Search Results (28,396)

Land use change is the most direct factor driving the supply and alteration of ecosystem services. This study employed the Dyna-CLUE tool to simulate future land use distributions under two scenarios—the Constrained Trend (CT) and Optimized Target-driven (OT) scenarios—based on land use data from 2010. Subsequently, their corresponding ecosystem service values (ESVs) were calculated, with the simulation outcomes revealing distinct land use layouts under each scenario. Under the CT scenario, grassland and urban areas expanded, whereas farmland and water bodies declined, reflecting a trend of urbanization at the expense of rural landscapes. In contrast, the OT scenario demonstrated a cessation of built-up land expansion, accompanied by marked increases in forest and water coverage, changes that facilitated the restoration of coastal watersheds, enhancing wetland provision and improving overall ESV. Consequently, per capita ESV increased substantially—from 1751 CNY in 2018 to 2356 CNY, matching the 2010 level—primarily due to the conversion of grasslands and farmlands into forests and wetlands. The OT scenario also improved the spatial distribution of ESVs, forming interconnected ecological zones around urban areas. The results underscore that policies restraining built-up expansion, promoting afforestation, and restoring wetlands can significantly improve ecosystem services and contribute to sustainability. Full article

In intelligent transportation systems and urban traffic management, accurate vehicle area intrusion detection based on surveillance imagery plays a critical role in ensuring road safety and operational efficiency. However, under real-world road surveillance conditions characterized by complex backgrounds, varying illumination, occlusion, and scale variations, mainstream detection algorithms often suffer from high false detection and missed detection rates, limiting their reliability and practical deployment. To address these challenges, this paper proposes YOLOv10-Intrusion, a high-precision vehicle area intrusion detection framework based on an improved version of YOLOv10s. The proposed algorithm incorporates Omni-Dimensional Dynamic Convolution (ODConv) and a custom-designed RCS_M module to enhance feature extraction and fine-grained recognition capability. In addition, a Bidirectional Feature Pyramid Network (BiFPN) is employed to optimize multi-scale feature fusion at the neck level. These improvements collectively reduce false detections and missed detections while improving model recall and mean Average Precision (mAP). Furthermore, the Wise-IoU (WIoU) loss function replaces the original Complete IoU (CIoU) loss to accelerate convergence and stabilize bounding box regression under complex surveillance conditions. A dedicated vehicle area intrusion dataset is constructed from real-world road surveillance footage, covering five vehicle categories across diverse road environments and lighting conditions. Experimental results demonstrate that, compared with the baseline YOLOv10s, YOLOv10-Intrusion achieves improvements of 1.5, 3.3, 3.6, and 2.8 percentage points in Precision, Recall, mAP@0.5, and mAP@0.5:0.95, respectively, and outperforms other mainstream detection algorithms in vehicle area intrusion detection tasks. Full article

Most of the dam structures around the world are approaching the end of their economic life of 50 to 70 years, especially due to sediment accumulation in reservoir areas. This situation necessitates the development of proactive infrastructure management strategies. This study presents an original framework for the process of renewal of aging dams that blends remote sensing techniques and meta-intuitive optimization methods. Within the scope of the study, the Hasanlar Dam located in Düzce was selected as a sample, and a new dam axis was determined in the upper part of the basin. A detailed volume–height curve was created using 12.5 m resolution ALOS PALSAR numerical height models (DEM) and GIS-based spatial data curation to calculate the reservoir storage capacity in precise increments of 2 m. To maximize the structural efficiency of the proposed “New Hasanlar Dam”, the cross-sectional area has been minimized through seven current algorithms such as Genetic Algorithm (GA), Arithmetic Optimization Algorithm (AOA), Gray Wolf Optimizer (GWO), Dragonfly Algorithm (DA), Particle Swarm Optimization (PSO), Crayfish Optimization Algorithm (CAO), and Cheetah Optimizer (CO). The findings obtained prove that the PSO and CAOs achieved a significant reduction in cross-sectional area by 29.36% and successfully approached the global optimum. The replacement of the 55.5 million m³ capacity of the existing Hasanlar Dam with a new structure with a height of 78 m will guarantee sustainability and structural safety in water management. As a result, this study reveals that the integration of high-resolution remote sensing data and advanced heuristic methods is a cost-effective and powerful tool in the strategic renovation of aging hydraulic infrastructures. Full article

Stadiums are large buildings that attract attention due to their high energy consumption and environmental impact. Considering the effects of climate change, the integration of sustainable energy solutions and energy efficiency is of great importance in the design and planning of these buildings. This study focuses on pitch lighting, which accounts for a significant and fluctuating share of energy consumption in stadiums, and aims to reduce its carbon footprint through the integration of renewable energy. This study aims to analyze the feasibility of achieving a net-zero annual energy balance for different levels of field lighting of a football stadium in accordance with FIFA lighting standards with solar energy systems in different climate zones and under future climate change scenarios. In addition, it is aimed at revealing the effect of climate change scenarios and climate zone differences on the azimuth angle, tilt angle, and area of the solar panel. In the study, a stadium model was created using parametric design—Grasshopper—and optimization software; lighting systems were designed according to FIFA standards, and lighting performance on the field was optimized with simulations through ClimateStudio and Galapagos. Based on Liverpool FC’s home match data, the annual illumination time is calculated, and the azimuth angle, tilt angle, and area of the solar panel systems are optimized for different climate scenarios. The most useful result of this study is that it demonstrates that the solar panel area required to meet stadium lighting needs varies depending on climate scenarios and geographical conditions and that the same energy production can be achieved with less panel area in low-emission scenarios. For instance, simulation results for Liverpool under the RCP 2.6 scenario show a decrease in the required panel area from 86.09 m² in 2050 to 84.27 m² by 2100. Similarly, in Moscow for the year 2050, the medium-emission scenario (RCP 4.5) requires a larger panel area (92.22 m²) compared to the low-emission RCP 2.6 scenario (88.12 m²) to achieve the same energy output. Full article

The watershed boundaries in arid and semi-arid regions are critical zones where ecological vulnerability and socio-economic development are in severe conflict. The upper and middle reaches of the Yellow River basin are a typical example of this dilemma. Intensive land use and human developmental interventions in this region have severely disrupted the integrity and balance of the ecosystem. While spatially designated, networked conservation areas can effectively promote the integrity and balance of regional ecosystems, these areas may fail to capture dynamic changes in vulnerability. This study develops a “functional diagnosis-structural diagnosis-integrated optimization” framework. It integrates various scenarios to diagnose vulnerability under uncertainty and identifies bottlenecks in ecological networks. For functional diagnosis, the coupling of the sensitivity–resilience–pressure (SRP) model and the Ordered Weighted Averaging (OWA) algorithm accurately locates vulnerable areas within the regional ecosystem. In terms of structural diagnosis, the Morphological Spatial Pattern Analysis (MSPA), Minimum Cumulative Resistance model (MCR), and Circuit Theory are integrated to identify structural bottlenecks. The main findings of this study are as follows: (1) Functional Diagnosis: The coupling of SRP and OWA reveals the non-linear vulnerability responses to policy preferences and identifies areas that consistently exhibit functional vulnerability across different scenarios. (2) Structural Diagnosis: The circuit theory combined with MSPA and MCR analysis identifies 72 ecological pinch points. These bottlenecks represent the weakest structural nodes crucial for maintaining regional ecological robustness. (3) Coupled Delineation and Differentiated Restoration Strategies: High vulnerability areas identified by SRP and consistently vulnerable areas identified by OWA are combined to delineate four distinct ecological restoration units: Alpine Fragile Matrix Unit, Loess Hilly Soil Conservation Unit, Anthropogenic Pressure Pinch Point Unit, Key Structural Stepping Stone Unit. Differentiated ecological restoration strategies are proposed based on the varying sensitivity, resilience, and pressure characteristics of these units. The “functional-structural” coupled ecological vulnerability evaluation framework can precisely identify vulnerable areas. The delineated restoration units and their corresponding restoration strategies provide reference and supplementation for the protected areas system, offering transferable tools for enhancing regional ecological efficiency. Full article

Photovoltaic (PV) performance in desert environments is significantly hindered by soiling and partial shading. To bridge the gap in empirical data for extreme Saharan conditions, this study presents a novel techno-economic assessment of uniform horizontal shading (UHS) specifically conducted in Mauritania. Controlled outdoor experiments were performed using a 250 W crystalline silicon PV module and a PVPM 2540C I–V curve tracer, applying progressive shading levels from 2.5% to 20%. The novelty of this work lies in the integration of high-resolution experimental I–V/P–V characterization with a localized techno-economic model for five pre-commercial PV plants. It was observed that PV modules are exceptionally sensitive to shading; specifically, a mere 10% shaded area leads to a catastrophic 90% drop in power and current, while the voltage remains remarkably stable. Thermographic analysis further validates the thermal gradients and bypass diode functionality. By quantifying the financial impacts, this research highlights that cumulative economic losses across the five real-world sites reached 87.95%, exceeding 55,000 MRU. These findings provide a strategic framework for optimizing PV systems in arid terrains and offer a robust tool for enhancing the design and operation of large-scale solar applications in desert environments. Full article

The Qilian Mountains serve as a crucial ecological security barrier in western China, and the soil structural stability of alpine meadows directly affects regional ecological security and the sustainable utilization of grasslands. However, current research on grazing mostly relies on short-term artificially controlled experiments, which differ greatly from the pattern of long-term natural grazing. Herein, this study abandoned the artificially controlled grazing method and selected sampling areas with stable grazing regimes for more than a decade. Taking no grazing (CK) as the control, four treatments were established, including light grazing (LG), moderate grazing (MG), heavy grazing (HG) and extreme grazing (EG). The particle size distribution and stability of mechanically stable and water-stable soil aggregates in different soil layers were determined. Combined with environmental and biological factors, the effects of grazing on the structure and stability of soil aggregates were elucidated. The results showed that no grazing improved the mechanical stability of soil aggregates but reduced their water stability. Light and moderate grazing maintained a balanced and resistant soil structure, with the surface soil being more fragile than the subsurface soil. Heavy and extreme grazing led to severe structural degradation, with the subsurface soil being more fragile than the surface soil. Soil aggregate stability was jointly regulated by elevation, soil properties, root biomass, nitrogen forms, mineralization and microbial biomass. In conclusion, from the perspective of soil structural stability and sustainable utilization, light and moderate grazing represent the optimal utilization mode for the alpine meadows of the Qilian Mountains. This mode not only maintains the structural stability of subsurface soil aggregates but also balances biological cementation and physical disturbance, thus avoiding the insufficient water stability under no grazing and the risk of structural fragmentation under heavy or extreme grazing. Environmental and biological factors mediated the divergent responses of mechanical and water stability to different grazing intensities. The findings of this study provide a scientific basis and new insights for the rational grazing management and soil conservation of alpine meadows in the Qilian Mountains. Full article

Membrane technology demonstrates broad prospects in the field of methane capture and purification due to its high efficiency and low energy consumption characteristics. This paper systematically reviews the research progress in membrane technology for methane separation in recent years, focusing on the design and optimization of membrane material systems, in-depth analysis of mass transfer mechanisms, and practical applications in areas such as biogas upgrading and natural gas decarbonization. Researchers have significantly enhanced membrane separation performance for CO₂/CH₄, CH₄/N₂, and other systems by developing novel material systems such as polymer membranes, inorganic membranes, and mixed matrix membranes (MMMs), combined with strategies like pore structure regulation, interface optimization, and functionalization. Although membrane technology has shown good economic feasibility and application potential in some scenarios, challenges such as long-term material stability, anti-plasticization capability, and large-scale manufacturing remain the main current obstacles. Future research should further focus on the development of novel membrane materials, process integration optimization, and intelligent process control to promote a greater role for membrane technology in the efficient utilization of methane resources and energy structure transformation. Full article

Rising urban temperatures have become a critical constraint to urban ecosystem resilience and livability due to rapid urbanization. This study proposes a novel intra-city zoning scheme, named component morphological blocks (CMBs), which classifies built-up areas into six types characterized by multidimensional urban canopy morphologies. The XGBoost-SHAP model, optimized via Bayesian tuning, was employed to examine the relative contributions of 16 potential driving variables to block-scale land surface temperature (LST). The results show that: (1) LST gradually increases with increasing building density in the warm seasons. The average building height (BH) exhibits a positive correlation with shaded area, thereby reducing LST on the block scale; (2) hotspots are mainly concentrated in function-oriented blocks with hotspot distribution indices of 1.85, 1.96, 1.24, and 1.14, respectively. Coldspots are largely observed in blue–green space in the warm seasons; (3) BH dominates the LST across seasons, while the building-related factors make a prominent impact on LST in warm seasons. The contribution of vegetation canopy density is followed by BH during autumn and winter (12.2%, 10.9%); (4) a distinct transition occurs between summer normalized difference built-up index (NDBI) and fractional vegetation cover around an NDBI of 0.1. In winter, the interaction between 2D and 3D vegetation factors indicates a shift in their relative contributions from negative to positive as they increase. This study demonstrates that CMBs serve as an effective choice for characterizing LST patterns at the block scale, providing insights for sustainable urban development aimed at mitigating the urban heat island effect. Full article

As a novel approach to address the lack of systematic studies on spatial Gross Ecosystem Product (GEP) accounting and Ecological Security Pattern construction, this study integrates GEP thresholds with Morphological Spatial Pattern Analysis (MSPA) to identify ecological sources. A resistance surface is constructed using five representative influencing factors, and the Minimum Cumulative Resistance (MCR) model is applied to extract ecological corridors, thereby establishing the Ecological Security Pattern for the Yellow River-Fronting Region of Henan in 2020. The results indicate the following: (1) GEP in the study area exhibits a spatial distribution of “high in the northwest, low in the southeast,” with regulating services accounting for more than 90% of the GEP. (2) A total of 11 ecological sources, 13 ecological corridors, and 7 ecological nodes were identified, primarily distributed in mountainous regions. (3) The Ecological Security Pattern exhibits spatial imbalance, with dense corridors in the western mountains and sparse distribution in the eastern plains. These findings provide scientific support for formulating ecological conservation measures and optimizing ecosystem management in the Yellow River Basin. Full article

Ground subsidence and shaft lining deformation caused by compressed dewatered bottom aquifers in deep unconsolidated strata mining areas are critical engineering challenges, making the study of the seepage–soil deformation coupling mechanism during groundwater injection remediation vital. This study built a visual cylindrical model (1025 mm × 150 mm); formulated well-graded analogous materials based on the D₂₀ principle to simulate sandy gravel layers; embedded FBG sensors at 200/400/600 mm depths, combined with a dial indicator on the model top; and conducted two water injection–dewatering cycles. Results indicate: water injection generates excess pore water pressure, placing the entire model in a tensile stress state with top rebound; post-injection vertical stress redistributes (tension above the injection point, compression below, and an interlaced transitional band), validating the necessity of full-section injection; during the second injection–dewatering cycle, tensile strain at the upper monitoring point reaches 597.77 με, while compressive strain at lower depths reaches −253.90 με, internal deformation stabilizes within 6.5–10.0 days, injection improves the in situ stress state by reducing effective stress, and the deformation of the field strata remains in a stabilization period, with the stabilization time decreasing as the depth of the strata increases. This study clarifies the temporal evolution and representative spatial variation in internal strain at monitored depths during injection, providing theoretical and design references for optimizing water injection schemes to mitigate coal mine shaft damage. Full article

Urban mental health is increasingly influenced by daily environmental exposures, yet limited empirical evidence exists regarding how the spatial configuration of blue–green environments, rather than their mere quantity, relates to emotional behavior in high-density cities. Guided by restoration theories and a perception-based perspective on landscape integration, this study analyzes the urban core of Shanghai by linking blue–green configurations to emotional states inferred from 20,907 geotagged social media facial photographs. Facial expressions serve to derive indices for emotional valence and arousal. The results demonstrate significant spatial clustering of emotional behavior, where hotspots are concentrated in higher-quality and more open settings, while coldspots cluster in dense areas with sparse vegetation. Emotional behavior also exhibits demographic heterogeneity, as females display higher valence and arousal than males. Furthermore, happiness tends to increase with age across both genders, whereas arousal declines specifically among male age groups. Crucially, emotional outcomes align more consistently with landscape integration and configuration than with isolated blue or green areas. Factors such as high connectivity, superior vegetation condition, and configurations featuring water embedded within green space are associated with favorable emotional responses. Conversely, extensive edge-dominated interfaces and high traffic exposure correlate with less favorable outcomes. These findings suggest a shift in blue–green planning from increasing total area toward optimizing spatial composition. Specifically, priority should be given to embedded and cohesive designs alongside the reduction of ambient stressors to foster emotionally supportive environments in dense urban cores. Methodologically, image-derived behavioral traces provide a scalable and ecologically grounded approach for investigating place-based affect at a city scale. Full article

Exit location can influence evacuation efficiency without changing the number of exits, yet its mechanism lacks quantitative characterization. Using a complex single-floor hospital outpatient department floor plan with 186 occupants as the case study, based on a direction-aware cellular automaton (CA) model, this study constructed two exit layout scenarios within the same complex building floor plan and independently repeated 50 simulations for each scenario under identical occupant population and model parameters. A mechanism-oriented analysis was conducted from the perspectives of evacuation efficiency, structural fairness, behavioral fairness, and structure–behavior deviation. The results showed that, in this case, exit relocation shortened the total evacuation time by approximately 20% ($p<0.001$) and significantly reduced the concentration of exit utilization, whereas the service area distribution changed only slightly, and local peak density did not increase significantly. This indicates that exit location improves evacuation efficiency by restructuring the crowd-splitting structure rather than by a simple balancing of structural service coverage. This study provides quantitative evidence for performance-based evacuation design and sustainable safety optimization in complex spaces. Full article

Cane density is a key management factor in raspberry production, directly affecting yield formation and canopy structure. However, most previous studies have focused on floricane cultivars and relied on conventional field measurements, while the response of primocane raspberries and their canopy level dynamics remain less explored. The objective of this study was to evaluate how cane density influences yield components, cane growth, and canopy structure in primocane raspberry cultivars, and to assess whether these effects can be captured using UAV-based multispectral imaging. Field experiments were conducted over two growing seasons using two primocane cultivars grown under different cane density treatments. Yield components and cane growth parameters were measured, and repeated drone multispectral surveys were performed during the production period to quantify the spatial and temporal variability of vegetation indices. Increasing cane density led to higher total yield per unit area in both cultivars, mainly through an increase in fruit number rather than fruit weight, indicating a compensatory yield response. Cane density significantly modified canopy architecture, with responses varying between cultivars and seasons. Multispectral vegetation indices revealed predominantly consistent density-dependent gradients, characterized by higher mean values and reduced spatial and temporal variability at higher cane densities. Denser cane configurations were associated with lower total temporal amplitude and smoother seasonal trajectories, indicating a stabilization of canopy reflectance dynamics. Although this overall pattern was preserved across indices, the magnitude and regularity of temporal responses were index-specific and cultivar-dependent. The results demonstrate that cane density management in primocane raspberries affects both yield formation and canopy structure, and that these effects can be effectively monitored using UAV-based multispectral imaging. Integrating remote sensing with field measurements offers a valuable approach for supporting data-driven optimization of raspberry production systems. Full article

The Navel Orangeworm (Amyelois transitella Walker, 1863), a primary pest of nut crops native to North America, poses a significant potential threat to China’s agricultural biosecurity, yet its potential distribution dynamics under climate change remain unquantified. This study utilized the Biomod2 ensemble model platform to predict habitat suitability under current and future climate scenarios (SSP1-2.6 and SSP5-8.5). We evaluated the prediction accuracy of the ensemble model using calibration data, with TSS = 0.898 and AUC = 0.978, while spatially stratified cross-validation confirmed moderate spatial transferability to novel environments (median validation AUC = 0.60–0.75). The model identified thermal factors—Temperature Seasonality (Bio4) and the Mean Temperature of the Wettest Quarter (Bio8)—as the dominant drivers of distribution. While currently climatically suitable habitats are primarily confined to the tropical and subtropical regions of southern China, projections indicate a complex spatial shift driven by future warming: optimal southern habitats will undergo a net contraction due to heat stress, whereas low and moderately suitable areas will expand northward into key temperate agricultural areas. These results highlight that climate change will substantially alter the spatial topology of the pest’s climatic envelope, providing a critical scientific baseline of climatic suitability. These projections do not equate to realized invasion risk, which is further constrained by host availability, land use, irrigation, and human transport, offering a conservative framework for prioritizing early surveillance and optimizing quarantine measures. Full article