Search Results (174)

High-altitude wetlands in the Caucasus Anatolia transition zone remain among the least-documented avian habitats in the Western Palearctic. Standardised avian biodiversity assessment in such systems provides essential evidence for sustainable wetland management, supporting the conservation planning and long-term ecological monitoring needed to safeguard these ecosystems under increasing anthropogenic pressure. We report on the avifauna of Çalı Lake (2237 m a.s.l.; 391 ha; Kars Province, Türkiye), a nationally designated wetland located on the Central Asian Flyway, based on five systematic survey periods conducted from March 2024 to Spring 2026 using line transects and point counts, combined with a 25 × 25 m grid-based GIS analysis encompassing 498 cells. Approximately 31 ha of the core open-water and marsh perimeter within the 391 ha designated boundary is covered; upland steppe and pasture zones beyond the active survey perimeter were excluded. A total of 154 species belonging to 18 orders and 41 families were recorded, representing approximately 30.5% of Turkey’s national checklist. IUCN status assessment identified two Endangered species, Neophron percnopterus and Oxyura leucocephala, two Vulnerable, five Near Threatened, and 145 Least Concern species. Grid-level species richness averaged 1.47 ± 1.20 per cell per period; cumulative richness per grid reached 7.62 ± 2.73 across all five survey periods. Spearman rank correlation between per-grid richness (S) and abundance (N) was consistently strong across all five periods (ρ = 0.52–0.60; all p < 0.001). A Friedman test indicated significant overall variation across periods (χ²(4) = 127.73, p < 0.001, Kendall’s W = 0.064, a negligible effect size by conventional benchmarks, indicating that the statistically significant variation reflects trivially small per-cell richness differences at this block size). Bonferroni-corrected post hoc Wilcoxon tests revealed that all significant contrasts involved the 2024 Spring–Summer period or the 2026 partial Spring window, while the four fully comparable 2024 Autumn–2025 periods showed no significant differences. A Lorenz concentration curve yielded a Gini coefficient of 0.351, with the top 10% of grid cells concentrating 24.0% of all individual detections in the central and south-western lake zones. Collectively, these findings document Çalı Lake as a species-rich high-altitude wetland with significant conservation value, and establish a reproducible spatial and temporal baseline for long-term ornithological monitoring. These results demonstrate the value of standardised biodiversity assessment as a practical tool for sustainable wetland governance and align with international sustainability frameworks, including the UN Sustainable Development Goals on life on land and clean water and sanitation. Full article

Rapid urban population aging and increasing land constraints pose significant challenges for improving both service coverage and spatial equity in elderly care facility planning. This study develops an integrated optimization framework that simultaneously addresses accessibility, efficiency, and equity in the spatial allocation of elderly care facilities. First, an improved Gaussian Two-Step Floating Catchment Area (G2SFCA) method is employed to evaluate accessibility patterns across multiple facility types under both walking and driving scenarios. Second, resource allocation equity is quantified using Lorenz curves and spatial Gini coefficients to identify mismatches between elderly care supply and population demand. Building upon these analyses, a fairness-oriented maximum covering location model—termed the Equity Maximum Covering Location Problem (EMCLP)—is formulated and further transformed into a Markov Decision Process. A deep reinforcement learning-based algorithm is subsequently designed to solve the EMCLP under complex spatial constraints. Experiment results demonstrate that the proposed approach achieves improved computational efficiency while maintaining robust solution quality, and effectively enhances service provision in underserved areas through differentiated functional allocation strategies. Full article

Coordinating public service supply and demand is essential to urban social sustainability. This study examines ten suburban districts of Beijing at six observation points from 2015 to 2024 and develops an integrated framework encompassing resource endowment, demand pressure, supply–demand matching, and spatial equity. Resource endowment and demand pressure are measured using spatial accessibility and objective weighting methods, while relative matching coefficients, Lorenz curves, and Gini coefficients are employed to evaluate spatial mismatch and equity. The results reveal a shift toward a dynamic polycentric supply pattern, persistent relative undersupply in Tongzhou and Daxing, and dimension-specific deficits in several otherwise balanced districts. Overall spatial equity improved during the study period, although localized mismatches remained. Public service planning should therefore move from uniform expansion toward demand-responsive, place-specific, and service-specific optimization. Full article

The Ganjiang River–Poyang Lake Basin is a typical river–lake composite water-system region and a major concentration area of intangible cultural heritage (ICH) in Jiangxi Province. However, officially listed ICH does not simply represent the natural distribution of cultural practices but reflects the combined effects of historical accumulation, environmental contexts, and institutional recognition. Based on 616 national- and provincial-level ICH items, this study employs the nearest neighbor index, kernel density analysis, Lorenz curve, standard deviational ellipse, and Geodetector to examine spatial patterns and associated factors. The results reveal significant spatial clustering (NNI = 0.31, Z = −39.16), characterized by riverine concentration, lakeside distribution, and polycentric development. Traditional craftsmanship and folk customs cluster around Poyang Lake, while traditional drama, folk literature, and quyi extend along the Ganjiang River. Distance to major water systems (q = 0.821), policy support (q = 0.813), and inheritors (q = 0.806) show the highest explanatory power. The findings reveal a spatial process of lake-area accumulation, river-channel diffusion, and nodal support. Full article

Urban waterlogging poses increasing threats to megacities; however, the spatial distribution of waterlogging risk inequality remains poorly understood. In this work, a comprehensive framework to evaluate urban waterlogging risk and its spatial inequality in Beijing is developed. The framework integrates machine learning-based waterlogging susceptibility, urban waterlogging resilience quantified using the entropy weight method, and population exposure data. The Gini index and Lorenz curves are employed to quantify risk inequality at both district and township scales. The central urban area is characterized by high- and very-high-susceptibility levels, while low-susceptibility areas are mainly concentrated in the outer suburbs. A distinct “core-periphery” pattern characterizes urban resilience: high resilience concentrates in the central urban area, while resilience drops significantly in the outer suburbs. The integration of susceptibility, resilience, and exposure reveals a profound spatial waterlogging risk disparity. The urban core has the highest waterlogging risk, but the burden is evenly spread across its dense population (Gini < 0.4). In contrast, outer suburbs and mountainous areas show severe inequality (Gini > 0.6), where a tiny fraction of the population bears most of the risk. This framework supports region-specific strategies to improve control efficiency and achieve environmental distributive justice. Full article

We analyze the effect of microscopic heterogeneity on the Lorenz curve of macroscopic observables. The Lorenz curve of a response function, being a cumulative and bounded quantity; it is often a more stable function than the corresponding probability density. We show here that by doing an exponent spectrum analysis of the complementary Lorenz curve, it is possible to obtain a reflection of the underlying heterogeneity that causes the response function to depart from a power law behavior. We demonstrate this framework first by synthetic data and then by analyzing the avalanche statistics of a two dimensional, Random Field Ising Model (RFIM) at zero temperature. This method can lead to possible use in estimating the microscopic heterogeneity of a system from the analysis of an estimated Lorenz curve, particularly in socio-economic and physical contexts where the full probability distribution function is unavailable. Full article

This study examines the spatiotemporal patterns of cropland change in Hunan Province and identifies the factors associated with net cropland decrease from 2000 to 2020. Using land-use transition analysis, spatial autocorrelation, Lorenz curves, Gini coefficients, and an interpretable XGBoost-SHAP model, this study analyzed cropland outflow, cropland inflow, net cropland change, and their associated explanatory patterns. The results show that: (1) cropland outflow was mainly concentrated in central and western Hunan, whereas cropland inflow was relatively more evident in central Hunan, but also occurred in parts of western and eastern Hunan. Total cropland area increased by 2961.73 km² from 2000 to 2020, but decreased by 1467.91 km² after peaking in 2009, indicating an inverted U-shaped trajectory; (2) the Gini coefficient of cropland outflow decreased from 0.4024 to 0.2891, while that of cropland inflow decreased from 0.3780 to 0.2538, indicating stronger spatial concentration of cropland outflow, although its spatial imbalance weakened over time; and (3) XGBoost-SHAP results showed that mechanical efficiency, gross domestic product (GDP), and fiscal conditions made the highest contributions to net cropland decrease, with mean absolute SHAP values of 0.21, 0.17, and 0.16, respectively. Overall, cropland change exhibited clear spatial heterogeneity, and socioeconomic and human-activity factors were dominant factors associated with net cropland decrease. These findings provide support for differentiated cropland protection and sustainable land-use management in major grain-producing regions. Full article

Agricultural supply chains operating under rural infrastructure constraints face persistent logistical inefficiencies that reduce producer income and weaken territorial sustainability. This paper assesses how collaborative and coordinated distribution architectures reshape economic performance, efficiency, and equity in dispersed networks of cocoa producers in El Carmen de Bolívar, Colombia. The unified optimization framework compares three regimes: decentralized non-collaborative individual shipments, collaborative consolidation based on distribution centers, and coordinated distribution with time-window synchronization. The findings show a reduction in average logistics costs from $0.688/kg in decentralized distribution to $0.323/kg with collaborative distribution centers, and even further to $0.282/kg in coordinated distribution, representing an overall reduction of approximately 59%. A sensitivity analysis across 64 accessibility configurations shows that the advantage of coordination increases as time rigidity increases. These structural improvements translate into a 13.97% increase in total producer utility, raising average utility from $278 to $317 per producer. In addition, the distributional assessment based on Lorenz curves and Gini coefficients indicates that inequality remains stable despite gains in welfare. These results demonstrate that spatial consolidation combined with temporal synchronization is a decisive lever for resilient and inclusive rural supply systems. Full article

Nonlinear dynamical systems exhibit complex behaviors such as periodicity and chaos, which are traditionally analyzed using time-series data. However, these approaches often fail to capture the intrinsic geometric structure of the system dynamics represented in the phase space. In this study, we address this limitation by proposing a topological machine learning framework that leverages phase portrait images to classify dynamical regimes. The primary objective of this study is to investigate whether the topological features extracted from phase portraits can effectively distinguish between periodic and chaotic behaviors across different nonlinear systems. To achieve this, we employed the Topological Data Analysis (TDA) technique of cubical homology, which enables the extraction of topological descriptors, such as persistence diagrams and Betti curves. We used these features to train multiple machine learning (ML) classifiers, including XGBoost, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Gaussian Naïve Bayes (GNB), and Random Forest (RF). The experimental results across benchmark systems, including the Chua, Lorenz, Mathieu–Duffing, and erbium-doped fiber laser models, demonstrate that the proposed approach achieves high classification accuracy, with performance improving from approximately 93% under $H_0$ features to 99–100% under $H_1$ and combined feature representations. These findings highlight that topological features, particularly $H_1$, effectively capture the underlying geometric structure of dynamical systems. Overall, the proposed framework provides a robust, interpretable, and generalizable approach for phase portrait classification, with potential applications in nonlinear system analysis, pattern recognition, and early detection of chaotic transitions. Full article

Existing ship emission inventories for coastal seas are typically gridded at 500 m to 1 km, a resolution too coarse to distinguish navigation channels from anchorage zones. Whether the hotspot patterns reported at such scales reflect true emission geography or are artifacts of spatial averaging remains an open question. We construct a 100 m resolution AIS-based emission inventory for two contrasting coastal environments in eastern China—the Yangtze River estuary and the Wenzhou coastal area—using the STEAM framework, and we quantify spatial concentration with Lorenz curve analyses. At this finer resolution, three emission archetypes become separable: discrete anchorage clusters, bankside berthing bands flanking navigation lanes, and sinuous riverbank traces in confined waterways. Emissions are extremely concentrated: the top 1% of grid cells capture over three-quarters of the total theoretical emission potential (Gini = 0.940), and this pattern persists across all months of 2023. Reaggregating the same data to 1 km reduces the top-1% share by roughly 10%, confirming that coarse gridding systematically understates anchorage contributions while overstating those of transit corridors. A dedicated sensitivity analysis on auxiliary engine load assumptions (±30% perturbation of canonical Jalkanen-style load brackets) shows that, while absolute emission totals carry approximately ±15% uncertainty, the spatial concentration of emissions is highly robust: Across all perturbation scenarios, the Gini coefficient varies by less than 0.01, the top-5% emission share varies by less than 2 percentage points, and the location of top-5% hotspot cells overlaps by ≥97.9% (Jaccard index). The results highlight stationary vessel hotspots—discrete anchorages and bankside berths—as a major and previously underemphasized contributor to the cumulative coastal ship emission budget, complementing rather than replacing the conventional navigation-lane focus, with direct implications for shore power siting, anchorage management, and emission control zone design. Full article

Urban emergency shelters constitute essential spatial elements within the framework of urban disaster prevention and mitigation. Addressing the shortcomings of existing evaluation methods, which often overlook the relationship between shelters and their served populations, this study utilizes Xi’an as a case study to develop a resilience assessment model that integrates supporting facilities, operational efficiency, and safety performance. To link this model to the served population, the research incorporates the service population pressure index and employs the Gini coefficient alongside the Lorenz curve to assess the congruence between shelter resilience and population distribution. Moreover, the introduction of the intervention priority index and population vulnerability index facilitates a comprehensive determination of shelter intervention priorities. The results reveal that emergency shelters in Xi’an display a spatial pattern characterized by a “single core with multiple centers,” with higher resilience levels, service pressures, and intervention priorities concentrated in the central urban area and lower values observed in peripheral zones. Additionally, a significant spatial mismatch is identified between shelter resilience and population service demands. Despite relying on static population data and not accounting for the effects of population migration, the evaluation framework presented in this study offers a transferable methodological reference for the comprehensive evaluation of shelters in densely populated urban areas, contributing to sustainable urban development. Full article

The main focus of this paper is to introduce a new probability model. Specifically, this paper presents a modified form of the Weibull distribution and investigates its various statistical properties, such as moments, moment-generating functions, reliability functions, quantile functions, and inequality measures such as Bonferroni and Lorenz curves. It also investigates the mean absolute deviation and entropy. Distributions of order statistics, reversed order statistics, and upper record values are also obtained. Additionally, univariate and bivariate moment structures are considered. The model parameters are estimated via the maximum likelihood method under simple random sampling and ranked set sampling, allowing an empirical evaluation of efficiency and reliability. Graphical representations exhibit the flexibility of the model, capturing various shapes in the probability density and hazard rate functions. To measure the practical quality of the model, actuarial metrics are used. A comparative analysis based on insurance, biomedical, and reliability datasets demonstrates the empirically improved performance and stability of the proposed new model for these specific datasets. Full article

With the continuous renewal of urban greening, pollen released by allergenic tree species has become a prominent environmental issue affecting residents’ health. However, existing research still lacks city-wide, rapidly replicable methods for identifying allergenic tree species and assessing exposure risks. Taking Beijing’s central urban districts as a case study, this research establishes a method for the automated identification of allergenic tree species and the assessment of pollen exposure risks based on high-resolution satellite imagery. This study coupled tree species distribution results derived from model inference with population density per unit area to delineate three tiers of exposure risk zones. Subsequently, these risk zones were overlaid with the road network within the study area to determine the distribution of roads with low, medium, and high exposure risk. Public transport stop locations were then introduced as a proxy variable for areas of high population mobility. Lorenz curves and Gini coefficients were calculated to quantify the spatial equity of pollen exposure risk. The results indicate that the model reliably identifies target tree species, with approximately 117,000 valid targets. Exposure risks exhibit significant clustering characteristics and can form continuous expansions along road networks. Incorporating population factors shows minimal change in risk concentration, suggesting pollen exposure risk is primarily driven by the spatial clustering of allergenic tree species and their accessibility within road networks. This risk is highly correlated with the spatial distribution patterns and accessibility characteristics of allergenic tree species, rather than being solely determined by population size. This study provides foundational data and methodological support for urban tree species identification, pollen exposure risk management, and optimised greening configurations. Full article

Rapid urbanization has intensified the mismatch between urban green space (UGS) and urban spatial vitality (USV), hindering sustainable development. To address this, we developed the Urban Green Space Vitality Adaptation Model (UGSVAM) and analyzed 64 subdistricts in central Nanjing. Specifically, this study asks: Does the mismatch exist? What are its spatiotemporal patterns? What factors drive it? Methodologically, we use the Gini coefficient and Lorenz curve to assess overall UGS-USV adaptation, then construct the Urban Green Space Vitality Density (UGVD) indicator to quantify the match level, classifying units as overloaded, underloaded, or balanced. OLS and GWR reveal global and local influencing mechanisms, while quadrant analysis supports differentiated planning. Results show: (1) UGS-USV adaptation in Nanjing is weak, with Gini coefficients of 0.466 (weekday) and 0.456 (weekend). UGVD exhibits a spatial pattern of a primary overload core in the central city, a secondary core in the southwest, and peripheral decline, with the southeast underloaded. Overloaded units also show notable temporal variation. (2) Globally POI density and intersection density promote UGVD, while excessive transport facilities, air pollution, and high temperatures inhibit it—ecological factors have stronger weekend effects. (3) Locally, the northeast is more sensitive to POI density, the southwest to transport and heat, and the Jiangbei New Area could enhance green space carrying capacity through transport optimization and spatial integration. The UGSVAM integrates spatial diagnosis, mechanism analysis, and planning response, offering a transferable framework for refining green space governance in high-density cities. Full article

Equitable access to sports facilities is essential for promoting residents’ well-being, yet existing studies mostly rely on large spatial analytical units, limiting the ability to identify intra-unit disparities in accessibility and equity. This study develops a building-scale framework for assessing sports facility accessibility from a spatial equity perspective, incorporating building volume-weighted population distribution and quantification of multi-type facility service capacity for precise demand and supply estimation. Taking the Yuexiu District, Guangzhou, as the study area, the study assesses the accessibility of residential buildings using the Gaussian Two-Step Floating Catchment Area (G2SFCA) method and evaluates spatial equity using the Lorenz curve and local Moran’s I. Results indicate a moderate level of equity in overall facility provision (Gini coefficient = 0.288), alongside substantial inter-type disparities, with Gini coefficients ranging from 0.330 to 0.800. Accessibility clusters exhibit pronounced scale variability, ranging from a few buildings to hundreds of buildings, with small clusters embedded within larger clusters of opposite accessibility. These fine-grained patterns are largely obscured in conventional aggregated-unit analyses, underscoring the necessity of building-scale assessment. Results provide a basis for precise allocation of both facility quantity and facility types, supporting efficient decision-making for urban planning and management. Full article