Search Results (12,116)

Inter-basin water transfer source areas must sustain local habitat quality while ensuring downstream water security, yet the spatial differentiation mechanisms, driving mechanisms, and scenario-dependent responses of their ecosystem services have not been statistically tested. This study aimed to assess historical changes and future trajectories of ecosystem services in the core water source area of the Middle Route of the South-to-North Water Diversion Project, and established a historical assessment–spatial statistics–driver attribution–scenario projection analytical framework. Five ecosystem services—water yield, soil conservation, nitrogen export, carbon storage, and habitat quality—were quantified using InVEST from 2005 to 2020 and projected to 2050 under SSP126, SSP245, and SSP585 via the PLUS–InVEST coupled model. Spatial patterns were analyzed using Getis–Ord Gi* hot–cold spot analysis, hexagon-based spatial statistics (4.5 km bins), Mantel tests, and the optimal-parameter-based geographical detector. Results show that slope was the dominant spatial driver, exhibiting highly significant Mantel correlations with all five services (p < 0.001), and two-factor interactions consistently exceeded individual factor effects (e.g., population density × temperature: q = 0.527 for habitat quality; slope × temperature: q = 0.516 for soil conservation). Hexagon-based statistics revealed that carbon storage declined substantially from 2005 to 2020 (−3.23%, from 98.75 t/ha to 95.56 t/ha), while water yield and soil conservation showed no pronounced temporal trends. Scenario projections revealed divergent trajectories: relative to the 2020 baseline (267.84 mm), water yield increased by 20.1% under SSP126 (321.86 mm) but declined by 56.3% under SSP585 (117.13 mm); nitrogen export increased under all scenarios; and habitat quality declined continuously to 0.557, 0.546, and 0.539 under SSP126, SSP245, and SSP585, respectively. Within this scenario framework, SSP126 and SSP245 may better support the maintenance of water source ecosystem functions, whereas SSP585 may be associated with greater potential ecological pressures, reflected in lower water yield, higher nitrogen export, and lower habitat quality. Full article

The Shendong mining area, located in the transition zone between the northern Loess Plateau and the Mu Us Sandy Land, is a representative ecologically fragile region and desert coal base in China. Using Google Earth Engine (GEE) and Landsat imagery from 1999 to 2024, this study constructed a long-term remote sensing ecological index (RSEI) dataset and integrated the Theil–Sen median slope estimator, Mann–Kendall test, and Hurst exponent to examine the spatiotemporal evolution, future trajectories, and multi-stage driving mechanisms of eco-environmental quality (EEQ) at the mining-area and individual-mine scales. At the mining-area scale, RSEI showed pronounced interannual fluctuations and a weak downward trend, characterized by a two-stage, wave-like trajectory with a narrowing amplitude. The mean RSEI and standard deviation decreased from 0.5669 and 0.0855 during 1999–2010 to 0.5182 and 0.0501 during 2011–2024. Moderate and good grades predominated, with lower EEQ in the mining core and higher EEQ in peripheral buffer zones. Across 13 representative mines, ecological quality generally remained moderate but exhibited spatial and stage-dependent heterogeneity, with Liuta Mine showing the greatest variability. Slight degradation was the dominant trend, although local recovery occurred, and Hurst analysis revealed marked spatial differences in future trajectories. RSEI variations in the Shendong mining area exhibited pronounced spatial and stage-dependent associations with high-intensity mining, climatic water–heat conditions, topographic background, and ecological governance and restoration processes. No continuous and irreversible overall decline was observed; however, without an independent non-mining control, the findings represent integrated ecological responses within the mining area rather than causal estimates of mining’s net ecological effect. Full article

Ecological resilience is a critical indicator of forest ecosystem stability and the capacity to respond to disturbance. Under intensifying climate change and human activities, accurately evaluating forest ecological resilience is important for ecosystem restoration and sustainable management. This study developed a satellite time−series−based framework for assessing ecological resilience from the complementary perspectives of resistance and recovery. Taking the Qianshan region, a typical forest area in the northeastern forest belt, as a case study, MODIS Normalized Difference Vegetation Index (NDVI) time−series data from 2005 to 2024 were analyzed. The Breaks For Additive Season and Trend (BFAST) algorithm was used to detect vegetation breakpoints, after which ecological resistance and recovery were quantified using breakpoint magnitude and post−disturbance NDVI growth rate. The optimal−parameter−based geographical detector (OPGD) was further applied to identify the spatial drivers of resistance and recovery and their interaction effects. Approximately 21% of the pixels in the Qianshan region experienced at least one breakpoint during the study period, and more than 80% of the disturbed pixels contained only one detected breakpoint. More than 70% of the disturbed pixels subsequently exhibited vegetation recovery, and most recovered pixels had normalized recovery values between 0.40 and 1.00. In contrast, ecological resistance was generally low and varied substantially among land−cover types. Forests exhibited higher resistance but lower recovery, whereas grasslands and croplands showed lower resistance but stronger post−disturbance recovery. Among the individual factors, precipitation and slope had relatively high explanatory power for the spatial differentiation of recovery. Factor interactions substantially enhanced explanatory power, with the interaction between precipitation and elevation exerting the strongest influence on resistance and the interaction between precipitation and slope exerting the strongest influence on recovery. Although mining density had relatively limited explanatory power at the regional scale, mining activities caused non−negligible localized impacts, particularly in open−pit mining areas. The proposed framework provides a practical basis for long−term monitoring, ecological restoration, and differentiated forest management in disturbance−prone regions. Full article

Background/Objectives: Socioeconomic indicators and geographic factors influence pediatric cancer outcomes, but evidence in Romania is limited. Methods: This retrospective cohort study included 6247 patients aged 0–19 years diagnosed with cancer and recorded in the Romanian National Pediatric Oncology and Hematology Registry between 1 January 2010, and 31 December 2024. Kaplan–Meier analysis was used to estimate the survival probabilities across four strata of regional and county socioeconomic categorization and two strata of community marginalization status. Unadjusted and multivariable Cox proportional hazards models estimated hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for sex, age group, primary cancer type (ICCC-3), tumor behavior, and geographical residence. Subgroup analyses assessed the association between rurality and pediatric cancer survival, irrespective of community marginalization status. Results: Survival probabilities were consistently lower among patients residing in more socioeconomically disadvantaged regions, counties, and marginalized communities (log-rank p ≤ 0.0001). In the most deprived strata, 5-year survival for regions, counties, and communities was 69.86% (95% CI: 67.49–72.10), 67.47% (95% CI: 63.32–71.26), and 65.51% (95% CI: 61.33–69.35), respectively. In adjusted models, residence in the least deprived regions (HR = 0.783, 95% CI = 0.744–0.952) and counties (HR = 0.749, 95% CI = 0.620–0.905) was associated with improved survival, a 22% and 25% lower risk of death, respectively, compared with residence in the most deprived categories. Community marginalization was associated with lower survival outcomes in unadjusted analyses, but was not significant after adjustment. Rural residence was associated with a 44% higher risk of death (HR = 1.436, 95% CI = 1.304–1.582), with a 5-year survival of 66.76% (95% CI: 64.91–68.53) among rural patients, compared with 75.93% (95% CI: 74.28–77.48) in urban patients. Conclusions: This is Romania’s first pediatric cancer survival study to evaluate persistent social and geographical disparities. Survival outcomes were consistently lower in more socioeconomically disadvantaged regions and counties, while the findings suggest that rural residence may explain the observed differences in survival at the community level. Policymakers and health systems in Romania should focus on covering pediatric cancer patients with appropriate proximity services across the entire national territory, thus enabling all patients to get timely access to quality care. Full article

Industrial land allocation spatial morphology (ILASM) is crucial for economic development and the advancement of new-type industrialization. However, existing studies lack a comprehensive understanding of the evolutionary characteristics of the spatial morphology of industrial land allocation, let alone its driving factors and the spatial heterogeneity of their effects. Therefore, this paper classifies industrial land allocation spatial morphology into traditional industrial land allocation spatial morphology (TILASM) and high-tech industrial land allocation spatial morphology (HILASM), then evaluates and identifies their characteristics based on the precise geographic coordinates of each industrial land parcel between 2007 and 2024 in the Yangtze River Delta (YRD). Subsequently, the Random Forest Regression model and Multi-Scale Geographically Weighted Regression model are integrated to systematically investigate the driving factors and spatiotemporal patterns of ILASM, including both TILASM and HILASM. The results show that from 2007 to 2024, different types of ILASM exhibited distinct spatiotemporal evolutionary characteristics. Specifically, first, in terms of the evolution of spatial distribution direction, overall industrial land allocation exhibited a pronounced agglomeration pattern, extending from the western (slightly northern) part of the region to the eastern (slightly southern) part. Moreover, the evolutionary direction of traditional industrial land allocation was consistent with that of overall industrial land allocation. However, high-tech industrial land allocation exhibited an agglomeration trend extending from west (slightly south) to east (slightly north). Second, in terms of evolution of agglomeration pattern, the spatial distribution of TILASM evolved from three-core dispersed configuration to a multi-core linkage, before reverting to a multi-core dispersed state; by contrast, both ILASM and HILASM exhibited a spatial pattern that progressed from dispersion to contiguous agglomeration. Third, the spatial distribution characteristics of different types of ILASM were shaped by the combined influence of natural conditions, economic development, social environment, innovation environment and infrastructure. However, the dominant driving factors differed among them. Specifically, the number of foreign-invested enterprises exhibited a negative influence on ILASM, while having positive effects on both TILASM and HILASM. The effects of patent applications, population density and internet penetration rate on ILASM; foreign-invested level and slope proportion on TILASM; as well as road density, labor quality and foreign invested level on HILASM all exhibited U-shaped relationships. Moreover, the influences of opening-up level and per capital road area on ILASM and HILASM displayed relatively complex N-shaped relationships. Finally, the effects of these crucial drivers displayed significant spatial non-stationarity and certain gradient effects, manifesting in southern–northern, western–eastern and core–periphery spatial differentiation patterns. Overall, this study provides scientific evidence and practical references for optimizing the spatial allocation of industrial land. Full article

Selecting suitable agricultural land is critical for food security and sustainable development, particularly in arid regions facing resource scarcity and environmental degradation. This study assesses agricultural land suitability in Sohag governorate, Egypt, using a hybrid Geographic Information System (GIS), Fuzzy Analytical Hierarchy Process (FAHP) and geostatistical approach. Thirty-four representative soil profiles were morphologically described and analyzed for ten physical (slope, depth, erosion, texture, stoniness, drainage) and chemical (EC, pH, CaCO₃, organic matter) criteria, weighted using both the Analytical Hierarchy Process (AHP) and FAHP. Geostatistical analysis characterized the spatial variability in soil properties across the study area. The two suitability maps were validated using Receiver Operating Characteristic (ROC) curves and Kappa statistics: the FAHP achieved higher prediction accuracy (AUC = 0.83, Kappa = 0.91) than the AHP (AUC = 0.81, Kappa = 0.88). The AHP-based map classified 40% (1154.92 km²) as moderately suitable (S2), 33% (952.81 km²) as marginally suitable (S3), and 27% (779.57 km²) as unsuitable (N); the FAHP-based map classified 42% (1212.67 km²) as S2, 30% (866.19 km²) as S3, and 28% (808.44 km²) as N. The proposed framework may serve as a reference for similar arid environments and support progress toward Sustainable Development Goals 2, 6, 8, 9, 11, 13 and 15, conditional on local soil, water, climate and management conditions. Full article

Within the framework of the dual carbon strategy, investigating the spatiotemporal characteristics and driving factors of carbon sequestration in metropolitan areas through land use analysis is important for mitigating climate change and promoting regional ecological protection and sustainable development. On the basis of land use time points for five phases from the Jinan metropolitan area (JMA) covering the period from 2000 to 2024, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was coupled with the extreme gradient boosting (XGBoost)–Shapley Additive exPlanations (SHAP) and multiscale geographically weighted regression (MGWR) models to explore the spatiotemporal variations in carbon storage and its driving factors. In the last 24 years, cropland has been the predominant land use category in the JMA, representing almost 62% of the overall area. Throughout the five periods, the transition from cropland to construction land predominated, resulting in an 11.78% reduction in farmland and a 49.73% expansion in construction land. Between 2000 and 2024, carbon storage in the JMA decreased overall, with a total reduction of 3.70 Tg. The occupation of farmland for construction purposes was the primary cause of the decrease in carbon storage. The spatial pattern of carbon storage was similar to that of land use in the JMA, characterized by a distribution pattern with elevated values in the southeast and reduced values in the northwest. The SHAP analysis results demonstrated that the contributions of driving factors such as elevation, vegetation coverage, human footprint, and population density were generally high, making them the main drivers affecting carbon storage, with a significantly greater contribution of natural factors than human activity factors. The MGWR model results revealed that the digital elevation model and fractional vegetation cover positively influenced carbon storage in the JMA, whereas the population density imposed a negative effect. These results could guide the judicious allocation and utilisation of resources in urban regions, the establishment of ecological conservation areas, and the advancement of regional sustainability. Full article

To support groundwater protection and sustainable utilization in southern Sichuan, this study aims to clarify the multi-year variation characteristics of groundwater levels (GWLs) and identify their main driving factors in the Yibin region. In this paper, 2019–2024 GWL monitoring records, hydrometeorological data, and multi-source geospatial datasets were integrated. Trend analysis, centroid migration modeling, continuous wavelet transform, Geodetector, and Fast Fourier Transform-based cross-correlation analysis were used to examine GWL dynamics and their controlling factors. The results show that GWL depth exhibits a distinct “shallow-northwest to deep-southeast” pattern, which is closely associated with regional aquifer lithology and hydrogeological conditions, with the most pronounced fluctuations occurring in the northwest. From 2019 to 2024, GWLs showed multi-scale periodic oscillations, with dominant periods of 50–64 months. GWLs in the red-bed region showed a continuous and slow decline, whereas those in the carbonate rock region remained relatively stable with a slight decreasing trend. Among the 13 hydrometeorological, geographic, and human activity factors, cropland area and precipitation had the strongest individual explanatory power. Their interactions with other factors produced nonlinear or bi-factor enhancement effects. The sustained expansion of cropland, together with declining precipitation, suggests that the observed phased and gradual decline in GWLs during 2019–2024 may be associated with a combined climate–human activity forcing mechanism. Annual GWL peaks were weakly and positively correlated with rainfall and temperature, while the lag between rainfall infiltration and GWL response varied with lithology. Full article

Snow disasters constitute a major natural hazard in Northwestern China, where heavy snowfall, blowing snow, and avalanches pose significant threats to infrastructure and socioeconomic activities. A scientific assessment of regional snow disaster risk is therefore critical for disaster prevention, spatial planning, and sustainable development. This study integrates multi-source remote sensing and geographic data to develop a comprehensive risk assessment method. By entropy weight method (EWM), we construct an assessment model that quantifies the combined hazard potential of heavy snowfall, blowing snow, and avalanches. The results reveal a significant spatial correlation among the three primary hazard types. The average potential hazard intensity of heavy snowfall is greater than that of blowing snow, which in turn exceeds that of avalanches. Spatially, the comprehensive snow disaster risk is most severe in the Altai Mountains, the Ili River valley, and the Tacheng region. A moderate-to-high risk level is distributed across the southwestern valleys and the foothills of the northeastern mountains. In contrast, the lowest risk areas are concentrated in certain interior valleys and the leeward slopes of the Junggar Basin. The resulting regional risk zoning was evaluated using receiver operating characteristic (ROC) curve analysis and disaster records. The model achieved an area under the receiver operating characteristic curve (AUC) of 0.871 and an overall accuracy of 84.3%, indicating good spatial discrimination between high- and low-risk zones. These metrics support the application of the framework to regional snow disaster risk assessment. Full article

Mediterranean agriculture is increasingly constrained by severe and recurrent water scarcity. Rising temperatures, declining precipitation, and more frequent droughts are driving higher crop water demand and reducing rainfall reliability. Combined with growing competition for limited freshwater resources, these climatic pressures pose a major challenge to the long-term sustainability and productivity of farming systems in the region. In this context, urban treated wastewater (UTWW) is increasingly recognized as a strategic alternative resource. Regulation (EU) 2020/741 establishes minimum quality requirements for agricultural water reuse based on the fit-for-purpose principle. The Italian regulatory framework requires regional authorities to plan water reuse by mapping reclamation facilities, water demand, and distribution networks. From this perspective, to support the planning process, this study describes the application of a Geographic Information System (GIS)-based methodology to assess the potential for UTWW reuse in Sicily by integrating national datasets (regularly updated) and comparing reclaimed water supply with irrigation demand from both qualitative and quantitative perspectives. UTWW supply was estimated by integrating data from the Italian National Institute of Statistics (ISTAT) Census of Water for Civil Use and the European Environment Agency (EEA) dataset, while irrigation demand was derived by combining Copernicus crop data, ISTAT irrigated-to-total UAA ratios and crop-specific irrigation demand (Seasonal Specific Volumes) derived from the SIGRIAN database. Two scenarios were analyzed for grasslands, vineyards, olive groves, and orchards. Scenario 1 included only wastewater treatment plants (WWTPs) located inside irrigation areas, whereas Scenario 2 also included selected WWTPs located outside irrigation areas where orographic and distance constraints allowed potentially feasible connections. Under Regulation (EU) 2020/741, potential compatibility with the required water quality classes was identified at the screening level for all crop categories considered, which require classes B, C or D. From a quantitative perspective, Scenario 1 identified 19 WWTPs serving 11 out of 38 irrigation areas with an aggregated uncapped demand coverage of 53%; only two areas reached full local demand satisfaction. Scenario 2 added 23 external WWTPs, increased potentially served areas to 20, and raised the aggregate uncapped coverage to 73%. When surplus volumes were capped within each irrigation area, effective demand satisfaction was 12% and 22% in Scenarios 1 and 2, respectively, highlighting the importance of storage, conveyance and inter-area transfer. The results indicate that treated wastewater reuse could contribute to agricultural water security and climate-resilient water management in Mediterranean regions. The framework supports the first-order identification of candidate reuse areas, but site-specific assessments of effluent quality, risk management, costs, and seasonal storage remain necessary before implementation. Full article

This study aims to spatially analyze the potential soil loss rates of the Özkonak Watershed, located within Nevşehir Province, using the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information Systems (GIS) and Remote Sensing (RS) technologies. In the 149.9 km² watershed, the main parameters triggering erosion—rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), land cover and management (C), and support practices (P)—were modeled in a GIS environment. According to the spatial analysis results, 85.8% of the watershed area falls within the “very low” and “low” erosion susceptibility classes. Nevertheless, erosion increases markedly in the northern areas with high slope gradients and in areas where agricultural activities are concentrated. The mean soil loss across the watershed was calculated as 2.75 t ha⁻¹ yr⁻¹. The eroded and transported material was determined to constitute a threat to the dam. The findings indicate that conservation plans, including afforestation in the upper watershed, adjustment of land use to natural land capability, and construction of check dams, should be implemented to ensure sustainable management of the watershed. From a soil and sediment remediation perspective, the identification of erosion-source areas and sediment-transport pathways provides a scientific basis for source-control measures aimed at reducing sediment delivery and associated water-quality deterioration in the Bayramhacılı Dam reservoir. Full article

Background/Objectives: Cardiac arrest and fluid, electrolyte, and acid–base disorders frequently coexist in critically ill patients and are associated with poor clinical outcomes. However, long-term population-level trends in mortality involving both conditions remain poorly characterized. This study evaluated temporal trends and demographic disparities in mortality involving cardiac arrest and fluid, electrolyte, and acid–base disorders among U.S. adults from 2004 to 2024. Methods: We conducted a retrospective population-based study using the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Multiple Cause of Death database. Adults aged ≥25 years with cardiac arrest (ICD-10: I46) and fluid, electrolyte, and acid–base disorders (ICD-10: E87) listed anywhere on the same death certificate between 2004 and 2024 were included. Age-adjusted mortality rates (AAMRs) were calculated using the 2000 U.S. standard population. Joinpoint regression was used to estimate annual percent change (APC) and average annual percent change (AAPC), with analyses stratified by demographic and geographic characteristics. Results: A total of 152,937 deaths involved both cardiac arrest and fluid, electrolyte, and acid–base disorders during the study period. The AAMR nearly doubled, increasing from 2.06 (95% CI, 2.00–2.13) in 2004 to 4.08 (95% CI, 4.00–4.16) in 2024, corresponding to an overall AAPC of 3.42% (95% CI, 2.58–4.26; p < 0.001). Mortality remained consistently higher among males, adults aged ≥65 years, and non-Hispanic Black individuals, with significant increases observed across all demographic groups. The West demonstrated the highest regional mortality burden (AAPC, 3.75%; p < 0.001). Urbanization analyses (2004–2020) showed higher mortality in non-metropolitan than metropolitan areas (AAPCs, 5.36% vs. 4.13%; both p < 0.001). Mortality increased through 2021 before declining modestly during 2021–2024. Conclusions: Mortality involving both cardiac arrest and fluid, electrolyte, and acid–base disorders increased substantially in the United States over the past two decades, with persistent disparities in age, sex, race/ethnicity, and geography. These findings identify populations at increased risk and support targeted public health strategies, equitable healthcare access, and improved recognition and management of metabolic disturbances in patients at risk for cardiac arrest. Full article

Rural logistics networks face the dual challenge of improving service reliability while maintaining long-term cost efficiency. Drawing on the resource-based view and transaction cost economics, this study examines how cold chain coverage and intelligent sorting contribute to the operational sustainability of urban–rural logistics and whether joint distribution conditions these relationships. Using monthly panel data from 150 outlets within a Chinese postal network from 2017–2023, we estimate outlet and time fixed-effects models with interaction terms. The results show that greater cold chain coverage and intelligent sorting penetration are associated with higher delivery success rates and lower unit delivery costs. However, joint distribution intensity weakens both the service-quality benefits and the cost-reduction effects of these investments, suggesting that cross-organizational coordination may constrain the conversion of specialized and technological resources into operational performance. Further heterogeneity analyses reveal that these performance improvements are concentrated in agricultural counties and geographically concentrated service areas, highlighting the importance of local demand characteristics and network conditions in determining the returns to logistics investment. The findings highlight the importance of aligning infrastructure investment, digital upgrading, and inter-organizational governance with local demand and network conditions. Full article

Deep learning-based vessel trajectory prediction using Automatic Identification System (AIS) has become a hot topic in the fields of maritime traffic monitoring, situational awareness, and navigational decision support. However, most previous studies have focused primarily on end-to-end model training using trajectory data from a single water area, which limits the resulting models’ ability to generalize to regions with different traffic patterns. To address this issue, this study proposes a method that constructs traffic context from historical AIS records at multiple geographic resolutions using H3, a hexagonal hierarchical spatial indexing system, and integrates this context with a Transformer-based trajectory predictor. A reliability-aware selector determines the contribution of the context to the final prediction, conditioning this decision on the vessel’s motion state and the retrieved historical patterns. Experiments on AIS data from three distinct water areas demonstrated that H3-indexed context improved cross-water prediction accuracy without requiring model retraining on the target area. These findings demonstrate that H3-indexed context, structured at multiple geographic resolutions and integrated through a selective mechanism, serves as transferable spatial context for vessel trajectory prediction. Full article

Many law enforcement agencies operate crisis service models that utilize the expertise of mental health professionals in assisting law enforcement officers (LEOs) when interacting with people experiencing a mental health crisis. This study examines three agencies with two different types of established crisis service models in the same geographical area to answer three research questions: (1) Does the type of crisis service model affect facilitators of success for the model? (2) Does the type of crisis service model affect how practitioners personally measure the success of the model they use? (3) What patterns exist in involuntary psychiatric examination rates before and after the implementation of the crisis service models? Sixteen practitioners representing two crisis service models responded to a survey investigating the first two questions. Participants were recruited through email. The analysis used inferential and descriptive statistics to examine their responses. A before-and-after design using descriptive statistics of publicly available data about involuntary psychiatric examinations was employed to investigate the third research question. Results showed variation across the model participants’ choices of facilitators important for model success and metrics, but only differences between the responses from members of two models in choosing the facilitator of clear policies and procedures (e.g., clearly written protocols) and the metric of use of force were at statistically significant levels. The practitioners of the models are the experts. Understanding how they judge the success of their work and what facilitates that success is vital for allocating resources effectively and adjusting policies as needed. The study determined that involuntary psychiatric examinations decreased concurrently with the use of crisis service models, but it is not possible to establish causation. More investigation is needed. Full article