Search Results (298)

Land use and land cover change (LULC) is a critical catalyst for global climate patterns, environmental conditions, and ecological dynamics. Remote sensing and geographic information system (GIS) methods have accelerated research on the impacts and variability of climate change. In ecologically sensitive karst regions, LULC poses significant challenges to sustainable urbanization. As a representative karst mountain city in China, Guiyang has undergone rapid spatial transformation, yet quantitative studies on its long-term LULC trajectories within an integrated spatial modeling framework remain insufficient. This study analyzed LULC dynamics in Guiyang from 2007 to 2022 and projected changes for 2027, 2032, 2037, and 2042. Using the CA-ANN model within the QGIS MOLUSCE plugin, we calibrated the model with multi-temporal LULC data and nine spatial drivers, including topographic, proximity, and socioeconomic factors. The model structure was optimized through iterative testing, resulting in a final configuration of 8 hidden layers and 500 iterations. This setup achieved high validation accuracy during training, with a hindcast simulation overall accuracy of 84.42% and a Kappa coefficient of 0.73 for simulating the 2022 land cover. Future projections indicate that impervious surfaces will continue to expand in a spatially constrained manner, reaching 332.82 km² by 2042, while shrubland area will sharply decrease to 10.75 km². Cultivated land and forest areas show relative stability with fluctuations. The projected patterns may exacerbate risks associated with surface runoff and ecological fragmentation due to established linkages between land use/cover change and ecosystem services. Through spatially explicit, multi-temporal scenario simulations, the findings underscore the urgent need in Guiyang’s unique karst setting to deeply integrate land-use planning with ecological conservation strategies, so as to strengthen regional ecological resilience. Full article

Accurate precipitation mapping is essential for effective disaster management; however, individual radar, satellite, and numerical weather prediction products often struggle in the topographically complex terrain of South Korea. This study proposes a high-resolution (~500 m) daily precipitation fusion framework that integrates Korea Meteorological Administration (KMA) radar, Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG), and Local Data Assimilation and Prediction System (LDAPS) data. The framework employs a Random Forest model augmented with a monthly Empirical Cumulative Distribution Function (ECDF) correction. Auxiliary predictors are incorporated to enhance physical interpretability and stability, including terrain attributes to represent orographic effects, land-cover information to account for surface-related modulation of precipitation, and seasonal cyclic signals to capture regime-dependent variability. These predictors complement dynamic precipitation inputs and enable the model to effectively capture nonlinear spatiotemporal patterns, resulting in improved performance relative to individual radar, IMERG, and LDAPS products. Evaluation against Automated Synoptic Observing System (ASOS) observations yielded a correlation coefficient of 0.935 and a mean absolute error of 3.304 mm day⁻¹ in a Leave-One-Year-Out (LOYO) validation for 2024. Regional analyses further indicate substantial performance gains in complex mountainous areas, including the Yeongdong–Yeongseo region, where the proposed framework markedly reduces estimation errors under challenging winter conditions. Overall, the results demonstrate the potential of the proposed fusion framework to provide robust, high-resolution precipitation estimates in regions characterized by strong topographic and seasonal heterogeneity, supporting applications related to hazard analysis and hydrometeorological assessment. Full article

The Arid Region of Northwest China (ARNC) functions as a critical ecological barrier for the Eurasian hinterland. To clarify the non-linear drivers of eco-environmental dynamics, a long-term (2000–2024) Remote Sensing Ecological Index (RSEI) time series was constructed and analyzed using an interpretable machine learning framework (XGBoost-SHAP). The analysis reveals pronounced spatial asymmetry in ecological evolution: improvements are concentrated in localized, human-managed areas, while degradation occurs as a diffuse process driven by geomorphological inertia. The ARNC exhibits low-level stability (mean RSEI 0.25–0.30) and marked unbalanced dynamics, with significant degradation (19.9%) affecting more than twice the area of improvement (6.5%). Attribution analysis identifies divergent driving mechanisms: ecological improvement (R² = 0.559) is primarily anthropogenic (58.3%), whereas degradation (R² = 0.692) is mainly governed by natural constraints (58.4%), particularly structural topographic factors, where intrinsic landscape vulnerability is exacerbated by human activities. SHAP analysis corroborates a “Greenness-Quality Paradox” in stable agroecosystems, where high vegetation cover coincides with reduced evaporative cooling and secondary salinization from irrigation, resulting in declining Eco-Environmental Quality (EEQ). A zero-threshold effect for grazing intensity is also identified, indicating that any increase beyond the baseline immediately initiates ecological decline. In response, a Resist-Accept-Direct (RAD) framework is proposed: direct salt-water balance regulation in oases, resist hydrological cutoff in ecotones, and accept natural dynamics in the desert matrix. These findings provide a scientific basis for reconciling artificial greening initiatives with hydrological sustainability in water-limited regions. Full article

Accurate lightning data are critical for disaster warning and climate research. This study systematically compares the Fengyun-4A Lightning Mapping Imager (FY-4A LMI) satellite and the Advanced Time-of-arrival and Direction (ADTD) lightning location network in the Beijing-Tianjin-Hebei (BTH) region (April–August, 2020–2023) using coefficient of variation (CV) analysis, Welch’s independent samples t-test, Pearson correlation analysis, and inverse distance weighting (IDW) interpolation. Key results: (1) A significant systematic discrepancy exists between the two datasets, with an annual mean ratio of 0.0636 (t = −5.1758, p < 0.01); FY-4A LMI shows higher observational stability (CV = 5.46%), while ADTD excels in capturing intense lightning events (CV = 28.01%). (2) Both datasets exhibit a consistent unimodal monthly pattern peaking in July (moderately strong positive correlation, r = 0.7354, p < 0.01) but differ distinctly in diurnal distribution. (3) High-density lightning areas of both datasets concentrate south of the Yanshan Mountains and east of the Taihang Mountains, shaped by topography and water vapor transport. This study reveals the three-factor (climatic background, topographic forcing, technical characteristics) coupled regulatory mechanism of data discrepancies and highlights the complementarity of the two datasets, providing a solid scientific basis for satellite-ground data fusion and regional lightning disaster defense. Full article

Background and Objectives: Tear film instability and corneal surface irregularity are important sources of variability in keratometric and corneal topographic measurements, particularly affecting astigmatic magnitude and axis. Accurate preoperative biometry is crucial for optimal refractive outcomes in cataract surgery. Dry eye disease (DED) may compromise the reproducibility of keratometric parameters, leading to errors in intraocular lens (IOL) power calculation. This study aimed to evaluate the impact of DED on the reproducibility of keratometric measurements and to assess the effect of a four-week treatment with lipid-containing artificial tears on these parameters in cataract patients. Materials and Methods: This cross-sectional study included 116 patients scheduled for cataract surgery, of whom 65 (56.0%) had DED and 51 (44.0%) served as controls. All patients underwent two preoperative keratometric measurements 10–20 min apart (IOL1 and IOL2). The control group proceeded to surgery the next day, while surgery in the DED group was postponed. Patients with DED received preoperative therapy with lipid-containing artificial tears. Follow-up assessments occurred one month after therapy (keratometric measurement named IOL3) and eight weeks postoperatively. Clinical evaluation included slit-lamp examination, dry eye testing according to Dry eye Workshop II (DEWS II) criteria: Ocular surface Disease Index (OSDI), Tear Break-Up Time (TBUT), Schirmer I, Oxford staining, and meibomian gland assessment), ocular biometry, and postoperative spherical equivalent measurement using an auto ref-keratometer. Nonparametric statistical analyses were applied to evaluate associations between parameters. Results: In the DED group, corneal astigmatism showed a significant difference between IOL1 and IOL2 (Wilcoxon signed-rank test {Z = 2.43; p = 0.015}). Significant changes in predicted IOL power were observed between pretreatment and posttreatment values (t = 2.57; p = 0.013) and between IOL2 and IOL3 (t = 2.23; p = 0.029), indicating improved keratometric stability following tear film therapy. No additional significant correlations were identified. Conclusions: DED adversely affects the reproducibility of keratometric measurements and may compromise IOL power selection. Preoperative identification and treatment of DED, followed by repeated biometry after tear film stabilization, are strongly recommended to enhance refractive accuracy and optimize surgical outcomes in cataract patients. Full article

Background: Intentional tooth replantation (ITR) is a promising treatment option for preserving teeth in cases where conventional endodontic therapy is challenging, or when previous endodontic treatment and apicoectomy have been unsuccessful. The procedure involves extracting the compromised tooth, preserving the alveolar socket and root surface, performing extraoral endodontic therapy, and replanting the tooth in the alveolar socket. Objective: An increase in evidence-based support for ITR has improved the viability of ITR as a treatment option for patients. This review aims to further establish and provide new areas of potential research for ITR with respect to root morphology, extraction, and surgical techniques, maintenance of the tooth socket, and methods for post-op stabilization. Materials and Methods: A literature review was performed across PubMed from 1 January 1980 to 1 July 2025, with a focus on oral surgery techniques, atraumatic extraction techniques, topographical discrepancies in root system anatomy, and ITR procedural outcomes. Conclusions: Although ITR is not a common procedure performed in contemporary clinical practice, gathering sufficient data on the variables influencing the procedure may help patient outcome and improve communication between the endodontist and oral surgeons. Full article

Intensified water consumption has driven rapid groundwater depletion globally, threatening economic and environmental sustainability. Understanding large-scale groundwater dynamics has been constrained by the scarcity of long-term, high-resolution records. This study uses multi-decadal, high-density groundwater level monitoring data from the Southern Hebei Plain (SHP) to analyze the evolution of the groundwater flow field and depression cones from 1959 to 2020. We quantitatively characterize trends over six decades and assess the impact of the South-to-North Water Diversion Project (SNWD). The regional flow field shifted from a natural topographic-driven pattern (foothills to coast) in the 1960s to localized systems centered on depression cones by the 1980s. Subsequent management policies and the SNWD have progressively reduced the extent of these cones, facilitating a partial recovery of the regional flow pattern towards its original direction. Shallow aquifer levels declined steeply from the 1980s until 2016, particularly along the Taihang Mountains’ alluvial fan margins, with cumulative drawdown of 20–60 m. After SNWD implementation, levels stabilized and began recovering in piedmont urban areas. Deep aquifer levels generally declined from the 1980s to 2016, with the most significant drawdown (40–90 m) occurring in the central–eastern plain. The recovery of deep aquifers lagged behind shallow ones. These results provide critical insights for supporting sustainable groundwater management and depression cone recovery in the Hebei Plain. Full article

Under concurrent global warming and multi-scale climate anomalies, regional precipitation has become more uneven and less stable, and extreme events occur more frequently, amplifying water scarcity and ecological risk. Focusing on mainland China, we analyze nearly 70 years of monthly station precipitation records together with eight climate drivers—the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), Multivariate ENSO Index (MEI), Arctic Oscillation (AO), surface air pressure (AP), wind speed (WS), relative humidity (RH), and surface solar radiation (SR)—and precipitation outputs from eight CMIP6 models. Using wavelet analysis and partial redundancy analysis, we systematically evaluate the qualitative relationships between climate drivers and precipitation and quantify the contribution of each driver. The results show that seasonal precipitation decreases stepwise from the southeast toward the northwest, and that stability is markedly lower in the northern arid and semi-arid regions than in the humid south, with widespread declines near the boundary between the second and third topographic steps of China. During the cold season, and in the northern arid and semi-arid zones and along the margins of the Tibetan Plateau, precipitation varies mainly with interdecadal swings of North Atlantic sea surface temperature and with the strength of polar and midlatitude circulation, and it is further amplified by variability in near-surface winds; the combined contribution reaches about 32% across the Northeast Plain, the Junggar Basin, and areas north of the Loess Plateau. During the warm season, and in the eastern and southern monsoon regions, precipitation is modulated primarily by tropical Pacific sea surface temperature and convection anomalies and by related changes in the position and strength of the subtropical high, moisture transport pathways, and relative humidity; the combined contribution is about 22% south of the Yangtze River and in adjacent areas. Our findings reveal the spatiotemporal variability of precipitation in China and its responses to multiple climate drivers and their relative contributions, providing a quantitative basis for water allocation and disaster risk management under climate change. Full article

Accurate identification of cultivated land in plateau and mountainous regions remains challenging due to complex terrain and the fragmented, small-scale distribution of farmland. This study develops a high-precision cropland identification model tailored to such environments, aiming to advance precision agriculture and support the scientific planning and refined management of agricultural resources. Taking Xundian County, Yunnan Province, as a case study, multispectral, synthetic aperture radar (SAR), topographic, texture, and time-series features were integrated to construct a comprehensive multi-source feature space. A baseline land use map was generated by fusing datasets from the European Space Agency (ESA), the Environmental Systems Research Institute (ESRI), and the China Resource and Environment Data Cloud (CRLC). Using 4000 randomly selected sample points, five machine learning algorithms—Support Vector Machine (SVM), Random Forest (RF), Tabular Multiple Prediction (TABM), XGBoost, and the NSGA-II optimized XGBoost (NSGA-II-XGBoost)—were compared for cropland identification. Results show that the NSGA-II-XGBoost model consistently achieved superior performance in classification accuracy, stability, and adaptability, reaching an overall accuracy of 95.75%, a Kappa coefficient of 0.91, a recall of 0.96, and an F1-score of 0.96. These findings demonstrate the strong capability of the NSGA-II-XGBoost model for cropland mapping under complex topographic conditions, providing a robust technical framework and methodological reference for farmland protection and natural resource classification in other mountainous regions. Full article

Wildfires increasingly threaten the operation and stability of regional socio-economic systems, where infrastructure, population, and environmental conditions are tightly interconnected. To enhance operational efficiency and strengthen community resilience, this study develops an integrated optimization framework for wildfire evacuation system design based on mixed-integer programming. The model simultaneously determines the locations of primary and secondary shelters and establishes both main and backup evacuation linkages, forming a dual-stage structure that ensures continuous accessibility even under disrupted conditions such as road blockages or fire spread. Wildfire risk indices derived from topographic and environmental data are incorporated to support risk-aware and balanced shelter allocation. A case study of Uiryeong County, South Korea, demonstrates that the proposed framework effectively improves evacuation efficiency and system reliability, producing spatially coherent and adaptive evacuation plans under diverse disruption scenarios. The findings highlight how operation optimization can enhance socio-economic system resilience and sustainability when facing large-scale environmental disruptions. Full article

The risk of urban flooding has escalated with increasing rainfall intensity and the expansion of impervious surfaces. While commercial models such as XP-SWMM provide reliable hydraulic analyses, their closed-source structure limits transparency and integration with external tools. In contrast, the Grid-Based Urban Drainage System Analysis Model (GUDS), developed on the Weighted Cellular Automata 2D (WCA2D) framework, offers greater flexibility for process verification and coupling with platforms such as GIS and spreadsheets. This study presents a comparative assessment of numerical stability and velocity estimation schemes between XP-SWMM and GUDS. Moving beyond previous validation-focused studies, it quantitatively examines how algorithmic formulations—particularly in flow velocity computation and numerical treatment—affect inundation propagation and model stability under varying topographic conditions. Results demonstrate that XP-SWMM yields higher analytical precision but is prone to numerical instability on steep slopes, whereas GUDS maintains stable simulations due to its simplified water-level-difference approach, albeit with reduced responsiveness to rapidly changing flows. The differences in maximum inundation depth, inundation area, and propagation speed were relatively minor—approximately 11.6%, 10.7%, and 9.2% on average, respectively. This work provides a novel quantitative perspective on the trade-offs between precision and stability in urban flood modeling, highlighting GUDS’s robustness and practical applicability as an open and extensible alternative to conventional equation-based models. Full article

Accurately reproducing the mechanical and dynamic behavior of fractured rock masses remains a key challenge in rock engineering, especially in marble quarry environments where discontinuity networks, excavation geometry, and topographic effects induce highly non-linear stress distributions. This study presents a multidisciplinary and physically calibrated numerical approach integrating field stress measurements, structural characterization, and dynamic modeling using the Distinct Element Method (DEM). The analysis focuses on a marble quarry located in the Apuan Alps (Italy), a tectonically complex metamorphic massif characterized by intense deformation and pervasive jointing that strongly influence rock mass behavior under both static and seismic loading. The initial stress field was calibrated using in situ measurements obtained by the CSIRO Hollow Inclusion technique, enabling reconstruction of the three-dimensional principal stress regime and its direct incorporation into a 3DEC numerical model. The calibrated model was then employed to simulate the dynamic response of the rock mass under seismic loading consistent with the Italian Building Code (NTC 2018). This coupled static–dynamic workflow provides a realistic evaluation of ground motion amplification, stress concentration, and potential failure mechanisms along pre-existing discontinuities. Results demonstrate that physically validated stress initialization yields a significantly more realistic response than models based on simplified lithostatic or empirical assumptions. The approach highlights the value of integrating geological, geotechnical, and seismological data into a unified modeling framework for a sustainable quarry stability analysis in fractured rock masses. Full article

The application of bioinspired nanocomposites in orthopedic implants marks a significant innovation in biomedical engineering, aimed at overcoming long-standing limitations of conventional implant materials. Traditional implants frequently suffer from poor osseointegration, mechanical mismatch with bone, and vulnerability to infection. Bioinspired nanocomposites, modeled after the hierarchical structures found in natural tissues such as bone and nacre, offer the potential to enhance mechanical performance, biological compatibility, and implant functionality. This study reviews and synthesizes current advancements in the design, fabrication, and functionalization of bioinspired nanocomposite materials for orthopedic use. Emphasis is placed on the integration of nanocrystalline hydroxyapatite (nHA), carbon nanotubes (CNTs), titanium dioxide (TiO₂) nanotubes, and other nanostructured coatings that mimic the extracellular matrix. Methods include comparative evaluations of mechanical properties, surface modifications for biocompatibility, and analyses of antibacterial efficacy through nano-topographical features. Bioinspired nanocomposites have been shown to improve osteoblast adhesion, proliferation, and differentiation, thereby enhancing osseointegration. Nanostructured coatings such as TiO₂ nanotubes increase surface hydrophilicity and corrosion resistance, supporting long-term implant stability. Mechanically, these composites offer high stiffness, superior wear resistance, and improved strength-to-weight ratios. Biomimetic combinations of hydroxyapatite, zirconia, and biopolymers have demonstrated effective load transfer and reduced stress shielding. Additionally, antibacterial functionality has been achieved via nanostructured surfaces that deter bacterial adhesion while remaining cytocompatible with host tissues. The integration of bioinspired nanocomposites into orthopedic implants provides a multifunctional platform for enhancing clinical outcomes. These materials not only replicate the mechanical and biological properties of native bone but also introduce new capabilities such as infection resistance and stimuli-responsive behavior. Despite these advancements, challenges including manufacturing scalability, long-term durability, and regulatory compliance remain. Continued interdisciplinary research is essential for translating these innovations from laboratory to clinical practice. Full article

Exploring the spatiotemporal patterns of cultivated land conversion to non-agricultural uses and their evolutionary driving mechanisms is of significant importance for regional cultivated land protection and food security. This study utilizes time-series land use datasets, DEM, meteorological data, and statistical yearbook data to construct an assessment model for the rate of cultivated land conversion to non-agricultural uses. Based on this model, the study conducts spatial autocorrelation analysis and locational gradient analysis to systematically investigate the characteristics and driving mechanisms of cultivated land conversion to non-agricultural uses in Jiangsu Province from 2000 to 2023. The study revealed several key findings: (1). The total area of cultivated land in Jiangsu Province has demonstrated a trend of ‘initial continuous decline followed by a slight recovery after 2015.’ Spatially, it exhibits a distribution pattern characterized by ‘continuous reduction around urban areas, with relative stability in the northern core regions’. (2). The temporal pattern of cultivated land conversion to non-agricultural use in Jiangsu Province follows a trajectory of ‘rapid expansion (2000–2015) followed by a gradual slowdown (2015–2023),’ with significant gradient differences observed spatially (‘Southern Jiangsu > Central Jiangsu > Northern Jiangsu’). (3). The conversion of cultivated land to non-agricultural use in Jiangsu Province results from the combined effects of natural constraints, socio-economic driving factors, and agricultural policies. Topographical constraints and urban radiation have emerged as the primary spatial conditions promoting non-agriculturalization, with urban expansion identified as the most direct driving factor of cultivated land conversion in recent years. Conversely, agricultural factors have exerted a relatively weaker influence on non-agriculturalization. These research findings provide a significant scientific basis for formulating differentiated cultivated land protection policies across the province, thereby assisting in achieving a balance between food security and coordinated urban–rural development. Full article

Underground mining often causes surface displacement and deformation above and around mined-out areas, and mining-induced subsidence has become a growing concern for ground stability worldwide. Given the proximity between the studied mine and a neighboring operation, potential mutual influences during extraction were examined to ensure the safety of surface structures. This study analyzes the stability of the overlying strata by combining theoretical prediction and numerical simulation, considering the cumulative effects of adjacent mining activities. The main findings are as follows: (1) The probability integration method was used to predict surface deformation and subsidence caused by underground mining, providing deformation data for the 4# shaft, 4# return air shaft, 5# return air shaft, and surrounding ground surface. (2) A three-dimensional geomechanical model was built using FLAC3D finite-difference software based on actual topographical and geological data to assess the impact of mining on overburden stability. Results show that the surrounding rock remained primarily in the elastic stage, with a maximum surface subsidence of 47.7 mm, confirming the structural stability of the 4# and 5# shafts. (3) Analyzing stress redistribution during deep ore extraction in both mining zones reveals that stress disturbances were mainly confined to the excavation areas, with a maximum local stress concentration of 83.34 MPa at stope corners. The combined mining activities resulted in an overall subsidence of approximately 48.7 mm, which decreased gradually outward from the center. This research presents an integrated theoretical and numerical framework that combines probability integration theory with FLAC3D simulation to assess the cumulative deformation and stress interactions of neighboring underground mines. The proposed method offers a practical and transferable tool for evaluating regional mine stability and surface deformation risks in multi-mine districts. Full article