kendall Tau correlation coefficient test (KTCCT). MOORA achieved the highest consistency for morphometric analysis (SCCT: 0.982; KTCCT: 0.958), while TOPSIS performed best for LULC analysis (SCCT: 0.800; KTCCT: 0.731). The final combined prioritization used MOORA for morphometric analysis and TOPSIS for LULC analysis, with proportional weighting of 72.7% and 27.3%, respectively. The scheme categorized the sub-basins into five levels of soil erosion priority. The composite ranking classified SB-9 and SB-1 under very high priority (25.94%); SB-2 and SB-3 under high priority (6.40%); SB-5, SB-6, and SB-10 under medium priority (36.37%); SB-4 and SB-8 under low priority (18.11%); and SB-11, SB-12, and SB-7 under very low priority (13.18%). This integrated method provides a practical decision-support tool for identifying and managing sub-basins susceptible to soil erosion, thereby promoting the long-term sustainability of land and water resources. Full article

Soil quality is central to agricultural sustainability and food security, yet coastal agroecosystems are increasingly threatened by degradation from intensive practices and seawater intrusion. This study aimed to integrate soil quality index (SQI), statistical modeling, machine learning (ML), and decision analysis to assess and manage soil health in the Skhirat coastal plain of Morocco. A total of 30 topsoil samples were collected and analyzed for chemical and nutrient properties. Spatial interpolation revealed strong coast–inland gradients where EC ranged from 0.47 to 6.3 dS/m with the highest salinity in the south-western fringe, while CEC (8.4–39.7 cmol/kg) and OM (0.54–2.81%) peaked inland. Principal component analysis (PCA) explained 65.9% of total variance, with salinity drivers loading negatively against fertility indicators. Redundancy analysis (RDA) biplots highlighted antagonism between salinity and fertility axes. The PCA-minimum data set (MDS)-SQI integrated key indicators and ranged from 0.084 to 0.897 (mean 0.614), classifying 33% of sites as low quality. The ML model linear regression achieved the best performance (R² = 0.907). Multi-criteria decision analysis (MCDA) using TOPSIS and PROMETHEE II prioritized coastal sites with indices up to 0.882, and robust underweight sensitivity (Spearman ρ = 0.992). This integrated framework demonstrates that soil chemical monitoring, AI prediction, and MCDA can jointly deliver robust, site-specific management strategies for vulnerable coastal agroecosystems. 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

Population aging has increased the need for public open spaces that older adults can use safely, comfortably, and confidently. In many urban parks and community squares, however, resting facilities are still designed as standardized street furniture, with cold materials, insufficient hand support, limited wheelchair-inclusive space, and weak support for everyday social interaction. This study examines age-friendly public facilities as micro-scale spatial elements that shape sitting, standing, staying, communication, and willingness to remain in small urban open spaces. Drawing on field observation, behavioral analysis, semi-structured interviews, and a multi-criteria design-evaluation process, the study identifies older adults’ key facility-use needs and translates them into design indicators and alternative facility schemes. The results show that physical support and inclusive spatial use are the most important design priorities. Standing-up assistance, sitting-posture support, perceived structural stability, and age-appropriate dimensional adaptation were more influential than purely decorative or auxiliary functions. Among the three alternative schemes, the modular pergola system performed best because it combined stable hand support, independent seating, an age-friendly interactive table, shaded resting space, wheelchair-inclusive layout, and wood-based sensory comfort. The sensitivity analysis further confirmed that this scheme maintained a stable advantage under most weight-adjustment conditions. The findings suggest that age-friendly public facility design should move beyond the improvement of individual furniture products and instead integrate bodily support, spatial accessibility, social interaction, material comfort, and environmental pattern quality. This study provides a design-decision framework for improving the inclusiveness, accessibility, and health-supportive capacity of urban public open spaces for older adults. Full article

Spatially explicit water-quality information is critical for precision management in pond aquaculture but point sampling alone cannot capture pond-to-pond heterogeneity in multi-unit farms. This single-date, single-farm study re-evaluated the potential of UAV hyperspectral imagery for water-quality screening in inland aquaculture ponds in Shanghai, China, using site-matched extraction from a 138-band orthomosaic (450–998 nm, Cubert S185) acquired during a single UAV survey on 24 August 2023 and matched with 23 GPS-registered sampling sites. Eight water-quality parameters were analyzed: chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), ammonium (${\mathrm{NH}}_4^{+}$ ), nitrite (${\mathrm{NO}}_2^{-}$), nephelometric turbidity unit (NTU), chlorophyll-a (Chla), and total suspended solids (TSS). Raw single-band correlations were modest ($\left|\mathrm{r}\right|$= 0.236–0.417), but two-band difference spectral indices (DSI), normalized spectral indices (NSI), and ratio spectral indices (RSI) substantially improved sensitivity, with $\left|\mathrm{r}\right|$ reaching 0.558–0.928. Quadratic inversion models were calibrated on the full dataset and assessed using three validation layers: two-fold cross-validation, nested leave-one-pond-out (LOPO) validation with within-fold predictor reselection, and extraction-window sensitivity tests. Bootstrap 95% confidence intervals for calibration (Cal) R² characterize small-sample uncertainty (n = 23). Three parameters satisfied all three defensibility criteria (Cal R² > 0.5, CV R² > 0.2, and LOPO R² > 0.2): ${\mathrm{NH}}_4^{+}$ (Cal R² = 0.836 [0.61, 0.94]; LOPO R² = 0.420), COD (0.607 [0.34, 0.82]; 0.328), and NTU (0.862 [0.77, 0.96]; 0.204). TP, TN, ${\mathrm{NO}}_2^{-}$, TSS, and Chla showed overfit behavior under nested holdout and were demoted to exploratory products. A TreeSHAP analysis confirmed that band-to-band contrast carried more explanatory power than raw reflectance magnitude. Extraction-sensitivity tests further demonstrated that positional uncertainty (±2-pixel offset: ΔCV $R^2$= 0.23–0.41) exceeded averaging-window sensitivity (3 × 3→10 × 10: ΔCV $R^2$ ≤ 0.11), identifying geolocation control as the dominant robustness constraint. This single-date, single-farm reanalysis suggests that UAV hyperspectral imagery may support exploratory pond-scale screening of ${\mathrm{NH}}_4^{+}$, COD, and NTU. However, robust quantitative inversion and broader transferability remain unverified and will require denser sampling, improved geolocation control, pond-edge masking, multi-site observations, and multi-temporal calibration. Full article

The rapid development of wind and solar energy necessitates a solution to the problem of the optimal spatial placement of wind farms (WFs) and solar farms (SFs) within electric power systems. The non-stationary generation schedules of WFs and SFs place increased demands on the flexibility of conventional generation, determined by the intensity of net load fluctuations. This paper proposes a methodology for the spatial optimization of WF and SF location, in which the optimization criteria include net load indicators (rate of net load change and net load increment), the base power of the RES system, and the economic criterion of maximum electricity generation. Unlike existing approaches, in which the geographical smoothing effect on power fluctuations is treated as an incidental outcome, the proposed methodology employs it as an explicit optimization criterion for RES placement. The algorithm provides for the preliminary ranking of candidate sites based on the maximum electricity generation criterion, followed by the redistribution of generating capacities among sites with an acceptable capacity factor in accordance with the selected optimization criterion. The methodology was tested on a model comprising six potential wind farm sites and two solar farm sites with a total installed capacity of 600 MW and a maximum power system load of 3000 MW. The obtained results show that the optimal redistribution of installed capacities among sites allows a 31.5% reduction in net load variability intensity to be achieved with an 11.6% reduction in electricity generation relative to the maximum possible. The study is based on idealized daily generation and consumption profiles and is theoretical in nature, proposing a pre-screening tool for RES siting that complements rather than replaces subsequent network-constrained planning studies, including power-flow analysis and grid verification, and establishes a methodological foundation for further development using real multi-year retrospective data. Full article

This study proposes a multi-criteria decision-making framework for determining optimal locations for shared micromobility stations in Kars, Türkiye. The approach integrates spatial data with structured expert evaluation and applies the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank candidate locations. Eight representative locations were evaluated based on five criteria: points of interest (POId), public transport distance, activity level, accessibility, and installation suitability. Spatial indicators were obtained through map-based measurements, while qualitative criteria were assessed using expert-based scoring by 11 experts. The results indicate that locations with high activity density, strong accessibility, and a high concentration of POIs achieve the highest suitability scores. The city center (L2) and Kafkas University (L1) were identified as the most suitable locations, with closeness coefficients of 0.862 and 0.783, respectively. In contrast, the train station (L5) showed the lowest suitability, with a closeness coefficient of 0.326. A sensitivity analysis confirmed that the ranking structure remained unchanged under moderate variations in criteria weights, indicating the robustness of the proposed model. The findings suggest that micromobility systems are primarily driven by intra-urban mobility demand rather than by long-distance transportation nodes. From a sustainability perspective, the proposed framework supports evidence-based planning of shared micromobility infrastructure, which can contribute to reducing dependence on private automobiles, improving urban accessibility, and promoting low-carbon transportation. The findings provide practical guidance for municipalities seeking to develop environmentally sustainable, socially accessible, and resource-efficient urban mobility systems in medium-sized cities. The framework can also support broader sustainable urban development strategies and contribute to the achievement of sustainable mobility objectives. Full article

Worldwide, flash floods are among the most unpredictable and hazardous hydrological phenomena, particularly in arid and semi-arid regions such as the Kingdom of Saudi Arabia, where sudden heavy rainfall follows prolonged periods of drought. This work presents an effective integrated model for flood hazard evaluation in the Hanefah Catchment, a socioeconomically vital area in the central part of Saudi Arabia that includes the capital city, Riyadh. Using high-resolution ALOS PALSAR 12.5 m Digital Elevation Model spatial data, we extracted and investigated indicative linear, areal, and relief morphometric keys of 64 sub-catchments. This paper employs a dual-method concept that integrates a multi-criteria ranking method and the El-Shamy approach in conjunction with morphotectonic analysis to model flood-susceptibility zones. Furthermore, this paper suggests a comparative assessment of low-cost morphometric models under data-scarce conditions, assessing the multi-criteria ranking method against El-Shamy’s approach, using the topographic position index (TPI) as an internal terrain scale benchmark. The ranking method successfully assigned 85.7% of the historically recorded flood locations to the high-hazard zone that covers ~24.22% of the Hanefah catchment. In contrast, the El-Shamy approach systematically underestimated flood susceptibility because regional tectonic activity increases bifurcation ratios, resulting in just ~42.9% of the historical floods being assigned to the high-hazard zone. The final results highlight the northern and northwestern parts of the catchment as high-hazard zones, characterized by high drainage density and steep relief. This study provides a refined, cost-effective model that aligns with the strategic objectives of Saudi Vision 2030 for sustainable water resources management and significant urban development. Full article

The development of sustainable tourism requires the use of planning methods that combine environmental protection with inclusive access to nature-based destinations. This article presents a macro-level spatial decision-support framework for planning service infrastructure for specialized off-road electric wheelchairs in mountain destinations. The proposed framework combines predefined static vehicle-related constraints, Geographic Information System (GIS) analysis using QGIS and OpenStreetMap data, and Multi-Criteria Decision Analysis (MCDA). The spatial filtering stage evaluates terrain feasibility using an adopted maximum longitudinal slope threshold and minimum path-width requirement. The location–allocation stage combines Simple Additive Weighting (SAW) with a spatial-dispersion procedure to identify service hubs that are both suitable and regionally distributed. The method is not a dynamic engineering model of vehicle performance, but a GIS-MCDA planning tool for preliminary regional infrastructure siting under predefined operational constraints. Full article

Increasing attention has been directed toward walkability evaluation because pedestrian environments are closely associated with mobility patterns, environmental quality, and everyday spatial experience. However, most existing walkability studies either emphasize objective spatial indicators or rely on subjective satisfaction surveys, while the relationship between expert evaluation and user satisfaction has received relatively limited attention, particularly regarding its nonlinear characteristics. In addition, walkability frameworks developed for urban public environments are often directly applied to university campuses without adequately considering the distinctive behavioral characteristics of campus pedestrian activities. To address these limitations, this study proposes an integrated AHP–Kano walkability evaluation framework for campus pedestrian systems. The framework combines the Analytic Hierarchy Process (AHP) with the Kano model to establish a perception-sensitive and behavior-oriented evaluation structure. AHP is employed to determine the relative importance of environmental indicators through expert judgment, while the Kano model is introduced to capture the asymmetric effects of different environmental attributes on user satisfaction. GIS analysis and field investigation were employed as supplementary spatial diagnostic tools to support the interpretation of pedestrian–environment characteristics. Using the Xiamen campus of Huaqiao University as a case study, this research constructs a multidimensional evaluation system covering accessibility, safety, comfort, landscape quality, and service functionality. Questionnaire surveys and expert evaluations were conducted to analyze the relationship between objective environmental importance and subjective perceptual response. The results indicate that safety- and accessibility-related attributes primarily function as must-be requirements that prevent dissatisfaction, whereas environmental cleanliness and selected experiential elements exhibit stronger satisfaction-enhancing effects. Several landscape-related indicators, commonly emphasized in urban walkability studies, demonstrate relatively weak perceptual sensitivity in campus contexts, reflecting the task-oriented and time-constrained nature of campus pedestrian behavior. The present study extends existing walkability research in several important respects. Rather than relying on conventional linear assumptions, the proposed framework incorporates nonlinear perceptual responses into walkability evaluation. The findings further demonstrate that pedestrian perception is highly context-dependent in campus environments, while the integrated framework further provides a behavior-sensitive basis for prioritizing spatial interventions. Full article

Introduction: International studies have demonstrated a positive impact on air quality associated with the presence of green areas in urban conglomerates. However, in Brazil, studies addressing the impacts of urban green areas on air quality are still incipient and are predominantly focused on large urban centers. The objective of this study was to investigate the relationship between urban green areas, surface temperature (LST), and air quality across 15 medium-sized Brazilian cities. Methods: Concentrations of particulate matter fractions (PM₁, PM_2.5, and PM₁₀) were monitored from January 2023 to May 2024 using second data from low-cost sensors. The NDVI and both daytime and nighttime LST profiles were extracted via Google Earth Engine within a 1 km buffer zone surrounding each station via the Sentinel-2 and MODIS 11A1 satellite data, respectively. Spatial–temporal co-variation patterns were explored using principal component analysis (PCA). To model these dynamics while controlling for spatial dependencies, a multi-criteria framework compared linear models (simple linear regression (LM) and linear mixed (LMM)) and generalized models (generalized additive (GAM) and generalized additive mixed (GAMM)). Results: The results revealed a positive relationship between NDVI and PM_2.5 and PM₁₀ fractions in specific regions, while surface temperatures showed a direct association with finer particles (PM₁ and PM_2.5). The regression coefficient showed the significant association of PM2.5 with NDVI and nighttime LST (β = 1.330; IC 95%: [0.397; 2.270]; p = 0.005). The GAMM was the best-fitting model for all particle fractions, demonstrating that incorporating monitoring stations as random intercepts successfully controls for unmeasured local heterogeneity, while penalized splines accurately capture non-linear environmental factors. Conclusions: Although many studies have shown that green areas in temperate regions typically act as consistent sinks for particulate matter, our study revealed localized and seasonal responses in tropical urban landscapes. It should be noted that our study is conducted on a national scale and that the use of low-cost sensors and remote sensing does not allow us to distinguish between the localized microclimatic benefits of vegetation and the long-range transport of regional pollutants. Full article

Freshwater reservoirs face increasing threats from eutrophication and anthropogenic nutrient enrichment, yet practical multicriteria tools for ranking site-specific vulnerability remain underutilized. This study applies the PROMETHEE/GAIA multicriteria decision analysis framework to rank water quality vulnerability at five sampling sites (L1–L5) in Shanzai Reservoir, Fujian Province, China, using ten water quality parameters (TN, TP, COD, DO, Chl-a, pH, temperature, N:P ratio, transparency, and carbon ratio) measured monthly from April 2023 to April 2024. The PROMETHEE II complete ranking and the GAIA biplot together provide both a spatial vulnerability ranking and parameter-level diagnostic visualization. The Reservoir Centre (L5) ranked first (Φ = +0.32), exhibiting the most favorable water quality, while the River Channel (L3) ranked last (Φ = −0.44), with mean TN (1.15 mg/L) and TP (0.088 mg/L) exceeding Chinese Class III standards and Chl-a (35.89 µg/L) surpassing eutrophication thresholds. Intermediate rankings: L4 (Φ = +0.20), L1 (Φ = 0.00), L2 (Φ = −0.04). Spatial vulnerability followed a clear zone-level gradient: the riverine zone (L1, L3) was most vulnerable, the transitional zone (L4) showed intermediate performance, and the lacustrine zone (L2, L5) was most favorable, consistent with reservoir hydrodynamic theory. The GAIA biplot revealed that nutrient criteria (TN, TP, Chl-a) were the primary drivers separating site vulnerability classes. A sensitivity analysis across eight weighting scenarios confirmed that L3 ranked last in all scenarios (Φ = −0.450 to −0.694), demonstrating the robustness of the recommendation to prioritize intervention at the river channel inflow zone. These findings offer a practical, reproducible decision-support framework for water quality management prioritization in subtropical freshwater reservoirs, subject to confirmation through multi-year monitoring programs. Full article

Urban sprawl in Iran has previously been examined through spatial measurement, driver classification, and multi-criteria weighting approaches. However, less attention has been given to the hierarchical structure through which governance, market, infrastructure, demographic, and regulatory conditions reinforce one another over time. This study develops a structural interpretation of urban sprawl in Iran’s major metropolitan regions by integrating expert refinement of key drivers with Interpretive Structural Modeling and MICMAC analysis. Rather than ranking drivers by relative importance, the analysis identifies their causal positioning within the wider sprawl system. The findings show that institutional fragmentation, weak enforcement capacity, and limited metropolitan coordination occupy the deepest structural levels, shaping downstream outcomes such as speculative land development, infrastructure-led peripheral expansion, housing pressure, and the growth of outlying settlements. The study contributes to urban-sprawl scholarship by reframing Iranian metropolitan expansion as a governance-embedded spatial process and by identifying leverage points for coordinated intervention. Policy responses should therefore prioritize institutional alignment, enforceable growth-management mechanisms, and infrastructure investment that supports compact rather than dispersed metropolitan development. Full article

Feeding and Eating Disorders (FED) require integrated, recovery-oriented care models that extend beyond clinical treatment and incorporate supportive environments capable of enhancing psychosocial well-being. Within this perspective, nature-based and socio-agricultural practices represent promising yet underexplored therapeutic resources, particularly when integrated into spatial planning frameworks. This study develops and tests a Geographic Information Systems (GIS)-based Decision Support System (DSS) that matches the specific therapeutic needs of individuals undergoing treatment for FED with the spatial distribution and characteristics of green and agricultural environments. The research is based on a case study involving the FED care center “Il Pellicano” in Perugia, Italy. Supply-side data were collected from 65 facilities, including 58 social farms, 6 community gardens, and the center’s private garden. Demand-side data were obtained through a questionnaire administered to patients by healthcare professionals, while supply-side attributes were collected through structured interviews with facility managers. The spatial matching process was implemented in a GIS environment using a non-compensatory multi-criteria approach that integrated thematic activities, spatial and/or organizational accessibility, confidentiality, spatial capacity, and environmental settings. The results reveal a substantial mismatch between demand and supply, with the current territorial system satisfying only 37.67% of expressed therapeutic needs. Sensitivity analysis indicates that the main constraints relate to the limited availability of medium-sized, low-attendance, and freely accessible environments. Beyond the local case study, the proposed DSS provides a transferable planning-support tool for designing personalized therapeutic pathways and strengthening the integration between green infrastructure, social farming, and healthcare systems. The study highlights the strategic role of spatial planning in promoting health equity, social inclusion, and community well-being. Full article