Search Results (2,397)

Satellite active-fire products may miss fires that occupy only a small fraction of a pixel and produce limited absolute thermal responses. In this study, weak thermal anomalies are operationally defined as confirmed fire-affected VIIRS pixels with relatively low absolute $B{T}_4$ and $\mathsf{\Delta }BT$ responses but positive deviations from their recent temporal and local spatial backgrounds. STAR-FD (Stratified Spatiotemporal Adaptive Residual Fire Detection) was developed to detect such anomalies from VIIRS 375 m observations. The method reconstructs a 14-day recent thermal background and jointly evaluates single-pixel temporal residuals and spatial-contrast temporal residuals. Stable non-fire samples are stratified by day/night condition, season, macroclimate zone, land cover, and view zenith angle, and residual thresholds are estimated within each stratum. Validation was conducted in Heilongjiang, northwestern India, and California using Sentinel-2 MSI, Landsat 8/9 OLI, and available external fire information. STAR-FD detected 927 overpass-level thermal-anomaly events, of which 855 were confirmed as Fire, corresponding to a confirmation rate of 92.23%. VNP14IMG detected 343 events, of which 333 were confirmed as Fire (97.08%). STAR-FD identified 522 more confirmed fire-related thermal-anomaly events than VNP14IMG, corresponding to a 156.76% increase, while retaining 88.05% of VNP14IMG events. In northwestern India and Heilongjiang, STAR-FD-added daytime confirmed fire pixels had median $B{T}_4$ values 9.49 K and 11.88 K lower, respectively, and median $\mathsf{\Delta }BT$ values 8.10 K and 10.78 K lower than detections shared by both methods. These results show that STAR-FD provides complementary detection of confirmed fire-related thermal anomalies with weaker absolute thermal signals. Full article

Páramo ecosystems are among the most biodiverse and hydrologically critical landscapes on Earth, yet their long-term sustainability is increasingly threatened by climate-driven wildfires. Vegetation Cover Fires (VCFs) in these high-altitude environments degrade carbon stocks, disrupt freshwater regulation, and undermine biodiversity conservation goals central to the UN Sustainable Development Goals (SDGs 13, 15, and 6). Between 2001 and 2023, 128 fire events consumed approximately 815 ha in the Sumapaz locality (the world’s largest continuous páramo), representing 64.9% of all fires recorded across Bogotá’s 20 localities. Despite this disproportionate ecological and social impact, no spatially explicit, operational risk management framework has been available for the region, representing a critical sustainability governance gap. This study addresses that gap by proposing an integrated climate-adaptive risk assessment and management strategy based on (i) the Canadian Forest Fire Danger Rating System Fire Weather Index (FWI), derived from ERA5 reanalysis climate data; (ii) spatial and temporal hotspot analysis of MODIS FIRMS active fire detections; and (iii) IDEAM’s multi-component vulnerability and threat scoring protocol. Spatial data were processed using ArcGIS, and FWI sub-indices were computed for each month of the 2001–2023 period. The FWI averaged 0.78 (low danger) across the study period yet peaked at 13.7 in February 2010 (moderate-to-high danger), consistent with the year of highest recorded fire activity (19 events). High- and very high-risk areas (3.70% combined) coincide with slopes >25%, the presence of the invasive and pyrogenic Ulex europaeus, and proximity to populated and agricultural lands. This study concludes with a three-pillar risk management framework—risk knowledge, risk reduction, and disaster management—providing spatially targeted, operationally viable strategies for local and institutional actors that directly support the sustainable conservation of páramo ecosystem services (water supply, carbon sequestration, biodiversity). The framework is designed to be updatable on a monthly basis using freely available ERA5 data, enabling continuous adaptive governance of wildfire risk as a contribution to long-term territorial sustainability. Limitations regarding MODIS detection uncertainty, ERA5 spatial resolution in complex terrain, and the need for probabilistic modeling are explicitly acknowledged. Full article

Subway tunnels exacerbate fire hazards, revealing a critical lacuna regarding the spatio-temporal coupling of fire progression and human egress. To address this, this study proposes and validates an Integrated Spatio-Temporal Risk Assessment Model to explicitly quantify survivability thresholds under complex fire dynamics. The framework synergizes Large-Eddy Simulation (LES) based Computational Fluid Dynamics with agent-based pedestrian trajectory modeling within a 3D tunnel featuring a 2% longitudinal gradient. Evaluating 9.5 MW and 12 MW fire energies, the model assessed Single-Sided Evacuation (SSE), Double-Sided Evacuation (DSE), and Sprinkler-Assisted Single-Sided Evacuation (SSE-S) across 2160 agents. Hazards were quantified by continuously resolving Fractional Effective Dose (FED) indices, 60 °C boundaries, and 500 ppm CO fronts. Simulations reveal the gradient induces a severe stack effect, accelerating toxic dispersion and yielding temperatures exceeding 1200 °C. Consequently, SSE engendered fatal bottlenecks (FED: 15.33), whereas DSE optimized pedestrian flux, capping peak FED at 0.52. Crucially, while active suppression (SSE-S) extinguished flames within 105 s, thermodynamic cooling induced a paradoxical loss of smoke buoyancy, causing toxic layers to stratify at the breathing zone. Ultimately, while DSE and SSE-S are paramount for survivability, water-based suppression generates localized toxicological risks, necessitating the integration of low-level smoke detection and extraction architectures in future subterranean designs. Full article

Micron-sized spherical gold powders possessing high dispersibility and favorable sintering performance are critical for high-performance thick-film gold conductor pastes. Herein, monodisperse micron-sized spherical gold powders were fabricated through an environmentally benign chemical reduction route, where L-ascorbic acid served as the reductant and gum arabic acted as the dispersant. The influences of solution pH, reaction temperature, stirring speed and reaction time on particle morphology and size distribution were systematically explored. With the mass ratio of gold precursor to reductant maintained at 1:1, the optimal synthetic conditions were determined as pH 3, 20 °C, 550 rpm and 20 min. Under such optimized conditions, spherical gold particles with an average diameter of 0.88 μm were harvested, featuring narrow particle-size distribution, high sphericity, good dispersibility and low organic residue of 0.70 wt%. The as-prepared powder delivered high crystallinity and appropriate sintering activity. Quantitative porosity characterization demonstrated that the thick film derived from this micron-scale gold powder achieved the minimum residual porosity in comparison with the other two counterparts, verifying its outstanding densification behavior. Benefiting from the well-developed dense conductive network, the resultant thick film achieved a low sheet resistance of 1.73 mΩ/sq, a superior adhesion strength of 3.65 N/mm², as well as reliable multi-firing stability. This work offers a feasible approach for large-scale manufacturing of high-quality gold powders toward thick-film electronic devices. Full article

Understanding where and why wildfires occur is essential for assessing fire danger and supporting mitigation strategies. This study proposes a spatiotemporal map to represent wildfire activity and support fire danger assessment in two fire-prone regions: Central–North Portugal and the Paraná Delta, Argentina. Active fire observations spanning over 10 years were analyzed using spatial network theory and graph-based clustering to map regional patterns and identify persistent and emerging hotspots. To complement this, high-resolution Meso-NH simulations at 0.5 km resolution were conducted for selected events, including the Arouca and Trancoso fires in Portugal and two events in the Paraná Delta. The maps reveal that the central areas of both regions are the most fire-prone. Small areas in Portugal emerged as regions of increasing activity and potential future recurrence, while the Paraná Delta showed a progressive northward expansion of fire activity. The historical hotspot map was complemented by atmospheric conditions obtained from the numerical simulations to reflect meteorological fire danger. The high-resolution numerical simulations can provide key insights into areas with elevated danger, demonstrating that integrating Earth observation data and numerical modeling is highly effective for wildfire management and risk assessment. Full article

Understanding wildfire dynamics and their climatic and topographic drivers is essential for effective fire management in Southeastern Europe. This study presents the first long-term assessment of wildfire trends across different land-cover types in Bulgaria, providing a methodological framework that is applicable across the wider Balkan region using the FireCCI51 burned area dataset (2001–2022). Burned area patterns were analyzed in relation to temperature, relative humidity, precipitation, the Ångström Index, Vapor Pressure Deficit (VPD), and topographic conditions. Burned area declined across most land-cover types, particularly croplands and forests. Croplands accounted for 96.4% of the total burned area (4.9 Mha), while forests, grasslands, shrublands, and wetlands represented 3.6%. Burned area was positively correlated with temperature (r = 0.37–0.53) and VPD (r = 0.40–0.53), and negatively with relative humidity (r = −0.48 to −0.55) and the Ångström Index, highlighting the importance of atmospheric dryness for wildfire activity. Seasonal climate-fire analyses further indicated that burned-area variability was more strongly associated with climatic conditions during the peak fire season than during the pre-fire season, particularly through lower relative humidity and higher vapor pressure deficit values. Topographic analysis revealed clear partitioning across land-cover classes. Cropland and wetland fires were concentrated in flat, low-elevation landscapes (mean altitudes ~117 m and ~40 m; slopes ~3.36% and ~2.04%), while forest and grassland fires occurred in higher, steeper terrain (mean altitudes ~351 m and ~315 m; slopes ~14.25% and ~9.76%). Shrubland occupied an intermediate niche (mean altitude ~287 m; slope ~9.43%), statistically overlapping with both forest and grassland categories, and acting as a transitional zone between lowland agricultural plains and mountainous ecosystems. Fire activity showed a clear seasonal pattern, with the highest burned areas occurring in August, coinciding with maximum VPD and minimum Angström index values. These results highlight the important role of atmospheric dryness and temperature variability in shaping wildfire activity in Bulgaria and demonstrate the usefulness of long-term satellite burned-area datasets for regional fire monitoring that can be applied not only in Bulgaria but also across the Balkan region. Full article

This paper proposes a post-training structured channel pruning scheme leveraging Gradient-Weighted Class Activation Mapping (Grad-CAM) for few-class fire detection under limited computational resources. After standard training, category-specific gradient signals extracted from the detection heads are used to generate channel-wise class activation maps over multi-scale feature layers, and fire and smoke responses are fused to rank channel importance. A layer-level retention quota is further applied to implement structured channel pruning, followed by lightweight fine-tuning. The pipeline does not require additional sparsity-inducing training. We validate the method on a self-established fire and smoke dataset containing 9041 images, using YOLOv5s, YOLOv5m, and YOLOv5l as baseline detectors. In workflow-level comparisons, the proposed method achieved higher mAP@0.5 than the implemented L1-based workflow at 40% and 60% pruning, but not at 80%. At 60% pruning, the pruned YOLOv5s model contained 2.158 M parameters and required 2.901 GFLOPs. These results indicate that Grad-CAM provides a useful class-aware criterion for channel importance and offers a promising model-compression strategy for resource-constrained fire detection, although physical edge-device performance remains to be evaluated. Full article

Super-resolution (SR) of remote-sensing imagery is commonly assessed through spatial fidelity or visual sharpness, although index-based geomatics requires preservation of cross-band spectral relationships. We compare five Sentinel-2 full-band SR configurations (LDSR-S2, SRGAN, SPAN, Mamba, and SWIN) in two hazard-mapping cases: flood-water detection during the 2024 Valencia flood and burn-scar mapping after the 2025 Palisades wildfire. Each model refines four native RGB–NIR bands, while SEN2SR reconstructs the remaining bands to produce a ten-band product at $2.5$ m. We evaluate native-grid reconstruction, the introduction of high-frequency details, and downstream thematic, boundary, and edge-region metrics against a bilinear-interpolation baseline. Dynamic-threshold MNDWI and dNBR detectors are applied independently to each output. Among the learned configurations, SWIN achieves the strongest native-grid reconstruction and task-specific spectral consistency and the strongest fire agreement, but adds the least high-frequency content. Flood full-ROI gains are modest, with LDSR-S2 increasing the F1-score from 0.085 for bilinear interpolation to 0.091. All learned configurations increase flood-edge recall, F1-score, and IoU while reducing edge precision and balanced accuracy. LDSR-S2 gives the strongest final edge F1-score and IoU in both tasks, Mamba gives the lowest learned-model symmetric flood-boundary distance. SPAN yields the best spatial consistency and lowest learned flood-edge spectral error and SRGAN adds the most high-frequency content and the largest combined edge-region gain, alongside the greatest task-specific spectral deviation and the largest symmetric boundary-distance increases. Thus, increased edge activation does not establish uniformly improved delineation or recovered sub-pixel detail. These cases demonstrate feasibility rather than generalization. Operational validation requires more diverse, time-synchronous, high-resolution, spectrally compatible references. Full article

The demand for materials with flame-retardant and electromagnetic shielding properties has increased research on sustainable and multifunctional composites. Thermoset-based hybrid composites containing Fe₃O₄ and activated carbon obtained from solid waste were investigated for flame retardancy and electromagnetic shielding. Activated carbon produced by pyrolysis of buckwheat hulls (agricultural waste) exhibited a BET surface area of 714.33 m²/g and a conductivity of 69.5 S/m, and was used as a filler to enhance electrical conductivity, while Fe₃O₄ was added to promote electromagnetic absorption. Composites with 1, 3, 5 and 7 wt% activated carbon at a constant 15 wt% Fe₃O₄, together with a complementary series at 5 wt% activated carbon with 10, 15, 30 and 45 wt% magnetite, were characterized by limiting oxygen index and thermal analysis. LOI values clustered between 32.31% (Nov-5-15) and 33.71% (Nov-3-15), a 1.40-percentage-point spread around the 34.31% reference Novolac. The 850 °C char yield peaked at 56.38% (Nov-3-15) and 55.34% (Nov-7-15), with T₅₀% reaching 898 °C and 882 °C, respectively, while DTA replaced the 529 °C Novolac exotherm with endothermic Tmax values of 485–501 °C. Electromagnetic shielding effectiveness over the 8–12 GHz range varied from 2.97 ± 0.3 dB (unfilled Nov-0) to a maximum of 9.19 ± 1.46 dB (Nov-5-45, 5 wt% activated carbon and 45 wt% Fe₃O₄), with an intermediate value of 7.43 dB for Nov-7-15. These hybrids are thus candidate materials for fire-safe phenolic-thermoset applications, where magnetic–dielectric coupling and a percolated char-barrier network govern flame-retardant performance, demonstrating the potential of waste-sourced carbon in sustainable composite production. Full article

Elemental mercury (Hg⁰) removal in coal combustion flue-gas over commercial V-based SCR catalysts is still limited by insufficient low-temperature activity and the complex interference of gas components. In this work, V₂O₅/TiO₂, V₂O₅⁻MoO₃/TiO₂, and V₂O₅⁻MoS₂/TiO₂ catalysts were comparatively investigated for Hg⁰ removal under simulated coal combustion flue-gas conditions. Among them, V₂O₅⁻MoS₂/TiO₂ exhibited the best performance over the whole temperature window of 200–400 °C, reaching a Hg⁰ removal efficiency of 73.3% at 200 °C, which was markedly higher than those of V₂O₅/TiO₂ and V₂O₅⁻MoO₃/TiO₂. Under multicomponent SCR atmospheres in coal-fired plants, the catalyst also showed the highest Hg⁰ oxidation efficiency of 72.9%, indicating that MoS₂ modification was more effective than oxide promotion in enhancing low-temperature mercury removal. XRD and FT-IR results showed that MoS₂ and vanadia were successfully incorporated onto TiO₂ as dispersed surface phases, while the MoS₂-modified catalyst exhibited a distinct and persistent terminal V=O feature, implying the formation of a coupled Mo-S-V interfacial environment. H₂-TPR and NH₃-TPD demonstrated that MoS₂ modification simultaneously stabilized the redox structure and moderated the surface acidity, suppressing excessively strong NH₃ retention while maintaining a tunable oxidation-active surface. XPS analysis further revealed atmosphere-dependent redistribution of O_α/O_β species, sulfur oxidation to SO₃²⁻/SO₄²⁻ species, and dynamic V⁵⁺/V⁴⁺ interconversion, confirming that MoS₂ acted not only as a sulfur-containing component but also as an interfacial electronic regulator. Post-reaction Hg 4f XPS showed that retained mercury mainly existed as Hg²⁺ species, while Hg-TPD indicated that MoS₂ modification provided a more diverse and thermally stable mercury-binding environment. These results demonstrate that Hg⁰ removal over V₂O₅⁻MoS₂/TiO₂ proceeds through oxidation-retention coupling rather than simple oxidation alone. The enhanced performance originates from the synergistic effects of active oxygen migration, vanadium redox cycling, sulfur-assisted stabilization, and interfacial Mo-S-V electronic coupling. This work provides a promising strategy for designing multifunctional SCR catalysts in coal-fired plants for efficient Hg⁰ control under practical coal combustion flue-gas conditions. Full article

Wildfires represent a major environmental hazard with significant impacts on ecosystems, climate, biodiversity, and human activities. The increasing frequency and intensity of wildfire events have highlighted the need for reliable and timely detection techniques based on satellite remote sensing. This study investigates the application of Proper Orthogonal Decomposition (POD) to thermal observations acquired from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellite for wildfire anomaly detection. A wildfire event that occurred on 8 August 2021 in Calabria, Southern Italy, was selected as the primary case study. To assess the consistency of the POD response beyond the primary case, the analysis was further extended to two additional wildfire events, Viggianello–Abate and Pazzano–Montestella, using the 15 × 15 pixel extraction window. Middle Infrared (MIR, 3.9 $\mathsf{\mu }$m) observations collected at 15 min intervals over a complete day were analyzed using four different spatial extraction windows (3 × 3, 15 × 15, 30 × 30, and 45 × 45 pixels). POD was employed to separate dominant background thermal variability from localized fire-induced anomalies. The analysis focused on higher-order POD modes, particularly the 6th, 7th, and 8th modes, which exhibited enhanced sensitivity to wildfire activity. Results showed that POD successfully identified thermal anomalies corresponding to wildfire occurrence times independently detected by the RST-FIRES methodology. The comparison of extraction window sizes revealed that the 15 × 15 pixel window provided the best balance between anomaly enhancement, spatial localization, and noise reduction. Larger windows introduced excessive spatial smoothing and reduced localization capability, whereas the smallest window was more affected by noise. The findings demonstrate the potential of POD as an effective complementary approach for wildfire detection and monitoring using geostationary satellite observations. Full article

Lightweight and high-strength sandwich panels are used across aerospace, transportation, marine, energy, civil and protective systems because large face separation can provide high flexural rigidity and specific load capacity at low mass. This review treats the panel as a coupled material–structure–interface–process system rather than ranking core topology in isolation. A scoping-review workflow was updated to 24 July 2026 and yielded a curated evidence corpus of 112 total references. The review reports the search and screening logic explicitly, uses descriptive rather than field-wide bibliometric claims, and organizes the synthesis around component roles, governing mechanisms, connection regions, performance requirements and application-driven selection. Conventional foam, honeycomb and corrugated cores are compared with lattice-truss, auxetic, origami/kirigami, hierarchical, bio-inspired, graded and triply periodic minimal-surface (TPMS) architectures. Particular emphasis is placed on face-core and nodal junctions, static and dynamic failure-mode competition, fatigue and environmental degradation, fire/thermal/acoustic functions, additive-manufacturing defects, modelling fidelity, and active/adaptive concepts using shape-memory alloys and piezoelectric actuation. Cross-study numerical envelopes that could not be traced to harmonized test conditions are not used as universal rankings; instead, a mechanism-based screening matrix identifies design strengths, limitations and reporting requirements. The synthesis indicates that engineering deployment depends on preserving intended load paths in the as-manufactured panel, controlling interfaces and defects, validating multi-hazard durability and connections at scale, and integrating multifunctional or adaptive functions without creating new weak links. Full article

Wildfire and atmospheric nitrogen (N) deposition are increasingly important drivers of forest recovery under global change, yet their combined effects on understory shrub dynamics remain poorly understood in subtropical forests. We quantified temporal changes in shrub aboveground biomass (AGB) following low-severity fire and N addition in a subtropical conifer–broadleaf mixed forest in Central China, and evaluated the underlying mechanisms of resource and trait. Burning reduced shrub AGB by 58.3% in the first post-fire year, but this negative effect rapidly weakened, disappeared within two years, and shifted to a net positive effect (+28.2%) by year four. Nitrogen addition increased shrub AGB by 26.5%, with gradually strengthening effects over time. Understory light availability, soil available N, and community-weighted leaf area were the key predictors explaining variation in shrub AGB. Fire induced changes in shrub AGB was most strongly associated with leaf area rather than specific leaf area or foliar nutrient concentrations. Nitrogen addition improved shrub growth primarily through increased soil N availability and foliar N enrichment. Overall, post-fire shrub recovery was governed by a successional shift in limiting factors, transitioning from initial disturbance constraint to light-driven structural control with increasing importance of soil nutrient supply. These findings demonstrate that post-fire shrub recovery in subtropical forests is increasingly governed by canopy-mediated structural strategies rather than acquisitive leaf economics during succession. Therefore, increasing wildfire activity and atmospheric N deposition may reinforce shrub-dominated understory states, with important implications for post-fire regeneration trajectories and long-term forest carbon dynamics. Full article

Forest management strongly influences understory plant communities, yet their responses to management remain context-dependent and scale-sensitive. This review synthesizes current knowledge on understory vegetation in managed forests by combining a bibliometric analysis of global research trends (1986–2025) with a comprehensive qualitative evaluation of empirical studies. The bibliometric assessment identified 726 publications, with a marked increase in output after 2017 and a predominance of research articles within Environmental Sciences, forestry, and biodiversity conservation. Research activity is geographically concentrated in North America and Europe, while other biomes remain comparatively underrepresented. The classical review highlights canopy structure and light availability as primary drivers of understory diversity. Management interventions such as thinning, harvesting, gap creation, and prescribed fire frequently increase local (α) species richness and vegetation cover in the short term by promoting early-seral and light-demanding species. However, these gains are often accompanied by compositional shifts toward ruderal and generalist taxa, reductions in bryophytes and forest specialists, and declines in spatial heterogeneity at broader scales. Consequently, β-diversity and landscape-level distinctiveness may decrease despite stable or elevated plot-level richness. Management intensity, retention of structural legacies (e.g., large trees and deadwood), soil and hydrological conditions, landscape context, and interactions with global change drivers (e.g., nitrogen deposition and climate warming) strongly mediate vegetation responses. Low-to-moderate-intensity systems that maintain structural heterogeneity and approximate natural disturbance regimes appear most effective at balancing production objectives with biodiversity conservation. Understory vegetation responses to forest management reflect trade-offs between short-term richness increases and long-term risks of compositional homogenization and specialist decline. Evaluating biodiversity outcomes therefore requires multi-scale, trait-informed approaches that move beyond species richness alone. This synthesis provides an integrative framework to support evidence-based, biodiversity-oriented forest management in increasingly human-modified landscapes. Full article

Large-scale spiking neural network simulation requires numerical integration that preserves membrane dynamics and spike timing without making fine-resolution updates prohibitively expensive. This balance is difficult for conductance-based leaky integrate-and-fire (LIF) networks because synaptic decay, threshold crossings, resets, and refractory periods form a hybrid dynamical system. To address this difficulty, we introduce a spike-aware propagation (SAP) approximation method that combines exact receptor-trace updates, analytic homogeneous membrane propagation, Gauss–Legendre quadrature, and spike localization, improving the accuracy–efficiency Pareto frontier. We establish an error bound and conditional convergence under consistent refinement for the proposed SAP. At h = 1 ms, the single-realization T = 1000 ms comparison showed a lower voltage RMSE for SAP than for Euler at the same width in the two high-activity regimes. The five-seed T = 200 ms robustness experiment likewise showed lower voltage RMSE for SAP than for NEST at the same width. At the highest drive, the paired mean reduction was 3.91 mV (95% CI, 3.85–3.97 mV). This quantified gain supports SAP as a practical route to an improved accuracy–efficiency balance in large-scale conductance-based LIF simulation while underscoring the method’s configuration-dependent and regime-dependent scope. Full article