Search Results (27,819)

Lanping County, located on the southeastern margin of the Qinghai–Tibet Plateau, is a key component of the “Three Parallel Rivers of Yunnan” World Natural Heritage Site, where widespread landslides pose significant threats to local communities. However, landslide spatial patterns and susceptibility assessments in this county remain poorly understood. This study compiled a detailed landslide inventory through high-resolution remote sensing interpretation, employing the certainty factor (CF) model to map landslide susceptibility and analyze spatial distribution patterns. The results show that a total of 1792 landslides were identified, predominantly distributed at elevations of 1500–3000 m, on slopes of 15–45° with aspects of 180–210°, and in areas with topographic relief of 150–450 m and annual rainfall >925 mm. Most landslides are located within 750 m of rivers, 4000 m of faults, and 1500 m of roads. The Jurassic (J) stratigraphic unit exhibited the highest landslide area density (LAD = 0.32). Morphometric analysis revealed that most landslides display longitudinal morphologies, with heights of 50–265 m and travel distances of 25–200 m, exhibiting allometric scaling relationships with volume. The mean reach angle of 31.8° was higher than that of Dongchuan District (29°). Susceptibility mapping indicated that the very low, low, moderate, high, and very high susceptibility zones account for 12.23%, 26.46%, 26.97%, 19.98%, and 14.36% of the study area, respectively. The high and very high susceptibility zones together comprise 34.34%, concentrated along the Lancang River main stem and its tributaries. These findings enhance understanding of landslide spatial distribution and morphological characteristics along the southeastern margin of the Qinghai–Tibet Plateau, providing a scientific basis for regional landslide management and sustainable land-use planning. Full article

Rapid urbanization has significantly altered land use patterns in Deqing County, placing increasing pressure on its ecosystem. This study establishes a Driving Force–Pressure–State–Impact (DPSI) framework and selects ten indicators to evaluate ecological sensitivity for 2014, 2019, and 2024. It then couples this framework with the PLUS model to simulate land use and ecological sensitivity changes under the following three 2034 scenarios: natural development (ND), ecological protection (EP), and urban development (UD). Results show that ecological sensitivity exhibits a “high west, low east” spatial pattern and it fluctuated with an initial decline followed by a rise from 2014 to 2024, though the overall trend was a slow decrease. Land use type (weight 0.342), distance to rivers (weight 0.191), and distance to roads (weight 0.146) were the dominant influencing factors, together depicting Deqing’s ecological landscape of “western forests, eastern farmlands, and dense water networks”. The PLUS model demonstrated good validation accuracy (Kappa = 0.81), and the contributions of driving factors shifted over time. Multi-scenario simulation indicates that the ecological protection (EP) scenario is more suitable for sustainable urban development. We recommend implementing differentiated ecological control zones, integrating sensitivity evaluation into planning decisions, and improving the differentiated ecological compensation mechanism. Full article

Agricultural production is an important source of global carbon emissions, yet differences in system boundaries and emission factors among previous studies have limited comparisons across crops and regions. This study investigated the distribution, emission sources, and regional disparities of agricultural carbon emissions across 31 major crop-producing provinces in China, using a unified life cycle assessment (LCA) framework based on agricultural input, crop production, and agronomic data in 2024. Carbon emissions per unit area (CEA) and per unit yield (CEY) were quantified under consistent accounting boundaries, and the contributions of different emission sources together with their spatial characteristics were discussed. CEA generally showed higher values in the central and eastern regions of China and Xinjiang, but lower values in southwestern and northeastern China. Xinjiang contributed the highest total carbon emissions (about 1.6 × 10⁵ t), primarily because extensive cotton cultivation requires intensive irrigation, mechanized operations, and plastic-film mulching, leading to high emissions from fertilizer use, energy consumption, and agricultural film. Rice exhibited the highest carbon emissions (accounting for 30% of all 11 types of crops), followed by cotton and tobacco, while soybeans, rapeseed, and sugar beets had relatively low emission intensities. Fertilizer production and application were the dominant emission sources for most upland crops, while methane emissions from flooded paddy fields accounted for the largest share of rice carbon emissions. Spatial clustering analysis further indicated that high-emission regions were concentrated in central and eastern China, while northeastern China formed distinct low-emission clusters. This study provided a consistent assessment of carbon emissions from major crops across China, offering a reference basis for formulating emission reduction strategies for different crops and regions. Full article

Background: In our companion study, the gingival mesenchymal stem cell (GMSC) secretome suppresses oxidative stress and induces apoptosis in primary oral squamous cell carcinoma (OSCC) cells, where those wet-lab results are themselves reported as preliminary; here we ask whether it also engages a proliferation × migration programme in patient tissue. The two arms differ in read-out type (apoptosis and redox there, transcript abundance here), not in opposed function. Methods: Primary OSCC cells received GMSC-conditioned medium (GMSC-CM) or indirect Transwell co-culture, assayed by RT-qPCR (VEGFA, TGFB1, MMP9, CXCL12, CCND1, PCNA, MYC, EGFR), MTT, and scratch-wound migration. Thirteen computational layers plus a GeoMx spatial verify-and-decide layer were applied to public data: TCGA-HNSC, GEO, CPTAC, single-cell inference, prognostic modelling, DepMap and LINCS L1000. Results: All eight transcripts were raised in all three arms (16 of 24 comparisons significant), indicating a pro-tumour transcriptional shift; metabolic activity was unchanged and wound closure was reduced under conditioned medium (p < 0.01). Of 1358 genes significant in all three modalities, 1219 (89.8%, 95% CI 88.0–91.3%) share direction against 25.0% expected by chance (3.59-fold; exact binomial p below machine precision). The pre-registered oral-cavity signature did not validate externally (GSE41613; C = 0.562), and no ligand–receptor pair survived permutation calibration. Conclusions: GMSC paracrine exposure induces a pro-tumour transcriptional programme in primary OSCC cells that replicates at patient level, without demonstrated functional or therapeutic consequence; gefitinib is nominated only as a hypothesis-generating candidate. The evidence rests on three primary cultures (n = 3), one GMSC donor preparation, one 24 h time point, a single reference gene, no cell-line authentication and no test of gefitinib; the study programme has concluded, and these experiments cannot be performed now. Full article

Reliable cropland, forestland, and grassland maps support resource assessment and ecological management in arid and semi-arid Central Asia. Existing land-cover products often delineate these classes differently, vary in reliability across classes and locations, and may share the same errors even when they agree. This study formulates multi-product fusion as a pixel- and class-specific reliability decision problem. To address this problem, we propose a reliability-adaptive fusion framework, the Discrepancy-Aware Reliability-Adaptive Fusion Network (DRAFNet), using 2020 maps from three global 30 m land-cover products—FROM-GLC Plus, GLC-FCS30D, and GlobeLand30—and variables representing aridity, temperature, precipitation, elevation, and slope. Unlike fixed-weight fusion methods and segmentation models that use the source products only as input channels, DRAFNet retains the categorical source decisions and adjusts each contribution according to its estimated reliability for the assigned class and location. Weight removed from an unreliable source is transferred to a residual expert, which provides an alternative prediction when the source products are unreliable or share the same error. Voting entropy and geo-environmental variables provide contextual information for this decision. On independent test samples from the five Central Asian countries, DRAFNet achieved an overall accuracy (OA) of 0.8275, a Kappa coefficient of 0.7698, a mean intersection over union (mIoU) of 0.7046, and a macro-averaged F1 score (Macro F1) of 0.8241. These values were 0.95–1.38 percentage points higher than those of U-Net++, the strongest benchmark. Local comparisons indicated more coherent spatial patterns and clearer boundaries in areas of pronounced disagreement. The mean and median absolute log-ratio deviations from area statistics reported by the Food and Agriculture Organization of the United Nations (FAO) were 0.618 and 0.450, respectively, both lower than those of the source products. These results support land-resource assessment and ecological management in Central Asia. Full article

Mudstone caprocks are important sealing formations for geological CO₂ storage, but the extent and mineralogical response of CO₂-induced alteration within mudstone caprocks remain poorly constrained. This study examines a Paleocene mudstone caprock from the Mingyuefeng Formation in the Lishui Sag, East China Sea Basin, where natural CO₂ charging has occurred. Mineralogical and geochemical analyses, including X-ray diffraction (XRD), rare earth elements (REE), and carbon–oxygen isotopes, were used to characterize CO₂–water–rock interaction at the reservoir–caprock transition. The studied caprock is dominated by quartz and clay minerals, with mineralogical characteristics favorable for caprock sealing. REE signatures indicate a felsic source and limited vertical REE redistribution within the studied interval. Carbonate minerals display distinct vertical variations across the sandstone–mudstone interface, with localized carbonate redistribution near the transition and carbonate depletion accompanied by clay-mineral alteration above it. Most samples retain δ¹³C values close to background levels, whereas a decimeter-scale interval adjacent to the interface exhibits depleted δ¹³C values accompanied by localized δ¹⁸O variations, consistent with the localized influence of CO₂-bearing fluids. The altered zone is restricted to a decimeter-scale interval above the reservoir–caprock transition, suggesting that CO₂-related alteration was spatially restricted within the studied interval. Carbonate redistribution and clay-mineral transformation may have contributed to geochemical buffering during CO₂–water–rock interaction, although their quantitative effects on pore structure and sealing performance require further petrophysical investigation. These results provide a natural analogue for understanding localized CO₂-induced alteration and potential geochemical self-sealing processes at reservoir–caprock interfaces. Full article

Synergistic pollution–carbon mitigation is critical for China’s dual carbon targets. Taking coal-resource Shanxi Province as the case, this study developed an integrated Long-range Energy Alternatives Planning (LEAP)–Community Multiscale Air Quality (CMAQ) coupled framework combined with a three-dimensional vector model to simulate energy consumption, CO₂, and major air pollutant emissions (CO₂, CO, SO₂, NO₂, PM_2.5, and PM₁₀) under Baseline and Policy scenarios (2026–2050). The core novelty of this study lies in methodological innovation: the multi-model linkage realizes full-chain energy-emission-atmosphere simulation, remedying the isolation flaw of single models in prior research. The results indicated that low-carbon levels would rise steadily in both scenarios from 2026 to 2050. The Policy scenario achieved superior long-term low-carbon performance compared with the Baseline scenario and narrowed gaps in underdeveloped social subsystems, despite short-term transition costs. This scenario optimized the overall energy structure yet failed to fully reduce emission loads from residential and transport sectors. It drastically cut carbon and pollutant emissions, optimized spatial emission patterns, and decoupled most air pollutants from carbon emissions. However, this scenario still had prominent limitations: phased delays in emission abatement, strong coupling of CO, NO₂ and carbon emissions, and rising residential carbon emissions. Further pollution–carbon synergy assessment revealed worsening multi-dimensional imbalances under the Baseline scenario. While the Policy scenario experienced temporary systemic imbalance, its long-term coordination level improved steadily. This finding verified that systematic, long-term low-carbon governance constituted the core driver of Shanxi’s green transition. Targeted phased, classified collaborative governance strategies were proposed to resolve structural transformation risks for resource-based regions. Full article

The Greater Mekong Subregion (GMS) has emerged as a strategic logistics hub due to rapid economic integration and the expansion of cross-border road transportation. However, international road logistics networks in the region must address several competing objectives, including minimizing transportation costs, reducing delivery times, and balancing transport distances among trading partners. To overcome these challenges, this study proposes an innovative hybrid computational framework that integrates the classical Transportation Problem with the Pythagorean methodology (TPPM). The proposed approach consolidates multiple transportation objectives into a unified performance metric based on the Pythagorean concept, thereby enabling simultaneous optimization under practical constraints. In addition, geographic inputs derived from Google Maps and Google Earth via web platforms, which are reliable open-source GIS tools, are incorporated into the transportation model to improve spatial accuracy. A simulated dataset comprising 35 suppliers and 42 customers, representing major logistics nodes in the GMS, is developed to evaluate the proposed method. The computational results indicate that the TPPM approach outperforms the conventional single-objective Classical Transportation Problem (CTP) by producing higher solution quality and more balanced performance. Overall, the findings demonstrate that the proposed hybrid method is a robust decision-support tool for sustainably enhancing the resilience of international logistics planning in emerging economic regions. Full article

Point clouds are widely used to represent 3D visual content in immersive media, digital twins, and autonomous systems, but acquisition, compression, transmission, and rendering can introduce visible geometry and attribute distortions. Full-reference point cloud quality assessment (FR-PCQA) aims to predict the perceptual quality of a distorted point cloud by comparing it with a reference. A reliable FR-PCQA model should consider both the perception of 3D content by the human visual system via projected views and the manifestation of quality degradation in the point cloud geometry, color, and spatial structure. In this paper, we propose a multi-view projection and 3D feature fusion model for FR-PCQA. The proposed model integrates two complementary branches. In the projection branch, DISTS is applied to multi-view renderings aligned with the reference to capture perceptual similarity, and an additional six groups of geometric and photometric fidelity features (e.g., occupancy, depth fidelity and gradient domain fidelity) are developed to describe explicit geometric and photometric differences in the projected observations. In the 3D Feature Fusion branch, PCQM measures local geometry and color degradation, while a global structural descriptor with eight groups covering point count, position, scale, spatial distribution, and density is constructed to characterize the global properties of point clouds. Finally, a gradient boosting regression tree (GBRT) regressor is employed to predict the final quality score. Extensive experimental results show that the Spearman rank order correlation coefficient (SROCC) values are 0.91537, 0.9101, and 0.9778 on the SJTU-PCQA, WPC, and ICIP2020 datasets, respectively, outperforming the existing PCQA methods. These results indicate that the proposed multi-view projection and 3D feature fusion model provides an accurate and interpretable solution for FR-PCQA. Full article

Oil palm plantations play an important role in agricultural production and carbon storage in tropical regions. The accurate estimation of aboveground carbon (AGC) is essential for sustainable plantation management, climate change mitigation, and carbon monitoring. Although field measurements provide reliable estimates, they are often time-consuming, labor-intensive, and costly, particularly over large plantation areas. Recent advances in remote sensing and machine learning offer efficient alternatives for AGC estimation using satellite imagery. In this study, we developed a machine learning framework for AGC estimation in oil palm plantations using Sentinel-2 multispectral imagery and Sentinel-1 synthetic aperture radar (SAR) data. Field measurements were integrated with spectral variables, vegetation indices, and SAR-derived parameters extracted from satellite data. A hybrid feature selection approach combining Pearson correlation, mutual information and mRMR was used to identify the most relevant variables. Six machine learning algorithms were evaluated, including Linear Regression, Random Forest, XGBoost, Gradient Boosting, LightGBM, and Extra Trees. Because the 160 observations comprise sixteen 10 m × 10 m grid cells nested within ten 40 m × 40 m field plots, model performance was assessed with leave-one-plot-out cross-validation: all sixteen cells of a plot were held out together, and the hybrid feature selection was repeated inside every fold using only that fold’s training plots. Performance was measured on pooled out-of-fold predictions using R², root mean squared error (RMSE), and average absolute relative error (AARE%). Under this spatially independent design the combined Sentinel-1 + Sentinel-2 dataset gave the highest accuracy (R² = 0.7950, RMSE = 4.14 t C ha⁻¹, AARE = 33.53%), followed by Sentinel-1 alone (R² = 0.7631, RMSE = 4.46 t C ha⁻¹) and Sentinel-2 alone (R² = 0.6108, RMSE = 5.71 t C ha⁻¹). Linear Regression and Extra Trees were the most robust models, whereas the boosted ensembles did not generalize to unseen plots. Repeating the evaluation with an ungrouped random split of the same data inflated R² by up to 0.70, showing that a large part of the accuracy obtainable under that design reflects within-plot spatial autocorrelation rather than predictive skill. These findings indicate that optical-SAR imagery combined with machine learning can provide useful AGC estimates in oil palm plantations, and that spatially independent validation is essential for reporting them honestly. The proposed framework can be used to support plantation-scale carbon mapping, monitoring, and carbon stock assessment, subject to further calibration and independent validation across additional plantations. Full article

Estuaries support distinct spawning and nursery habitats for migratory fishes, yet the differential environmental response patterns between these two critical early life habitats remain poorly understood from a spatial non-stationarity perspective. Based on six ichthyoplankton surveys conducted during peak and late spawning seasons from 2018 to 2020 in the Yangtze Estuary, this study applied geographically weighted regression (GWR) models to quantify the spatially varying effects of sea surface temperature, sea surface salinity, chlorophyll-a, water depth and distance to coast on the distributions of Coilia mystus eggs and larvae. The results reveal clear divergence in both spatial pattern and environmental drivers between spawning and nursery habitats. Spawning grounds were persistently concentrated in the middle reaches of the South Branch, and shifted approximately 10 km upstream during the spring saltwater intrusion event in 2020. Nursery grounds, by contrast, formed a stable dual-core structure, with the northern core at the North Branch mouth consistently supporting higher larval densities than the southern core in the North and South Passages. Salinity was the primary limiting factor for spawning in spring, while temperature dominated in summer, and chlorophyll-a was never retained in optimal egg models. For larvae, chlorophyll-a emerged as a consistent key driver alongside salinity and temperature, and local regression coefficients spanned a wider range than those for eggs, indicating greater spatial heterogeneity in larval distribution–environment relationships. This study provides the first comparative analysis of spatially non-stationary environmental controls on spawning versus nursery habitats of C. mystus, and offers empirical support for stage-specific habitat conservation and fisheries management in the Yangtze Estuary. Full article

Old urban areas face severe spatial supply–demand contradictions as aboveground space nears saturation while public service demand grows. Developing underground public spaces offers a key solution, yet fragmented development limits overall benefits, necessitating coordinated aboveground–underground development to achieve urban renewal and sustainability. Taking Shanghai’s old urban areas as a case, this study constructs an evaluation system with 17 aboveground indicators across 5 dimensions and 9 underground indicators across 3 dimensions. Using the combination of AHP–entropy weight method for weighting, the coupling coordination degree model, and the obstacle degree model, this study identifies the temporal evolution trends in the development levels of the two systems, the characteristics of their coupling coordination stages, and the main constraining factors from 1995 to 2025. The results show: (1) Both systems have shown continuous growth, with underground public space accelerating its development after 2010, and by 2015, it had nearly caught up with the aboveground system in the time-series projection results; (2) The D value of coupling coordination has increased from 0.2431 to 0.9532, experiencing three stages of low coupling coordination, general coupling coordination, and high coupling coordination; (3) The obstacle factors have shown a dynamic evolution path from scale shortage to morphological complexity, and then to the synergy of the aboveground and underground morphologies. In the higher coupling coordination stage, the length of the aboveground bus lines and the landscape shape index of the underground became the dominant obstacles. This study provides a quantitative basis for coordinated planning and decision-making in the renewal of old urban areas. Full article

Long-term soil-moisture trends on the Chinese Loess Plateau are inferred from gridded products, but product choice can alter whether change is read as drying or wetting. We audited trends from the Global Land Data Assimilation System (GLDAS), ECMWF Reanalysis v5 Land (ERA5-Land), Soil Moisture of China by in situ data (SMCI), and Global Land Evaporation Amsterdam Model root-zone soil moisture (GLEAM SMrz) for 2001–2022, with an endpoint-extension test to 2025. We compared product-specific trends, spatial agreement, core-product medians, product-set bridge and leave-one-out sensitivities, and associations with precipitation, vapor pressure deficit, forest–shrub–grass cover change, and a potential-storage proxy. The core products shared substantial detrended interannual variability, yet their regional trend point estimates did not converge in sign. GLDAS gave a positive regional Sen-slope estimate, whereas ERA5-Land, SMCI, and GLEAM SMrz gave negative estimates. The core-product median was negative over 72.7% of the study area, but unanimous decline occurred over only 24.9%, and 63.5% showed mixed product signs. Only 36.9% of the area retained direction across all five robustness checks, and no environmental variable achieved repeatable same-direction support across all core products. Hydrologically, these results indicate that apparent Loess Plateau wetting or drying should be interpreted as product-dependent evidence of soil-water availability rather than as a universally robust soil-moisture trend or direct environmental response. Full article

Equitable access to dental care across Germany remains constrained by geographic barriers, yet traditional provider-to-population ratios fail to capture spatial complexity. This study employed a Modified Huff Three-Step Floating Catchment Area (MH3SFCA) method to quantify dental care accessibility at the ZIP-code level across all 8171 German postal code zones, integrating 2022 Census demand data, 38,023 dental facilities, and network-based travel times. Results revealed stark geographic disparities: accessibility exhibited strong positive spatial autocorrelation (Moran’s I = 0.97, p < 0.001), with 22.6% of the population in high-access urban clusters concentrated in Berlin, Hamburg, and the Rhine-Ruhr region, while statistically significant cold spots affected only a small share of the national population but formed geographically persistent clusters in rural and peripheral regions. The Gini coefficient of 0.55 indicated moderate overall inequality, substantially higher than for physician distribution (Gini = 0.19). Regional heterogeneity was prominent: Mecklenburg-Western Pomerania had 74.9% of its population in the lowest accessibility quartile (mean index = 0.7), while Berlin achieved near-universal high access (mean = 15.3). The MH3SFCA framework provides German planning bodies with a dynamic tool for routine accessibility monitoring and scenario analysis, supporting targeted, place-based workforce interventions that move beyond static mapping toward more equitable distribution of dental care. Full article

In recent years, the agentive role of youth groups in urban regeneration has garnered increasing academic attention. As vital carriers of urban cultural heritage, the ways in which historic districts can leverage youth dynamics to achieve vitality revitalization have emerged as a key research issue. This study selects the Fayuan Temple Historic and Cultural District in Beijing as an empirical case, constructs a public space evaluation system grounded in the concept of “youth-friendliness,” adopts a mixed-method approach integrating field surveys, questionnaire administration, and multi-source data mining, and employs Importance–Performance Analysis (IPA) modeling for deconstruction. Based on behavioral characteristic differences, youth within the district are categorized into two groups: “resident/local youth” and “transient visiting youth.” The comprehensive experience quality scores were 3.559 (Fair) for resident and local youth and 3.85 (Fair) for temporary visitors, with cultural space scoring highest for both groups. Resident youth demonstrate stronger demands for renewal concerning the completeness of cultural facilities, diversity of commercial formats, and street navigability. Transient visiting youth, by contrast, exhibit greater concern for eight factors: pedestrian safety and comfort, static traffic order, diversity of commercial formats, quality of consumption environment, richness of social venues, pleasantness of spatial scale, landscape interactivity, and street navigability. These findings indicate that youth groups with varying interactive relationships with historic districts possess significantly heterogeneous needs regarding public space utilization, and their expectations for historic district regeneration also manifest differentiated characteristics. This provides a scientific basis for formulating precise, multi-layered strategies for district renewal. Full article