Search Results (444)

This study assesses the impact of climate change and human activities on vegetation dynamics (kNDVI) on the Qinghai-Tibet Plateau (QTP) between 2000 and 2022, considering both lag and cumulative effects. Given the QTP’s high sensitivity to climate change and human activities, it is imperative to understand their effects on vegetation for the sustainable development of regional and national terrestrial ecosystems. Using MOD13Q1 NDVI and climate and human activity data, we applied methods such as Sen-MK, lag and cumulative effect analysis, improved residual analysis, and geographical detector analysis. The outcomes were as follows. (1) The vegetation kNDVI on the QTP showed an overall fluctuating growth trend between 2000 and 2022; improved regions were more significant than degraded regions, with improved regions primarily distributed in humid and semi-humid areas with favorable climate conditions, and degraded regions primarily in arid and semi-arid areas; this implies that climate conditions have a significant impact on vegetation changes on the QTP. (2) The analysis of lag and cumulative effects revealed that temperature and precipitation have a substantial cumulative effect on vegetation kNDVI on the QTP. The vegetation kNDVI showed a lag effect of 0 months and a cumulative effect of 1 month for temperature, and a lag effect of 0 months and a cumulative effect of 2 months for precipitation, respectively. (3) Improved residual analysis based on lag and cumulative effects revealed that human activities positively contributed 66% to the changes in vegetation kNDVI on the QTP, suggesting a notable positive impact of human activities. Geographical detector analysis indicated that, among different human activity factors affecting vegetation kNDVI changes, the explanatory power in 2005 and 2015 ranked as X3 (livestock density) > X1 (population density) > X2 (per capita GDP) > X4 (artificial afforestation density) > X5 (land use type), and in 2020, as X3 > X4 > X1 > X5 > X2. The explanatory power of afforestation density and land use type has relatively increased, indicating that recent efforts in ecological protection and restoration on the QTP, including developing artificial forest areas and afforestation programs, have considerably contributed to vegetation greening. Full article

The sand–gravel brine deposit in the Mahai Basin is a newly discovered large-scale potassium–bearing brine deposit. The potassium–bearing brine is primarily found at depths exceeding 150 m within the porous alluvial and fluvial sand–gravel reservoir of the Middle to Lower Pleistocene. This deposit is characterized by a relatively shallow water table, moderate–to–strong aquifer productivity, high salinity, and a KCl content that meets the conditions for exploitation, with the advantage of reduced salt crystallization during well mining, making it a potential reserve base for potash development. A geochemical analysis of the sand–gravel brine revealed consistent trends for the major ions K⁺, Na⁺, Mg²⁺, Cl⁻, and SO₄²⁻ along the east–west axis of the alluvial fan, while Ca²⁺ showed an opposite trend compared to Mg²⁺. Along the exploration lines from north to south, the concentrations of the main ions gradually increase. The brine is enriched in Na⁺ and Cl⁻ ions, while SO₄²⁻ and HCO₃⁻ are depleted. In the K⁺-Na⁺-Mg²⁺/Cl⁻-H₂O (25 °C) quaternary phase diagram, the brine falls within the halite stability field, with the hydrochemical type classified as chloride type. The brine coefficient characteristics indicate a multi-source origin involving residual evaporation, salt rock leaching, and metamorphic sedimentary brine. Comparison studies of the ionic composition and isotopic signatures (δD, δ¹⁸O, δ³⁷Cl, and δ⁷Li) of deep sand–gravel brines in the study area with interstitial and confined brines in the southern depression suggest similar geochemical characteristics between them. The genetic analysis of the deposit proposes that during the basin tectonic evolution, the potassium-rich interstitial and confined brines originally located in the southern depression of the Mahai Basin were displaced under compressional forces and migrated northward as the depositional center shifted, eventually backfilling into the loose alluvial and fluvial sand and gravel reservoirs at the front of the Saishiteng Mountains, forming the deep sand–gravel brine deposits in the foreland. Full article

The net primary productivity (NPP) of vegetation is the key indicator for assessing ecosystem productivity and carbon cycling. The Ulan Mulun River Basin (UMRB) in Northwest China is a typical coal mining area, including open-pit mining (OPM) and underground coal mining (UGM). There are limited studies utilizing long-term, high-resolution data to investigate the spatiotemporal and driving mechanisms of NPP in different types of mining and non-coal mining (NCM) areas. In this study, NPP was estimated using high-resolution Landsat data (30 m) and an improved CASA model for the period 1987–2022. The spatiotemporal variations in NPP across the basin were systematically investigated using Theil–Sen–MK trend analysis, partial derivatives, and multivariate regression residual to explore and quantify the impacts of climate variability (CV) and human activities (HAs) on the different coal mining and NCM areas. The research results show that the overall fluctuating upward trend of vegetation cover in the country is 64.84% during the period from 1987 to 2022. However, there is a decreasing trend of NPP in the coal mining areas. Precipitation was the major factor influencing the change in NPP (21.835 gC/m²/a), while HAs had a lesser effect (4.667 gC/m²/a). In addition, UGM and NCM were more positively affected by HAs than OPM, while OPM was more positively affected by CV than UGM and NCM. These findings can guide scientific ecological restoration strategies, assess carbon balance impacts, and optimize land management and planning in mining areas to achieve a balance between resource development and environmental protection. Full article

With the intensification of climate change and anthropogenic impacts, the ecological environment in drylands faces serious challenges, underscoring the necessity for regionally adapted ecological quality evaluation. This study evaluates the suitability of the original Remote Sensing Ecological Index (oRSEI), modified RSEI (mRSEI), and adapted RSEI (aRSEI) in a typical dryland region of northern China. Spatio-temporal changes in ecological quality from 2000 to 2022 were analyzed using Theil–Sen median trend analysis, the Mann–Kendall test, and the Hurst exponent. Multiple regression residual analysis quantified the relative contributions of climate change and human activities to ecological quality changes. Results showed that (1) the aRSEI was the most suitable index for the study area; (2) observed changes exhibited significant spatial heterogeneity, with improvements generally in the inner areas of the Yellow River and declines in the outer areas; and (3) changes in ecological quality were primarily driven by climate change and human activities, with human activities dominating from 2000 to 2011 and the influence of climate change increasing from 2012 to 2022. This study compares the efficacy of RSEIs in evaluating dryland ecological quality, identifies spatio-temporal change patterns, and elucidates driving mechanisms, offering scientific evidence and policy recommendations for targeted conservation and restoration measures to address future changes in dryland regions. Full article

In this article, we propose the detection of crowd anomalies through the extraction of information in the form of time series in video format using a multimodal approach. Through pattern recognition algorithms and segmentation, informative measures of the number of people and image occupancy are extracted at regular intervals, which are then analyzed to obtain trends and anomalous behaviors. Specifically, through temporal decomposition and residual analysis, intervals or specific situations of unusual behaviors are identified, which can be used in decision-making and the improvement of actions in sectors related to human movement such as tourism or security. This methodology introduces a novel, privacy-focused approach by analyzing anonymized metrics rather than tracking or recognizing individuals, setting a new standard for ethical crowd monitoring. Applied to the webcam of Turisme Comunitat Valenciana in the town of Morella (Comunitat Valenciana, Spain), this approach has shown excellent results, correctly detecting specific anomalous situations and unusual overall increases during the previous weekend and during the October 2023 festivities. These results have been obtained while preserving the confidentiality of individuals at all times by using measures that maximize anonymity, without trajectory recording or person recognition. Full article

In the recent past, mangrove ecosystems have undergone significant transformation, necessitating precise classification, the assessment of ecological changes, and the identification of suitable sites for urgent replantation. Therefore, this study aims to address three key objectives: first, to map the current extent of mangroves; second, to assess the ecological changes within these ecosystems; and third, to identify suitable areas for replantation, ensuring their sustainability across coastal Asir. The mangrove classification was conducted using an ensemble of machine learning models, utilizing the key spectral indices from Landsat 8 data for 2023. To analyze the ecological trends and to assess the changes over time, Landsat 5–8 data from 1991 to 2023 were used. Finally, a generalized additive model (GAM) identified the areas suitable for reforestation. The EC identified the mangrove area as 14.69 sq. km, with a 95.6% F1 score, 91.3% OA, and a KC of 0.83. The trends in the NDVI and LST increased (p = 0.029, 0.049), whereas the NDWI showed no significant change (p = 0.186). The GAM model demonstrated a strong fit (with an adjusted R² of 0.89) and high predictive accuracy (R² = 0.91) for mangrove priority reforestation suitability, confirmed by a 10-fold cross-validation and minimal bias in the residual diagnostics. The suitability varied across groups, with Group (e) showing the highest suitability at 77%. Moran’s I analysis revealed significant spatial clustering. This study provides actionable insights for mangrove reforestation, supporting the for sustainable development through targeted efforts that enhance ecological resilience in coastal regions. Full article

Net ecosystem productivity (NEP) plays a vital role in quantifying the carbon exchange between the atmosphere and terrestrial ecosystems. Understanding the effects of dominant driving forces and their respective contribution rates on NEP can aid in the effective management of terrestrial carbon sinks, especially in rapidly urbanizing coastal areas where climate change (CC) and human activities (HA) occur frequently. Combining MODIS NPP products and meteorological data from 2000 to 2020, this paper established a Modis NPP-Soil heterotrophic respiration (R_h) model to estimate the magnitude of NEP in China’s coastal zone (CCZ). Hotspot analysis, variation trend, partial correlation, and residual analysis were applied to explore the spatiotemporal patterns of NEP and the contributions of CC and HA to the dynamics of NEP. We also explored the changes in NEP in different land use types. It was found that there is a clear north–south difference in the spatial pattern of NEP in CCZ, with Zhejiang Province serving as the main watershed for this difference. In addition, NEP in most regions showed an improvement trend, especially in the Beijing–Tianjin–Hebei region and Shandong Province, but the pixel values of NEP here were generally not as high as that in most southern provinces. According to the types of driving forces, the improvement of NEP in these regions primarily results from the synergistic effects of CC and HA. NEP changes in provinces south of Zhejiang are mainly dominated by single-factor-driven degradation. The area where HA contributes to the increase in NEP is much larger than that of CC. From the perspective of land use types, forests and farmland are the dominant contributors to the magnitude of NEP in CCZ. Full article

Polyurethane grouting trenchless technology has been widely applied to the rehabilitation of concealed defects in engineering structures. The interfacial properties between polyurethane and engineering structures are key factors determining the stability of the composite structure. In practical applications, the interface shapes of different engineering structures vary significantly, and the influence of the interface shape on interfacial properties should not be overlooked. This study focuses on engineering structures with curved interfaces, such as pile foundations, pipelines, and tunnels. Direct shear tests were conducted on polyurethane and concrete composite specimens with curved interfaces. A comparative analysis of the shear behavior between curved and planar composite specimens was performed, and the influence of arc diameter and polyurethane density on the shear behavior of curved and planar composite specimens was investigated. Additionally, SEM (Scanning Electron Microscopy) was used to conduct a microscopic examination of the interfaces with different polyurethane densities after failure, and the microscopic shear mechanisms between polyurethane and concrete materials were explored. The results revealed that the shear behavior of curved specimens was significantly higher than that of planar specimens. The shear strengths of curved specimens with diameters of 400 mm, 500 mm, and 700 mm were approximately 1.50, 1.39, and 1.10 times those of planar specimens, respectively. With increasing polyurethane density, the variation trend of shear strength in curved specimens was similar to that of planar specimens. However, significant differences were observed in the shear modulus, peak displacement, and shear residual strength between curved and planar specimens as the polyurethane density varied. Different diameter curved interface specimens exhibited a similar trend of shear strength variation with polyurethane density, gradually decreasing as the curvature diameter increased, and ultimately approaching that of planar specimens. Full article

In this paper, nonlinear system identification using Bayesian network has been implemented to discover open-loop lateral-directional aerodynamic model parameters of an agile aircraft using a grey box modelling structure. Our novel technique has been demonstrated on simulated flight data from an F-16 nonlinear simulation of its Flight Dynamic Model (FDM). A mathematical model has been obtained using time series analysis of a Box–Jenkins (BJ) model structure, and parameter refinement has been performed using Bayesian mechanics. The aircraft nonlinear Flight Dynamic Model is adequately excited with doublet inputs, as per the dictates of its natural frequency, in accordance with non-parametric modelling (Finite Impulse Response) estimates. Time histories of optimized doublet inputs in the form of aileron and rudder deflections, and outputs in the form of roll and yaw rates are recorded. Dataset is pre-processed by implementing de-trending, smoothing, and filtering techniques. Blend of System Identification time-domain grey box modelling structures to include Output Error (OE) and Box–Jenkins (BJ) Models are stage-wise implemented in multiple flight conditions under varied stochastic models. Furthermore, a reduced order parsimonious model is obtained using Akaike information Criteria (AIC). Parameter error minimization activity is conducted using the Levenberg–Marquardt (L-M) Algorithm, and parameter refinement is performed using the Bayesian Algorithm due to its natural connection with grey box modelling. Comparative analysis of different nonlinear estimators is performed to obtain best estimates for the lateral–directional aerodynamic model of supersonic aircraft. Model Quality Assessment is conducted through statistical techniques namely: Residual Analysis, Best Fit Percentage, Fit Percentage Error, Mean Squared Error, and Model order. Results have shown promising one-step model predictions with an accuracy of 96.25%. Being a sequel to our previous research work for postulating longitudinal aerodynamic model of supersonic aircraft, this work completes the overall aerodynamic model, further leading towards insight to its flight control laws and subsequent simulator design. Full article

The middle reaches of the Yellow River Basin (MYRB) are known for their significant soil erosion and fragile ecological environment, where vegetation growth is important. However, the vegetation’s reaction to climate change (CC) and human activity (HA), and the potential driving mechanisms underlying such changes in the MYRB, have not yet been clarified. Thus, based on remote sensing data, combined with trend analysis and the Hurst method and supplemented by the structural equation model (SEM) and residual analysis method, we aimed to conduct an analysis of the spatio-temporal evolution of the normalized difference vegetation index (NDVI) in the MYRB from 2000 to 2020. Additionally, we explored how climate and human factors together affect the NDVI and quantified the proportion of their respective contributions to NDVI change. The NDVI exhibited a fluctuating upward trend in the MYRB. Moreover, approximately 97.7% of the area showed an improving trend, with nearly 50% of the area continuing to maintain an improving trend. Precipitation and temperature had positive effects on the NDVI, while vapor pressure deficit (VPD) and land use intensity (LUI) had negative effects. HA played a pivotal role in the vegetation improvement area with a contribution rate of 67.53%. The study revealed NDVI variations and emphasized the influence of HA on the NDVI in the MYRB. The findings are vital in comprehending the response mechanism of ecosystems and guiding reasonable environmental protection policies, which is beneficial for the sustainable development of the region. Full article

The outbreak of epidemics such as African swine fever has intensified the use of disinfectants in pig farms, resulting in an increasing residual concentration of disinfectants in environmental media; however, the high-frequency excessive use of disinfectants that damage pig farm manure anaerobic fermentation systems and their mechanisms has not attracted enough attention. Especially, the complex effects of residual disinfectants on anaerobic fermentation systems for pig manure remain poorly understood, thus impeding the application of disinfectants in practical anaerobic fermentation systems. Herein, we explored the effects of glutaraldehyde disinfectant on methane production, effluent physicochemical indices, and microbial communities in a fully automated methanogenic potential test system (AMPTSII). The results show that adding glutaraldehyde led to remarkable alterations in methane production, chemical oxygen demand (COD), volatile solids (VS), and polysaccharide and phosphorus concentrations. During the anaerobic process, the production of methane displayed a notable decrease of 5.0–98% in all glutaraldehyde treatments, and the trend was especially apparent for treatments containing high levels of glutaraldehyde. Comparisons of the effluent quality showed that in the presence of 0.002–0.04% glutaraldehyde, the COD and total phosphorus (TP) increased by 12–310% and 15–27%, respectively. Moreover, the addition of 0.01–0.08% glutaraldehyde decreased the ammonium (NH₄⁺-N) concentration and VS degradation rate by 7.7–15% and 4.9–26.2%. Furthermore, microbiological analysis showed that the glutaraldehyde treatments had adverse effects on the microbial community. Notably, certain functional bacteria were restrained, as highlighted by the decreases in relative abundance and microbial diversity by 1.3–17% and 0.06–21%, respectively. This study provides a theoretical basis for the rational use of disinfectants in anaerobic fermentation systems. Full article

This study conducted an in-depth analysis of the sediment dynamics in the lower reaches of the Changhua River and its estuary on Hainan Island. Through field collection of topographic data and sediment sampling, combined with advanced computational techniques, the study explored the transport pathways and depositional patterns of sediments. The grain size trend analysis (GSTA) method was utilized, in conjunction with the Flemming triangle diagram method, to classify the dynamic environment of the sediments. Furthermore, hydrodynamic modeling results were integrated to further analyze the transport trends of the sediments. The study revealed that the sediment types in the research area are complex, primarily consisting of gravelly sand and sandy gravel, indicating a generally coarse sedimentary environment in the region. The sediments in the lower reaches of the Changhua River generally transport towards the south and southwest (in the direction of Beili Bay). The net sediment transport directions inferred from the GSTA model are largely consistent with the Eulerian residual flow patterns, especially in the offshore area, where discrepancies are observed in the nearshore zone. The nearshore transport is influenced by the combined effects of alongshore currents, residual flows, and river inputs, while the offshore transport exhibits a shift from the northwest to southwest directions, reflecting the regional circulation patterns. Full article

Understanding the long-term performance deterioration trends and mechanisms of asphalt pavement is crucial for effective maintenance strategies. This study characterizes and correlates the multi-scale performance deterioration of a 14-year asphalt pavement. Air void measurements, indirect tensile (IDT) fatigue testing, Fourier transform infrared spectroscopy (FTIR), and dynamic shear rheometer (DSR) testing were conducted on pavement cores and recovered binder. Multiple regression analysis was then performed on various performance indicators. Laboratory results indicate that the chemical composition and viscoelastic properties of SBS-modified binders evolve rapidly in the first few years, followed by a relatively stable aging rate. After 14 years, the mechanical and rheological properties of lower-layer mixtures deteriorate to a similar degree as the surface layer. Correlation analysis revealed that the residual strength of the mixture is more influenced by air voids, while reductions in fatigue life are primarily driven by binder aging. These findings highlight the necessity of applying preventive maintenance within the first 3–5 years to rejuvenate the surface asphalt and rehabilitate both the surface and underlying layers after long-term service. Full article

The operational practice of the design of the Bozena 5 demining machine has shown that its belts are the critical component that fundamentally affects the functionality of the entire machine. This article is a practical continuation and extension of the previous research results from the point of view of materials (research of the uniaxial fatigue life in bending and torsion), calculation (creation of the necessary mathematical, analytical and numerical models for the research) and construction (i.e., patented design of the belt tensioning of this machine). All these actions are aimed at a single objective—to achieve a condition that guarantees a sufficient service life without malfunctions, since repairing these machines in the field is often impossible. Therefore, this study examined the fatigue life of welded joints (uniaxial bending and torsion) of S960 QL and S500MC steels welded by MAG technology. Subsequently, the data were compared with previous results (electron and laser welds) and the influence of each type of weld on the fatigue life relative to the base material was discussed. It was found that conventional MAG technology had a more significant negative impact on the fatigue life of the base material than non-conventional technologies. This trend was particularly true for the bending stress. At the same time, the bending stress was identified by the FEM analysis as the dominant load on the belt. The maximum stress in the belt link under the considered boundary conditions was approximately 240 MPa (in bending). This stress corresponded to the continuous fatigue life (more than 10⁷ cycles) for both base materials tested (S960QL, S500MC). In the whole studied spectrum of controlled deformation amplitudes (Manson–Coffin), the life of MAG welds was lower in comparison with the base material and with welds made by unconventional technologies. All the activities carried out so far (research on microstructure, hardness, strength, residual stresses, tribological properties and fatigue life) have shown that the original belt design (S500MC) using MAG technology has significant deficiencies in the state of optimal life. It is expected that the proposed material change (use of S960QL instead of S500MC) and work with advanced technologies will bring this state significantly closer. Full article

Eurasian dryland ecosystems consist mainly of cropland and grassland, and their changes are driven by both natural factors and human activities. This study utilized the normalized difference vegetation index (NDVI), gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) to analyze the changing characteristics of vegetation activity in Eurasia over the past two decades. Additionally, we integrated the mean annual temperature (MAT), the mean annual precipitation (MAP), the soil moisture (SM), the vapor pressure deficit (VPD) and the terrestrial water storage (TWS) to analyze natural factors’ influence on the vegetation activity from 2003 to 2022. Through partial correlation and residual analysis, we quantitatively described the contributions of both natural and human factors to changes in vegetation activity. The results indicated an overall increasing trend in vegetation activity in Eurasia; the growth rates of vegetation greenness, productivity and photosynthetic capacity were 1.00 × 10⁻³ yr⁻¹ (p < 0.01), 1.30 g C m⁻² yr⁻² (p < 0.01) and 1.00 × 10⁻³ Wm⁻²μm⁻¹sr⁻¹yr⁻¹ (p < 0.01), respectively. Furthermore, we found that soil moisture was the most important natural factor influencing vegetation activity. Human activities were identified as the main driving factors of vegetation activity in the Eurasian drylands. The relative contributions of human-induced changes to NDVI, GPP and SIF were 52.45%, 55.81% and 74.18%, respectively. These findings can deepen our understanding of the impacts of current natural change and intensified human activities on dryland vegetation coverage change in Eurasia. Full article