Search Results (4,719)

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

Constrained multi-objective optimization problems (CMOPs) widely exist in scientific research and industrial applications. In Type IV CMOPs, where the constrained Pareto front (CPF) is significantly separated from the unconstrained Pareto front (UPF) by large infeasible barriers, traditional single-population evolutionary algorithms often suffer from severe search reachability difficulties. Moreover, while existing dual-population coevolutionary frameworks can exploit auxiliary populations to provide global guidance for obstacle crossing, they typically adopt a constant knowledge transfer intensity, which may introduce negative transfer and interfere with fine-grained CPF convergence in later evolutionary stages. To address these challenges, this paper proposes a Dual-Population Constrained Multi-Objective Evolutionary Algorithm with Adaptive Knowledge Migration (ADCMO). The algorithm constructs a main–auxiliary dual-population coevolutionary framework: the main population pursues feasible convergence under the original constraints, while the auxiliary population explores the unconstrained objective landscape to maintain global awareness. A linearly decaying migration control factor is introduced to dynamically regulate the intensity of cross-population knowledge transfer. Specifically, a dual-defense mechanism is established by simultaneously controlling the auxiliary participation ratio in mating pool construction and the auxiliary offspring injection scale in environmental selection, thereby achieving the synergistic effect of enhanced obstacle crossing in early evolution and progressive interference suppression in later stages. Extensive experiments on two benchmark suites comprising 23 test problems and ten representative real-world constrained multi-objective optimization problems demonstrate that ADCMO shows clear advantages on several large-barrier Type IV-like CMOPs, especially on the LIR-CMOP suite, while maintaining feasible and competitive behavior on most remaining instances. Ablation studies further verify the non-negligible contributions of the auxiliary population, the adaptive migration factor, and the dual-defense mechanism to the overall performance. Full article

Health tourism represents a dynamic sector operating at the intersection of medical services, international patient mobility, and tourism development. Despite its growing prominence, the academic literature frequently conflates health tourism with medical and wellness tourism—a conceptual ambiguity that complicates the establishment of robust, sustainable legal frameworks. Addressing this gap, the present paper conceptualizes health tourism as an overarching framework that encompasses recovery, wellness, and medical sub-sectors. Within this comprehensive paradigm, we explore the contemporary landscape of health tourism in Northern Cyprus through a stakeholder-driven qualitative lens. Utilizing a qualitative case study design, data were gathered via semi-structured interviews with 40 key respondents representing healthcare, travel, public administration, academia, and related professional domains, and subsequently subjected to thematic analysis using NVivo 15 software. The findings reveal that the sector in Northern Cyprus is heavily skewed toward medical tourism, with a concentrated focus on in vitro fertilization (IVF), cosmetic surgery, dental care, and bariatric procedures. Conversely, wellness and rehabilitation tourism remain largely untapped strategic niches. The analysis further indicates that sectoral growth is constrained by structural bottlenecks, including fragmented governance, limited international recognition, transport and accessibility barriers, inadequate accreditation systems, lack of stakeholder synergy, and ethical concerns regarding advertising and patient safety. Moving beyond standard environmental sustainability, this research underscores that long-term destination resilience requires ethical governance, clinical quality controls, patient-rights advocacy, transparent legal frameworks, and community-level economic integration. Ultimately, this study proposes an integrated, stakeholder-centric paradigm tailored to the unique socio-political and structural realities of Northern Cyprus, offering actionable policy recommendations that enrich the discourse on sustainable medical tourism from a small-island perspective. Full article

Environmental datasets are often characterized by complex spatial structures and the presence of atypical observations that may influence the interpretation of landscape patterns. This study proposes a comparative framework for identifying spatial outliers in landscape structure using two complementary approaches: K-means clustering and multivariate visual exploration based on Chernoff faces. The analysis is conducted on two temporal snapshots (1956 and 2019) representing long-term changes in land use and land cover in the Zemplínska Šírava region, Eastern Slovakia. Outlier detection results from both approaches are systematically compared to assess their consistency and robustness. The two methods show substantial correspondence in the identification of anomalous landscape units. The number of land-cover classes increases from 19 in 1956 to 25 in 2019, reflecting increased landscape heterogeneity over time. Persistent spatial outliers across both methods and time periods include road networks and associated land and broad-leaved forest with continuous canopy, indicating the structural stability of these landscape elements despite long-term transformation. The results demonstrate that combining clustering-based approaches with multivariate visual analytics can improve the interpretation of complex spatial patterns in environmental data. However, the study is exploratory in nature, and the interpretation of Chernoff faces involves inherent visual subjectivity, which should be considered when evaluating the results. The proposed framework should therefore be regarded as a complementary exploratory tool rather than standalone analytical evidence. Future research may extend this framework by integrating identified spatial outliers into environmental assessment models focused on biodiversity patterns, ecological connectivity, and sustainable landscape planning. Full article

The global regulatory landscape is shifting from voluntary corporate social responsibility (CSR) reporting to mandatory Environmental, Social, and Governance (ESG) disclosure, yet whether this transition drives substantive corporate environmental change or merely symbolic compliance remains empirically contested. This study investigates the causal impact of mandatory ESG disclosure on firm value and operational carbon intensity, drawing on an unbalanced panel of 9682 firm-year observations for 1626 listed firms from the European Union (EU-27) and Japan covering the period 2018 to 2024. The EU serves as the treatment group, where mandatory disclosure requirements escalated substantially from 2021 onward through the Sustainable Finance Disclosure Regulation and the Corporate Sustainability Reporting Directive proposal. Japan serves as the control group, representing a developed economy with sophisticated capital markets and high ESG awareness that maintained a voluntary disclosure environment throughout the study period. A Difference-in-Differences framework with firm- and year-fixed effects is employed, and causal identification is validated through a dynamic event study analysis. Three principal findings emerge. First, mandatory ESG disclosure is not associated with a statistically significant improvement in firm value in the EU–Japan comparative context, a result that is interpreted as descriptive rather than causal given evidence of pre-existing valuation divergence between the two groups. Second, mandatory disclosure is associated with a significant and progressive reduction in Scope 1 and 2 carbon intensity, indicating substantive operational decarbonization rather than symbolic compliance. Third, this emissions-reducing effect is significantly amplified among firms with dedicated CSR sustainability committees, while the board independence policy indicator yields no significant moderating effect, a finding attributed to data limitations. These results carry direct implications for policymakers designing climate-related disclosure frameworks and for scholars examining the boundary conditions under which mandatory transparency translates into genuine environmental performance. Full article

Mountain stream ecosystems are often considered among the least disturbed freshwater environments; however, increasing land-use pressures may affect their ecological integrity even under apparently high-water quality conditions. This study aimed to assess the relative influence of landscape, physicochemical, and hydromorphological factors on benthic macroinvertebrate communities in three sub-catchments (Ambroz, Jerte, and Tiétar) of the Sierra de Gredos (Central Spain). A total of 33 sampling sites were surveyed, and macroinvertebrate assemblages were analyzed in relation to environmental variables using partial Redundancy Analysis (pRDA) and variance partitioning. All sites were classified as having “Excellent” ecological status based on the Iberian Biological Monitoring Working Party (IBMWP) index. However, multivariate analyses revealed clear spatial patterns and responses to environmental gradients. Results indicated that catchment-scale landscape characteristics defined the pool of potential colonizers, while local physicochemical and hydromorphological conditions acted as secondary filters structuring macroinvertebrate assemblages. Landscape variables explained the largest fraction of variance in community structure (30.6%), followed by physicochemical parameters (29.0%) and hydromorphological indices (24.9%), with a significant shared component (16.5%) indicating interactions among drivers. Agricultural land use, particularly in the Jerte sub-catchment, was associated with shifts in community composition, favoring tolerant taxa such as Diptera, while sub-catchments dominated by natural vegetation supported higher richness of sensitive groups, including Ephemeroptera and Plecoptera. These findings highlight the importance of multi-scale processes in structuring mountain stream communities and reveal limitations of traditional biotic indices in detecting early ecological changes. The results support the integration of catchment-scale variables into ecological assessment frameworks and emphasize the need for preventive, basin-scale management strategies to maintain ecological integrity under increasing anthropogenic pressure. Full article

Soil wind erosion (SWE) remains a significant challenge to improving ecological environmental quality and achieving sustainable socioeconomic development in drylands of northern China. An in-depth understanding of the spatio-temporal variations and underlying mechanisms of regional SWE is a prerequisite for the scientific prevention and mitigation of erosion-related hazards. However, in regions with high variability in intra-annual climate, quantitative studies on the spatial heterogeneity and intra-annual variability of drivers of SWE are scarce. This knowledge gap poses challenges for policymakers in developing effective landscape management strategies that are spatially and temporally specific. Here, the dynamics of SWE in the Xilingol typical steppe of China were simulated using the Revised Wind Erosion Equation (RWEQ) at seasonal and annual scales during 2000–2020. Stepwise regression and geographically weighted regression (GWR) were employed to examine the spatial heterogeneity in the relationships between SWE and environmental variables. The results revealed that RWEQ simulations were significantly correlated with the frequency of dust storm events at the seasonal scale (R² = 0.807, p < 0.01). SWE in spring accounted for approximately two-thirds of the annual total, indicating that spring was the critical period for SWE control. High SWE intensity was concentrated in sandy soil regions, with the Otindag Sandy Land and Gahai Elesu Sandy Land being identified as priority areas for desertification prevention and control. Over the study period, SWE exhibited an overall decreasing trend at both seasonal and annual scales, suggesting an enhancement in the ecosystem’s capacity for windbreak and sand stabilization. The stepwise regression results indicated that climatic factors generally had greater explanatory power than topographic and landscape pattern variables. Wind speed showed the strongest association with SWE across different time scales, whereas the relationships of normalized difference vegetation index (NDVI) and precipitation with SWE exhibited clear seasonal dependence. The GWR results further revealed pronounced spatial heterogeneity and seasonal variability in both the direction and magnitude of the associations between SWE and climatic and landscape pattern variables. These findings provide scientific support for identifying priority areas for desertification prevention and for developing spatio-temporally targeted landscape management strategies in dryland sandy regions. Full article

Natural climate variations and human activities have significantly altered the river–lake hydrological regimes in the middle and lower reaches of the Yangtze River, leading to substantial changes in the inundation patterns of the Dongting Lake wetland, which in turn profoundly affect the spatial distribution and landscape patterns of wetland vegetation. Determining the response mechanisms and appropriate thresholds of wetland landscape patterns to hydrological rhythm changes is of great importance for maintaining the health of wetland ecosystems and optimizing the ecological operation of water conservancy projects. Based on long-term measured water level data (1992–2023) and multi-temporal Landsat remote sensing images (1997–2022), combined with a digital elevation model (DEM), this study systematically analyzed the spatiotemporal evolution characteristics of the inundation processes in Dongting Lake before and after the operation of the Three Gorges Project (TGP) and their driving mechanisms on the plant landscape patterns of the floodplain wetland. The results show that after the TGP operation, the inundation pattern of Dongting Lake exhibited a drying trend, with a significant decline in annual mean water level (the largest drop of approximately 0.7 m in East Dongting Lake) and a marked reduction in the lake-wide average inundation duration (T) and inundation frequency (F). From 1997 to 2022, the total area of wetland vegetation in Dongting Lake showed a significant expansion trend, and the succession of the landscape pattern experienced a nonlinear process of stability, fragmentation, and recovery. The stepwise regression model revealed that the three elements of the inundation process explained more than 80% of the landscape pattern variation, among which inundation frequency (F) and inundation duration (T) were the core driving factors. Specifically, inundation frequency primarily regulated landscape diversity (SHDI) and contagion (CONTAG) through an environmental filtering effect, while maximum inundation depth (H) mainly maintained the physical connectivity (COHESION) of the landscape. Furthermore, the study quantified the stable hydrological range of the Dongting Lake wetland ecosystem: when the inundation frequency is maintained at 0.40–0.50 and the annual inundation duration is controlled at 4–5 months, the wetland landscape is in an optimal structural state. Once the warning thresholds are breached (e.g., F < 0.35 or T < 90 days), it may trigger the rapid expansion of cultivated poplar forests under combined hydrological and anthropogenic influences, leading to severe habitat fragmentation. These findings deepen the understanding of the response mechanisms of vegetation landscape patterns in large lake wetlands under altered hydrological rhythms. Full article

Landscape Ecological Risk (LER) reflects the potential adverse effects of landscape change on ecological structure, function, and stability. In rapidly urbanizing megacities such as Dhaka, vegetation loss and built-up expansion have intensified environmental pressure over recent decades. This study examines the spatiotemporal dynamics of LER in Dhaka from 2004 to 2024 under the combined influence of vegetation change and urban expansion. Multi-temporal remote sensing data were used to generate land cover maps, derive Fractional Vegetation Cover (FVC), and quantify urbanization intensity using Nighttime Light (NTL) data. The Landscape Ecological Risk Index (LERI) was calculated using landscape pattern metrics, while bivariate spatial autocorrelation and geographically weighted regression (GWR) were applied to examine spatial associations and local spatial heterogeneity. The results show that vegetation degradation affected 34.39% of the study area during 2004–2024, while high-risk zones increased from 24.36% in 2004 to 42.95% in 2024. Land cover analysis further indicates a substantial expansion of built-up areas, accompanied by the contraction and fragmentation of vegetation, agricultural land, and lowland classes. Spatial analyses reveal that the relationships among vegetation cover, urbanization intensity, and ecological risk vary across the city and became increasingly spatially differentiated over time. These findings suggest that vegetation loss and urban expansion are spatially associated with increasing ecological risk in Dhaka. However, the results should be interpreted with caution because of uncertainties related to remotely sensed data, unsupervised land cover classification, resampling procedures, and limited ground validation. Despite these limitations, the study provides a spatially explicit framework for understanding ecological risk dynamics and offers useful evidence for green-space conservation, ecological restoration, and sustainable urban planning in rapidly urbanizing regions. Full article

The European Union (EU) and national governments have set clear targets to reduce agricultural emissions, including ammonia from manure spreading practice, with regulations such as the Ambient Air Quality (AQ) and Clean Air Directives, the Common Agricultural Policy (CAP), and the Green Deal, with implication for ecosystem services and landscape planning, reflecting broader environmental sustainability objectives including those addressed by the Sustainable Development Goals (SDGs). Informative Inventory Reports (IIRs) are critical tools within the EMEP/EEA framework for monitoring long-range transboundary air pollution. They utilize three distinct methodological tiers (Tiers 1, 2, and 3) to estimate emission data across Europe. Despite the availability of Earth Observation (EO) data and products from the Copernicus Programme current estimation methods still rarely integrate EO information to produce spatially explicit estimates. This paper reviews current methodologies for estimating ammonia in IIRs and in scientific literature, including advanced methods not yet implemented in official inventories but potentially capable of supporting more spatially explicit and process-oriented estimation. A Medium Effort Methodology (MEM) is identified among those reviewed as a representative methodological pathway for integrating EO information with Tier 3 approaches. Building on this, the paper explores the association between specific EO data and Copernicus products, and input variables required by MEM, identifying opportunities and barriers for environmental monitoring with potential relevance to sustainable agriculture. Full article

Waterfront built environments are increasingly exposed to hydrological variability and climate-related pressures that challenge conventional land-based building typologies. This systematic review examines permanently buoyant floating systems and flood-responsive amphibious systems as water-adaptive approaches to climate adaptation and regenerative waterfront development. Peer-reviewed studies indexed in Scopus and Web of Science were reviewed for January 2015–August 2025, with searches last updated on 15 August 2025. The review combines PRISMA-guided selection, bibliometric mapping of the screened publication landscape (N = 1410), and qualitative synthesis of the core evidence base (N = 63). Regenerative potential is operationalised as credible only where supported by explicit ecological, socio-spatial, governance-related, or performance-oriented evidence, including life-cycle assessment, post-occupancy evidence, ecological monitoring, habitat enhancement, blue-green infrastructure integration, or documented implementation mechanisms. The findings show that floating typologies dominate the evidence base, whereas amphibious approaches are less frequent but more directly associated with in-place flood adaptation. Persistent gaps concern regulatory frameworks, infrastructure interfaces, life-cycle assessment, ecological validation, and long-term post-occupancy monitoring. The review concludes that scalability depends on context-specific siting, institutional permission, regulatory approval, and verifiable environmental performance. Full article

Rooftop farms are urban green infrastructure integrating food production, ecological regulation, and public services, and their management increasingly relies on data-driven approaches. However, open built environments, microclimatic heterogeneity, and limited sensor deployment challenge continuous monitoring and short-term prediction of rooftop plant growth. This study proposes and validates a virtual sensor-driven digital twin system using a rooftop tomato case in Xiamen, China. The system adopts a five-layer architecture comprising data acquisition, transmission, modeling, processing, and application service layers. By coupling a Long Short-Term Memory (LSTM) weather prediction model with the Decision Support System for Agrotechnology Transfer (DSSAT) crop growth model, a predictive virtual sensor module was developed to forecast leaf area index (LAI), aboveground biomass, phenology, and yield for seven days. Results show that the system links environmental data acquisition, LSTM–DSSAT prediction, database storage, and three-dimensional visualization, transforming rooftop plant growth into an updatable, predictable, and visualized digital twin object. The coupled model showed high predictive accuracy, with R² values of 0.9814 for LAI and 0.9966 for aboveground biomass, while supporting phenology and yield prediction. The system supports irrigation optimization, landscape management, and activity planning in sensor-constrained rooftop farms. Full article

Exposure to urban green spaces has been associated with mental wellbeing, but the neural responses to specific visual properties of urban green spaces remain unclear. This study investigated regional electroencephalogram (EEG) responses to latent visual dimensions of virtual urban green space exposures. This study used a quantitative scene-based approach that extracted 41 visual metrics to capture the heterogeneous structural properties of 24 panoramic urban green images. EEG recordings were analyzed from 150 participants, each of whom viewed eight randomly selected images repeated three times. Dimension-wise factor analysis with varimax rotation was used to derive latent factor scores for four conceptual dimensions: naturalness, complexity, coherence, and visual scale. These factors were then used as predictors in crossed mixed-effects models of regional EEG relative power changes. The hypothesis-driven primary analysis showed a significant and positive association between parietal alpha–theta activity and a naturalness factor reflecting green–grey scene compositions. Exploratory frontal associations with a terrain-related visual scale factor reached nominal significance but did not survive false discovery rate correction. Overall, the findings support a quantitative, feature-based approach for linking urban green space structure with regional neurophysiological responses. This study provides a methodological step toward more evidence-informed assessment of smart and sustainable urban environments. Full article

Traditional villages are important carriers of rural cultural heritage, yet their spatio-temporal distribution and underlying mechanisms remain insufficiently understood, particularly regarding the interaction between environmental and socio-cultural drivers over long historical periods. Focusing on 131 nationally recognized traditional villages in southern Hebei, China, this study integrates GIS-based spatial analysis with historical interpretation to examine their spatial patterns, temporal evolution, and driving factors from the pre-Sui period to the Qing Dynasty and post-Qing period. The results show that traditional villages exhibit a highly clustered and uneven distribution, primarily concentrated in mountain-front zones in the western and southwestern parts of the region. Spatial analysis reveals a multi-core clustering structure, and spatial autocorrelation confirms that this pattern is statistically significant. Temporally, village formation follows a non-linear process of concentration, expansion, and stabilization, with the Ming Dynasty representing a key peak period. The findings further indicate that dominant driving mechanisms shifted over time: early settlement was mainly constrained by environmental conditions, whereas later development increasingly depended on socio-cultural processes such as migration, defense, clan organization, and regional exchange. In the contemporary context, economic development and accessibility introduce complex and non-linear effects. These results suggest that traditional villages should be understood as dynamic cultural landscapes shaped by long-term human–environment interactions. This study provides an integrated framework for understanding rural settlement dynamics and offers insights relevant to rural heritage conservation and sustainable development in transitional regions. Full article

Mining activities elevate environmental noise and represent a major disturbance in terrestrial ecosystems. Vegetation belts are often used as mitigation measures. This study evaluates the role of Robinia pseudoacacia L. forest plantations in reducing noise at the lignite complex of western Macedonia, in Greece. Field measurements of noise level (LAeq) were conducted inside and outside the plantations from spring to autumn during 2020 and 2021. Measurements were taken at five points across four sites differing in their distance from the noise source. Leaf Area Index (LAI) was recorded, and meteorological variables were measured concurrently. Linear mixed-effect models were used to assess the effects of forest presence, distance from source, climatic conditions, and LAI, while accounting for repeated measurements across sampling days and sites. Noise levels were significantly lower within plantations than outside, indicating that restored forest stands can act as buffers to mining noise. The distance of trees from the noise source and atmospheric conditions are also significant drivers of noise levels. These findings highlight the potential of post-mining plantations to provide an additional acoustic regulation service in restored industrial landscapes. Full article