Search Results (121)

Cropland abandonment is increasing in the upper and middle Yangtze River Basin due to complex terrain, urbanization, and labor migration. This threatens regional food security. To address the challenge of monitoring abandonment in fragmented hilly areas, we developed a framework. We integrated machine learning with time-series analysis. We mapped cropland probability using multi-source remote sensing data, random forest, and kernel density estimation, then applied LandTrendr to detect land-use changes and track the spatiotemporal evolution of abandonment from 2000 to 2022. Next, we combined Geodetector and linear regression to identify driving factors. The results show that abandoned cropland exhibited an increasing trend from 2000 to 2010, with an average annual growth rate of 20.4%. From 2010 to 2013, the area of abandoned cropland declined rapidly, decreasing by 44.6%. Between 2013 and 2022, abandoned cropland decreased steadily, with an average annual reduction rate of 24.7%. Spatially, abandonment was clustered in the central mountains and southern hills. Key drivers included distance to towns (DtT), total grain output (GTO), and GDP. Our approach supports cropland management and rural revitalization in regions with complex terrain. Full article

Currently, pore fractal characteristics of deep marine–terrestrial transitional coal-measure mudstones in the central Sichuan Basin remain poorly understood. To clarify the pore fractal characteristics and their controlling factors, seven representative deep mudstone samples were collected from the Longtan Formation of Well NT1H in the Suining area, central Sichuan Basin. These samples were subjected to total organic carbon (TOC) content determination, vitrinite reflectance (Ro) measurement, X-ray diffraction (XRD) analysis of whole-rock and clay minerals, and low-pressure nitrogen adsorption (LPN₂A) experiments. Pore fractal dimensions were calculated based on the Frenkel–Halsey–Hill (FHH) theoretical model. The influences of mineral composition, organic geochemical characteristics, and pore structural parameters on pore fractal dimensions were analyzed. The results indicate that shale pores in the study area are predominantly developed as mesopores, exhibiting dual fractal characteristics; fractal dimension D1 (structural fractal dimension at high-pressure segment) ranges from 2.6662 to 2.7366, and fractal dimension D2 (surface fractal dimension at low-pressure segment) ranges from 2.5895 to 2.6363. Mineral composition exerts differential control over pore fractal dimensions. The effects of organic matter content and thermal evolution degree on fractal dimensions exhibit stage-dependent characteristics. Correlations between pore structural parameters and fractal dimensions indicate that small-aperture pores (micropores and mesopores) constitute the primary factor controlling pore heterogeneity in shales. These findings provide a theoretical basis for “reservoir evaluation” and “sweet spot” optimization of deep marine–terrestrial transitional coal-measure shales in central Sichuan Basin. Full article

Precise, spatially explicit sub-provincial GDP estimates are essential for regional planning, especially in mountainous areas where official economic data remain spatially coarse and unevenly distributed. This study develops a multisource county-level GDP spatialization framework for Sichuan Province, China, integrating corrected NPP/VIIRS nighttime-light (NTL) data with Points of Interest (POIs), land-use structure indicators (proportion of farmland (PFL); proportion of construction land (PCL)), elevation, precipitation, accessibility and population density within a unified indicator system. Two regression approaches—Ordinary Least Squares (OLS) as a global benchmark and Geographically Weighted Regression (GWR) as the spatially adaptive primary model—are calibrated on county-level cross-sectional data for 2020 (n = 183) and evaluated using R², adjusted R², AICc and residual spatial diagnostics. The multisource GWR model achieves R² = 0.882 (adjusted R² = 0.872, AICc = 5712.26), substantially outperforming both the global OLS benchmark (R² = 0.801) and NTL-only GWR baseline (R² = 0.662), confirming that spatial nonstationarity is an intrinsic feature of the GDP–proxy relationship and that integrating complementary geospatial proxies is the primary pathway to improved estimation accuracy in topographically heterogeneous regions. The GWR-based GDP surface exhibits a pronounced basin–plateau contrast: high-value clusters concentrate along the Chengdu Plain and adjacent city corridors, while extensive low-value zones prevail across the western highlands (global Moran’s I = 0.33, Z = 14.26, p < 0.001). Spatially varying GWR coefficients reveal that elevation and precipitation constrain GDP most strongly in high-altitude counties, construction land exerts a consistently positive but spatially graded effect, and the influences of accessibility and population density are context-dependent and locally differentiated. These findings support differentiated territorial development policies: plateau counties require accessibility-first strategies; hill counties benefit from targeted small-city industrialization; and basin cores need managed growth to balance agglomeration advantages against congestion pressures. The framework relies exclusively on globally or nationally available data and is portable to other mountainous regions, though cross-regional validation and extension to multi-year panels using geographically weighted panel regression remain important directions for future work. Full article

The Tibetan Plateau (TP) experienced significant climatic transitions and tectonic uplift during the Middle Miocene. Little is known about plant diversity changes and their relationship with climatic and tectonic processes in spite of extensive reconstructions of vegetation change over this period. Based on palynological assemblages spanning ~15–12 Ma from the Lunpola Basin, we quantitatively reconstruct the evolution of plant diversity around the Middle Miocene Climatic Transition (MMCT) in the central TP. Plant taxa richness and evenness of three groups of tree, shrub and herb, and pteridophyte are estimated using Hill numbers methods. Three distinct diversity phases are identified. From ~15 to 14.2 Ma, plant richness gradually increased while evenness decreased, possibly due to the development of vertical vegetation zones driven by the uplift of the central TP. From ~14.2 to 13.8 Ma, richness dropped sharply in response to rapid climatic deterioration in the MMCT. From ~13.8 to 12 Ma, both richness and evenness increased under fluctuations, associated with paleo-lake shrinkage and expansion of lakeside wetlands caused by persistent plateau uplift and climatic aridification. Long-term changes in plant diversity within the Lunpola Basin were influenced by global climate changes, the uplift of central TP, and regional hydrological dynamics during the Middle Miocene. Our findings provide paleoecological insights into the coevolution of TP growth, climate change, hydrological process, and biodiversity of alpine ecosystem. Full article

Gully erosion is a significant threat to the sustainability of soil in Mediterranean basins. Despite its impact, there is a lack of research providing accurate regional-scale cartography of complete gully networks. This study aims to automatically map the gully network in the olive-growing landscapes of the Guadalquivir basin (Spain) using Machine Learning (ML) algorithms: Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR). We integrated these models with 17 predictive variables (including hydrotopographic, climatic, and edaphic factors) and the Gully Head Initiation (GHI) index. RF was the most suitable model, achieving an Area Under the Curve (AUC) of 0.91 and an F1-score of 0.83, and enabled the delineation of a gully network totalling 8439.05 km. Variable importance analysis revealed that flow accumulation (17.33%) and the GHI index (nearly 30%) were the primary predictors, with the Rainy Day Normal (RDN)-based formulation outperforming the maximum daily precipitation (Pmax)-based one. Spatially, countryside hill landscapes exhibited the highest gully densities (42.50 m/ha). The results demonstrate the effectiveness of combining ML with physically based indices to generate high-resolution gully cartography for soil conservation planning in Mediterranean olive groves. Full article

Solanum rostratum is a globally regulated invasive species, known for its detrimental impacts on local biodiversity, human and livestock health, and agricultural productivity. This study employed the Biomod2 ensemble modeling framework to analyze the geographic distribution of S. rostratum in China, identify key environmental factors limiting its spread, and provide a scientific basis for its management and control. By integrating species distribution data with multiple environmental variables, we predicted the potential geographic distribution of this species. Pearson correlation analysis and variance inflation factor (VIF) testing were applied to identify significant environmental variables constraining its spread, including precipitation seasonality (bio15), mean temperature of the wettest quarter (bio8), precipitation of the warmest quarter (bio18), isothermality (bio3), precipitation of the driest month (bio14), and human footprint. Three Biomod2-based ensemble models (EMmean, EMca and EMwmean) were based on the receiver operating characteristic curve (ROC), true skill statistic (TSS), and Kappa coefficient. Of these, EMca demonstrated the highest predictive accuracy. The model identified highly suitable habitats for S. rostratum primarily in semi-arid and semi-humid regions with high human activity, including the Northeast Plain, bounded by the Greater Khingan, Lesser Khingan, and Changbai Mountains; the northern North China Plain extending to the Shandong Hills and Yellow River basin; and the Junggar Basin extending to the Altai Mountains. These regions should be prioritized for future monitoring and control efforts. This study provides both empirical data and theoretical insights to accurately delineate potential invasion zones of S. rostratum, enhancing surveillance and guiding effective prevention and control strategies. Full article

Low-maturity shale is a prime target for in situ conversion (ICP), yet heating window selection remains largely empirical because pore evolution and hydrocarbon generation are rarely quantified in tandem. Nenjiang Formation shale from the Songliao Basin (TOC = 8.91%; R_o,max = 0.54%) was subjected to closed-system pyrolysis at 300–500 °C (20 °C h⁻¹; 72 h per step). Released oil and gas and residual chloroform-extractable bitumen (“A”) were quantified, and pore evolution was characterized using 2D low-field NMR, SEM, micro-CT, and low-pressure N₂ adsorption. Fractal dimensions (D_s and D_p) were derived from Frenkel–Halsey–Hill (FHH) fitting. Oil yield and bitumen “A” increased sharply above 350 °C and peaked at 375 °C, whereas gas generation accelerated above 400 °C and continued to increase to 500 °C. NMR indicates a temperature-dependent shift in retained hydrocarbons toward weaker confinement and higher mobility, with enhanced expulsion/mobility signals near 375 °C. At 375 °C, BJH pore volume and average pore diameter reached maxima (0.0675 cm³ g⁻¹ and 15.36 nm), while D_s and D_p reached minima (2.343 and 2.444). The coincidence of peak oil expulsion with minimum fractal complexity suggests that FHH-based fractal indices provide a quantitative metric for comparing ICP heating windows in low-maturity shale. Full article

Dry forests are increasingly threatened by degradation, which determines their structural integrity, functional capacity, and the ability to provide essential ecosystem services. Degradation is the consequence of processes that reduce the different attributes of forests. This study aimed to (i) identify remote sensing proxies for above-ground biomass (AGB) and tree regeneration in three ecoregions of dry forest localized in west Argentina; (ii) analyze the temporal dynamics between 1993 and 2023; (iii) assess the role of precipitation in their temporal variability, and (iv) map their spatial distribution. The median Tasseled Cap Transformation Wetness (TCTW) was the best-performing spectral proxy for AGB, while median Enhanced Vegetation Index (EVI) best captured tree regeneration. In the time series of TCTW, no significant breakpoint was detected; however, a pronounced decline in the median EVI occurred in 1998 in the Monte of Plains and Plateaus and Monte of Hills and Basins ecoregions, particularly near watercourses. In the Dry Chaco, tree regeneration recovered after 2013; however, a decline after a breakpoint coincided with decreased precipitation. Overall, AGB and tree regeneration exhibited contrasting temporal and spatial patterns, underscoring the heterogeneity of dry forests. A weakening relationship between precipitation, a key driver of forests, and forest attributes suggests the influence of other factors, including topography and land use change. Full article

The western Kuqa Foreland Basin exhibits complex hydrocarbon distribution with unclear accumulation processes. This study integrated seismic data, microscopic observations, crude oil properties, and basin modelling to establish a dynamic hydrocarbon migration model for the study area. The results indicated two distinct accumulation phases. During the early phase (16–5 Ma), hydrocarbons migrated eastward along a single unconformity and accumulated in the buried-hill reservoir of well E937 in the southern part of the Baicheng hydrocarbon-generating depression. In contrast, the southwestern region failed to accumulate hydrocarbons because of its distance from the Triassic source rock hydrocarbon generation centre and complex migration pathways. During the late phase (5–0 Ma), the Jurassic hydrocarbon generation centre shifted westward, and hydrocarbons migrated through a composite conduit system comprising faults, weathered crust, and sandstone structural ridges. This process promoted the expansion of the eastern E937 well trap, whereas well WEN54 and other southwestern wells exhibited hydrocarbon accumulation potential. The simulation results predicted that hydrocarbon reservoirs in the eastern region were mainly concentrated in the Qiulitage structural belt east of well E938. This study provides a theoretical basis and predictive guidance for hydrocarbon exploration in this area. Full article

The Colombian Orinoquia was shaped within a tectonic and sedimentary framework linked to the uplift of the Andean cordilleras during the Oligocene–Miocene. This orogenic event generated two tectonic fronts and facilitated extensive fluvial sedimentation across a broad alluvial geosyncline. The present geomorphological configuration reflects the cumulative interaction of tectonic and erosional processes with Quaternary climatic dynamics, which together produced complex landscape assemblages characterized by plains with distinctive drainage patterns. To delineate and characterize geomorphological units, we employed multidimensional imagery and Machine Learning techniques within the Google Earth Engine platform. The classification model integrated dual polarizations of synthetic aperture radar (L-band) with key topographic variables including elevation, slope, aspect, convexity, and roughness. The analysis identified three major physiographic units: (i) the Foothills and the Floodplain, both dominated by fluvial environments; (ii) the High plains and Serranía de La Macarena (Macarena Mountain Range), where denudational processes predominate; and (iii) localized aeolian environments embedded within the Floodplain. These contrasting dynamics have generated a broad spectrum of landforms, ranging from terraces and alluvial fans in the Foothills to hills and other erosional features in La Macarena. The Floodplain, developed over a sedimentary depression, illustrates the combined action of fluvial and aeolian processes, whereas the High plains is characterized by rolling plains and peneplains formed through the uplift and erosion of Tertiary sediments. Such geomorphic heterogeneity underscores the interplay between tectonic activity, climatic forcing, and surface processes in shaping the Orinoquia landscape. The geomorphological classification using Random Forest demonstrated high effectiveness in discriminating units at a regional scale, with accuracy levels supported by confusion matrices and associated Kappa indices. Nevertheless, some degree of classificatory overlap was observed in fluvial environments, likely reflecting their transitional nature and complex sedimentary dynamics. Overall, this methodological approach enhances the objectivity of geomorphological analysis and establishes a replicable framework for assessing landform distribution in tropical sedimentary basins. Full article

With the intensification of global warming, surface thermal environment issues have become increasingly prominent, particularly in the ecologically fragile Yellow River Basin (YRB). However, most studies neglect the synergistic effects of underlying surface composition and geomorphological context, limiting the understanding of regional thermal contribution patterns. Based on MODIS-derived land surface temperature and Landsat 8-based land use and Fathom DEM-derived geomorphological datasets, this study constructs an integrated assessment framework combining a dual “quality–quantity” perspective with land use–geomorphology coupling, systematically analyzing the comprehensive thermal contributions of different underlying surfaces. Results show that (1) the YRB features diverse underlying surfaces, transitioning from natural (forest, grassland) to human-dominated (cropland, construction land) land uses, and from high-altitude, large undulating mountains to low-altitude, small undulating plains along the source-to-downstream gradient. (2) The average LST is 17.97 °C, displaying a south–north and east–west gradient. Human disturbance intensity drives thermal responses at the land use level, with natural surfaces contributing to cooling regulation, while artificial and desert surfaces generate heat accumulation. Geomorphology jointly shapes the thermal distribution, with high mountains acting as cold sources and plains/hills as heat sources. (3) Dual “quality–quantity” dimensional evaluation reveals that temperature-based assessments alone overestimate localized extremes (e.g., towns, extremely high mountains) and underestimate broad, moderate surfaces (e.g., drylands, large and medium undulating high mountains). This “area-neglect effect” may lead to biased regional thermal assessments and unbalanced resource allocation. (4) Coupled land use–geomorphology analysis uncovers the multi-scale composite mechanisms of thermal formation and mitigates single-factor assessment biases. Geomorphology defines macro-scale energy exchange, while land use regulates local heat responses. The results provide scientific support for large-scale thermal assessment and refined management. Full article

The factors influencing urban pluvial flooding in cities with complex topography, such as hill–basin systems, are highly nonlinear and spatially heterogeneous due to the interplay between rugged terrain and intensive human activities. However, previous research has predominantly focused on plain, mountainous, and coastal cities. As a result, the waterlogging mechanisms in hill–basin areas remain notably understudied. In this study, we developed a geographically explainable artificial intelligence (GeoXAI) framework integrating Geographical Machine Learning Regression (GeoMLR) and Geographical Shapley (GeoShapley) values to analyze nonlinear impacts of flooding factors in Changsha, a typical hill–basin city. The XGBoost model was employed to predict flooding risk (validation AUC = 0.8597, R² = 0.8973), while the GeoMLR model verified stable nonlinear driving relationships between factors and flooding susceptibility (test set R² = 0.7546)—both supporting the proposal of targeted zonal regulation strategies. Results indicated that impervious surface density (ISD), normalized difference vegetation index (NDVI), and slope are the dominant drivers of flooding, with each exhibiting distinct nonlinear threshold effects (ISD > 0.35, NDVI < 0.70, Slope < 5°) that differ significantly from those identified in plain, mountainous, or coastal regions. Spatial analysis further revealed that topography regulates flooding by controlling convergence pathways and flow velocity, while vegetation mitigates flooding through enhanced interception and infiltration, showing complementary effects across zones. Based on these findings, we proposed tailored zonal management strategies. This study not only advances the mechanistic understanding of urban waterlogging in hill–basin regions but also provides a transferable GeoXAI framework offering a robust methodological foundation for flood resilience planning in topographically complex cities. Full article

This paper presents the results of a research project on the use of stone in Roman architecture in Oderzo and Concordia Sagittaria, located between the Tagliamento and the Piave rivers (Italy). The study involved a documental survey, material sampling and analysis, provenance identification, and interpretation of results to reconstruct ancient stone trade routes. During sampling, 33 carbonate rock specimens were collected from archaeological sites and architectural elements in Oderzo, and 52 from Concordia Sagittaria. In both cities, these rocks were primarily used for architectural elements such as columns and capitals, whereas these lithotypes were less frequently employed in structures and infrastructures. The analysis revealed a significant reliance on regional limestones. Petrographic examinations (PLM-TL) identified six main limestone groups, many of which were linked to quarries located in the Aurisina and in the Triestine Karst region, as well as in the Prealps and Berici Hills. The study encountered several challenges: many analysed samples displayed petrographic characteristics consistent with multiple sources, complicating the precise identification of their extraction site. Despite a detailed understanding of the region’s geology, reference geological datasets often overlook outcrops that may have been exploited in antiquity. Consequently, when samples lacked distinctive features, tracing them to a particular quarrying basin proved difficult. In conclusion, the research underscores the extensive use of local limestones while acknowledging the challenges posed by limited petrographic reference data, which hinder the precise identification of the source basins of the materials used in Roman construction. Full article

Mountainous urban areas like Guiyang face unique fire safety challenges due to rugged terrain and complex road networks, which hinder fire station accessibility. This study proposes a GIS-based framework that integrates nighttime light (NPP/VIIRS) and point of interest (POI) data to assess fire risk and accessibility. Kernel density estimation quantified POI distributions across four risk categories, and the Spatial Appraisal and Valuation of Environment and Ecosystems (SAVEE) model combined these with NPP/VIIRS data to generate a composite fire risk map. Accessibility was evaluated using the enhanced two-step floating catchment area (E2SFCA) method with road network travel times; 80.13% of demand units were covered within the five-minute threshold, while 53.25% of all units exhibited low accessibility. Spatial autocorrelation analysis (Moran’s I) revealed clustered high risk in central basins and service gaps on surrounding hills, reflecting the dominant influence of terrain alongside protected forests and farmlands. The results indicate that targeted road upgrades and station relocations can improve fire service coverage. The approach is scalable and supports more equitable emergency response in mountainous settings. Full article

The Lop sheep (LOP), a unique local breed from Xinjiang, exhibits remarkable resilience to the harsh conditions of a desert arid climate and frequent sandstorms, alongside notable fecundity characteristics. This study aims to investigate the adaptability of LOP within this challenging environment by collecting whole blood samples from 110 LOP individuals in the Lop Nur region of Xinjiang for genome resequencing. The resulting data will be compared with whole genome resequencing information from 22 local sheep breeds worldwide to analyze the origin and evolution of LOP. Additionally, comparisons will be made with HUS sheep from warm and humid regions to identify genomic differences through selection signal analysis, thereby assessing the impact of a desert arid climate on the extreme living conditions of LOP. Finally, qPCR was used to preliminarily analyse the impact of the desert arid climate on the genome of the Bactrian sheep. Genetic diversity results indicate that LOP exhibits a relatively stable genetic structure alongside high genetic diversity. The results of population structure analysis and gene flow indicate that we can tentatively posit that LOP is a breed that originated from the Middle East, subsequently mixing with MGS upon its arrival in Xinjiang. Chinese local sheep breeds trace their origins to AMS, with the gene flow evolving from west to east, progressing through mountainous hills (BSBS), basins (LOP, HTS, CLHS, DLS), plains (MGS, TANS), and coastal areas (HUS). LOP is associated with ALTS, BSBS, HTS, CLHS, and DLS, as well as with MGS, HUS, TANS, WDS, and SSSP, in a context of gene exchange, with the degree of exchange diminishing in that order. Selection signal analysis revealed that the candidate genes identified are closely related to adaptation to desert arid climates and disease resistance (PDGFD, NDUFS3, ATP1B2, ITGB8, and CD79A), using HUS as the reference group. qPCR results demonstrated that LOP was significantly upregulated in cardiac, splenic, and lung tissues compared to HUS, suggesting that LOP plays a crucial role in cardiac function, immune response, and respiratory capacity. Full article