Open Geosciences

In the land classification problem, although the application of land data and remote sensing technology can provide a lot of data, the difference of data quality, data format, and data sources lead to the difficulty of land classification. Therefore, a land use classification method based on remote sensing image and multi-source data was proposed. The multi-structure element binary morphology is used to carry out the corrosion operation on the mutation pixels in the remote sensing image to complete the denoising. Based on this, the chaotic leapfrog algorithm is used to enhance the denoised remote sensing image. Through the fusion of multi-source feature data, the spatial information of remote sensing image is combined with the attribute information of other data sources to extract spectral and shape features and complete the classification of land use. The experimental results show that the R ² value of the proposed method is 0.97, the MAE value is 0.09, and the Kappa coefficient remains above 0.9. This indicates that the method can effectively enhance the features of land remote sensing images through remote sensing and multi-source data fusion, and has ideal accuracy for multi-class land use classification, which can achieve accurate classification of land use.

Timely acquisition of geological structure information is crucial for large-scale water conservancy and hydropower projects. Understanding surrounding rock structure is critical for rock deformation analysis and geological evaluation of hydraulic adits. This study proposes a new method of OC-AINet to achieve efficient and accurate recognition of geological structure information of large hydraulic adits. An ordinary digital camera is used to obtain images of the Heishanxia adit, and dense point clouds are generated through multi-view stereo reconstruction. 2D–3D feature semantic super-pixel blocks are segmented by combining color, texture, and other geological semantics with AINet, and then a hierarchical regional clustering is carried out for rock structural planes extraction. The experimental results show that the difference between the rock structural plane identification error of the proposed method and that of the traditional manual method is less than 5 degrees, which meets the requirements of geological analysis. In addition, it has higher efficiency and safety than the manual method. The proposed OC-AINet has significantly improved the accuracy and reliability of the segmentation results and promotes the application of photogrammetry technology in geological scenes, especially in hydraulic adit environments.

Eutrophication of water bodies is a major ecological problem associated with increased input of nitrogen and phosphorus during rapid economic development. The abundance of chlorophyll-a (Chl-a) in aquatic systems serves as a reliable ecological indicator of lake water quality that is strongly correlated to the degree of eutrophication. Using multi-source remote sensing data – including Landsat and Sentinel-2 imagery – and employing Theil-Sen median analysis, the Mann–Kendall trend test, and Pearson correlation analysis, we comprehensively examined the spatial and temporal dynamics, as well as the driving forces, of Chl-a concentrations in medium and large lakes (lake area >10 km²) across China from 1986 to 2023. The results showed that, over the past four decades, Chl-a concentration in Chinese lakes generally exhibited a declining trend, with a more pronounced decrease occurring after 2013. Significant regional disparities were observed: lakes in the southwestern region demonstrated the most pronounced declines, while those in the southern region exhibited the least. Seasonal variability in Chl-a was consistent across the country, with concentrations peaking between July and August and reaching their lowest levels from November to March. Nevertheless, the extent of seasonal variation differed regionally, being lower in western China and greater in the eastern and southern regions. Land surface temperature, water vapor content, and soil moisture showed strong positive correlations with Chl-a concentrations, while elevation and wind speed displayed negative correlations. These relationships also varied significantly in geographic subregions. Overall, the study revealed the spatiotemporal patterns and driving mechanisms of Chl-a dynamics in Chinese lakes and highlighted the spatial heterogeneity of ecological and geographical influences on Chl-a concentrations.

Underground coal mining impacts surface deformation not only during mining operations but also after mine closures, potentially causing prolonged subsidence or uplift. Long-term predictions of surface deformation in closed mining areas remain challenging, as traditional statistical methods have limited capability in modeling complex spatiotemporal deformation patterns. To address this, this study utilized the small base line subsets interferometric synthetic aperture radar technique to derive deformation results in the line-of-sight direction for the study area. A long short-term memory (LSTM) neural network combined with the gray wolf optimizer (GWO) algorithm was introduced to improve prediction accuracy. Experimental results showed that the LSTM model achieved a correlation coefficient of 0.93 with the observed data, while the GWO–LSTM model further enhanced prediction accuracy with a correlation coefficient of 0.99, demonstrating its potential for complex deformation prediction. The findings provide a scientific basis for surface deformation prediction and risk assessment in closed mining areas and have practical significance for disaster warning and decision-making in the region. As synthetic aperture radar data availability continue to grow, this method holds promise for broader applications in other geological environments.

Iron (Fe) is an essential trace element for the growth of phytoplankton in the ocean. Humic substances (HSs) are key components of dissolved Fe-binding organic ligands (Lt). Both Lt and HSs are widely accepted to regulate the distribution of dissolved iron (DFe) and influence its availability to marine phytoplankton and other organisms. This paper provides a concise overview of the historical progression of DFe determination and its speciation, including Lt and HSs, using electrochemical methods. It also reviews applications of these methods in examining the effects of HSs on DFe, drawing from spectroscopy, chromatography, and mass spectrometry data. Electrochemical techniques can measure the concentrations of HSs and the binding capacity of DFe, offering valuable insights into the role of HSs on DFe in marine settings. Spectroscopy, chromatography, and mass spectrometry allow for detailed characterization of the structure, properties, and types of organic ligands and HSs. These methodologies have enhanced our understanding of Lt and HSs, whether of marine or terrestrial origin, as significant ligands for DFe, influencing its concentration, distribution, and circulation. Future research should delve deeper into the mechanisms and chemical properties of Fe complexation with organic matter. Additionally, the impact of various factors on HSs complexes in relation to DFe warrants further exploration, benefiting from synchronous analysis using multiple detection methods. Such advancements would offer crucial insights into the biogeochemical cycling of Fe and enhance various research domains.

The United Nations sustainable development goals aim to promote global industrialization and innovation and achieve sustainable and inclusive economic development by 2030. The sustainable growth of provincial economies has emerged as a critical component of the national plan as China’s economy transitions to a new normal. This article builds an assessment index system encompassing the four "economy–society–ecology–innovation" dimensions to better assess the degree of sustainable economic development in China’s regions. It then uses the gray correlation analysis method to measure and analyze the sustainable economic development of China’s regions from 2006 to 2017. Additionally, the spatial evolution characteristics of each region’s sustainable economic development and spatial pattern are investigated through exploratory spatial data analysis and GIS spatial analysis techniques. This essay seeks to support the region’s economy in achieving sustainable development by offering theoretical underpinnings and useful advice for the creation of successful regional development plans. The study’s findings indicate that in 2017, the assessed value of the level of economic sustainability of China’s regions averaged 0.7156, an increase of 7.3% compared to 2006 while the degree of sustainable economic development in the rest of China, except Inner Mongolia, Shaanxi, and Xinjiang, has steadily increased between 2006 and 2017, the gap between the regions has also widened, with the eastern region having a much higher level of sustainable economic development than the central and western regions. An analysis of the spatial evolution reveals that the degree of sustainable economic development in every region of China generally increases in positive spatial correlation. Its spatial agglomeration is becoming increasingly apparent, with more regions becoming high-high-type and low-low-type agglomerations. Regional wealth disparities, ecological governance capabilities, and technological innovation levels were identified at the local level as essential factors for provincial economic sustainable development, with varying impacts across different regions.

Rapid urbanization in southern Saudi Arabia necessitates accurate geotechnical assessments to support sustainable development. However, the region lacks comprehensive seismic-based soil classification studies, raising concerns regarding construction safety. This study utilizes seismic refraction and tomography techniques to characterize soil properties and evaluate their appropriateness for infrastructure development. Ten seismic refraction and tomography surveys and two multichannel analysis of surface wave profiles were conducted to classify soil conditions based on seismic velocities and geotechnical parameters. The results reveal three distinct subsurface layers: (1) alluvial soil (V p = 300–940 m/s), (2) fractured basement (V p = 1,350–1,890 m/s), and (3) massive basement (V p > 2,400 m/s). According to National Earthquake Hazards Reduction Program criteria, soil classification identifies loose sediments (Class E) as unsuitable for construction, while stiffer deposits (Classes D and C) offer stable foundations. Integrating seismic techniques presents a cost-effective alternative to traditional drilling, providing a rapid assessment tool for urban planners. These findings aid in optimizing construction site selection, thereby minimizing risks associated with weak soil zones.

Background One of the best-studied subjects in the area is gold mineralization, and researchers have focused on the veins, their direct weathering products, or fluid inclusion analyses. Abu Khusheiba gold deposits in Jordan were characterized as epithermal deposits, and the wadi sediments below were investigated in some studies. Although epithermal mineralization is confirmed at Wadi Abu Khusheiba, part of the southern Jordanian Aheimer Volcanic Suite, the source of mineralizing fluids is uncertain. Among the most critical scientific issues is whether the fluids are magmatic, meteoric, or mixed, and what it would mean for gold deposition and resource potential. Moreover, the area lacks comprehensive geochemical and isotopic studies that would reveal fluid evolution, styles of alteration, and metal transport mechanisms. Stable isotope research (e.g., oxygen) in conjunction with mineralogical studies can shed light on mineralization sources and environments – addressing an important knowledge gap. Economically, fluid evolution knowledge is required to evaluate the future gold exploration potential of the Abu Khusheiba area. Results In accordance with stable isotope data (δ¹⁸O: 10.8 to 16.4‰), the fluids have a magmatic source with negligible meteoric water interaction. The evidence for a low-sulfidation epithermal system with constant state hydrothermal conditions comes from banded colloform quartz textures and potassic alteration. Such evidence enhances regional mineral exploration strategies as well as new ore-forming process understanding.

Digital terrain model (DTM) has wide-ranging applications in numerous fields, including natural resource management, urban planning, environmental protection, and disaster monitoring. Utilizing LiDAR data to generate DTM is now a mainstream method. In current applications, LiDAR data are still treated as having primarily additive errors; however, studies have shown that it is affected by both additive and multiplicative errors. From the perspective of error theory and surveying adjustment, it is theoretically inappropriate to treat mixed additive and multiplicative errors directly as additive errors, as each error model is based on a distinct theoretical framework. In view of this, we applied the mixed additive and multiplicative error theory to the generation of LiDAR-derived DTM products and validated its accuracy through two real measurement cases and one simulation case. The experimental results demonstrate that the mixed additive and multiplicative errors theory provides higher accuracy than the additive error theory in both DTM fitting and interpolation. This confirms that incorporating the mixed additive and multiplicative error theory into DTM product generation is beneficial.

Considering that the traditional Hoek–Brown model only accounts for strain hardening effects in rock materials, while many rock materials exhibit strain softening effects under large deformation, a modified Hoek–Brown model has been developed to simultaneously describe both material hardening and softening characteristics. This enhancement builds upon the traditional Hoek–Brown model by introducing plastic internal variables that characterize material damage or degradation. To address numerical singularities and convergence difficulties encountered during the implementation of the modified Hoek–Brown model, a function smoothing method is employed. The physical significance of model parameters in the modified model is clarified through theoretical analysis and single-factor variable analysis methods. Finally, the modified Hoek–Brown model is applied to practical engineering calculations. The study results demonstrate that the modified Hoek–Brown model can effectively account for both strain hardening and strain softening effects in materials. The function smoothing method proves to be effective in mitigating numerical singularities and convergence issues encountered in the implementation of the modified Hoek–Brown model. For soft rock tunnels, when significant displacements occur in the surrounding rock, both displacements and stresses around the tunnel calculated using the modified Hoek–Brown model are more consistent with engineering reality than those obtained using the traditional Hoek–Brown model. It is recommended to consider applying the modified Hoek–Brown model in practical engineering calculations.

This study provides a comprehensive assessment of environmental and human health risks associated with potentially toxic elements in the coastal sediments of the Gulf of Aqaba. A total of 33 sediment samples were analyzed using inductively coupled plasma mass spectrometry, revealing Fe (1,526–5,123 mg/kg), Zn (16.8–32.0 mg/kg), Pb (3.5–9.1 mg/kg), Co (2.2–6.4 mg/kg), and Cd (0.05–0.18 mg/kg). The concentrations detected were within acceptable limits and below the Interim Sediment Quality Guidelines, indicating minimal environmental risk. Environmental indices, including the pollution index, modified contamination degree, pollution load index, hazard index, and lifetime cancer risk indicate no contamination or health risks for adults or children through ingestion and dermal contact pathways. Principal component and correlation analysis suggest that Fe, Zn, and Co primarily originate from natural geological processes due to their strong association with elements typically derived from bedrock weathering, while minor anthropogenic contributions may arise from tourism and coastal activities. The findings confirm that the sediments pose no environmental or health risks, providing a baseline for future monitoring and pollution management in the Gulf of Aqaba.

The European green agenda aims to preserve the environment and climate, reduce CO2 emissions, and replace fossil fuels with renewable energy. It mostly relies on electric vehicles, energy storage, solar, and wind power plants. It requires an order of magnitude higher amount of critical minerals (In this text, the term minerals is often used for individual chemical elements, although it is common to refer to combinations of chemical elements that have a corresponding chemical composition, crystallization, and name.), poorly represented in the lithosphere, with problematic recycling, with extraction requiring considerable amounts of energy, fossil fuels and causing unacceptable damage to people and nature in countries that supply raw materials. Rising global average temperatures cast doubt on the overall effects of decarbonisation. The time frame of profit-oriented planning is too short and cannot respect the dynamics of the energy sector. Together with market uncertainty, regulations, and incentives did not encourage investors to take all the steps we had hoped for. The long-term needs and availability of key minerals are considered together with an overview of the financial and environmental conditions offered to the population in the countries where mining is carried out. Growing popular resistance to cheap and environmentally damaging mining and increasing demand for critical minerals may call into question the sustainability of current practices. The development of new technologies should be geared towards solutions that use abundant minerals in the lithosphere, while long-term sustainability requires, within a much-desired paradigm shift, that fair conditions be offered to the population of countries that supply critical minerals. The main objective of this article is to use scientifically based considerations to identify the key issues of the title topic, to assess this complex and multidisciplinary subject, and to draw feasible conclusions and recommendations.

Investigations into the complex pore–throat structures (PTS) of tight sandstone reservoirs are vital for optimizing waterflooding strategies. In this study, 13 cores from the Dingbian area of the Ordos Basin were examined using casting thin sections, X-ray diffraction, high-pressure mercury injection (HPMI), and nuclear magnetic resonance (NMR). These analyses quantitatively characterized mineral composition, petrophysical properties, PTS heterogeneity, and fluid mobility. Based on these findings, high-temperature and high-pressure waterflooding experiments were performed to explore dynamic waterflooding behavior and systematic factors influencing fluid mobility and waterflooding efficiency (E w). Results indicate significant differences in fluid mobility across four PTS types, transitioning from uniform displacement (type I) to finger displacement (type IV), with corresponding reductions in movable fluid saturation and E w. Residual oil morphologies evolve from dispersed membranes to continuous clusters and sheet shapes. Integrated HPMI and NMR analysis accurately delineates the full pore–throat size distribution (PSD) (0.0001–10 μm) that exhibit multi-fractal characteristics, enabling differentiation of macropores, mesopores, micropores, and nanopores. Micropores, which are relatively uniform, dominate reservoir petrophysical properties and serve as primary sites for movable fluids. Elevated clay mineral content augments PTS heterogeneity, lowers permeability, and promotes nonlinear seepage phenomena (blockage and bypassing), leading to more extensive residual oil accumulation and reduced E w. Overall, PTS heterogeneity emerges as the principal factor governing fluid mobility and E w, highlighting the importance of full PSD characterization and real seepage condition simulation in reservoir engineering. This study provides key insights into optimizing water injection strategies, suggesting that maintain a stable injection pressure and injection volume multiple of less than 2 pore volumes, while also considering clay mineral sensitivity.

Remote sensing images contain complex scene information and have multi-scale characteristics after being imaged by remote sensing equipment because the target instances in natural scenes are different sizes. In addition, small target instances are more difficult to identify in complex backgrounds, resulting in serious scale imbalance problems, which pose a serious challenge to identifying and positioning target objects. To address this problem, this article proposes a detection method for multi-scale remote sensing image targets by combining the frequency attention mechanism. The model first introduces an improved frequency channel attention mechanism to design a feature extraction module to improve the extraction of key features by the neural network; second, considering that the complete intersection over union method does not comprehensively consider the aspect ratio of the bounding box, which will cause the loss of small-scale target feature information, the efficient intersection over union method is used to improve it; then, because of the high missed detection rate of the non-maximum suppression (NMS) method, Soft-EIoU-NMS is used to replace the original NMS method. The experiment first conducted ablation experiments on the LEVIR dataset, where the target scale changes little and the number of ground object categories is small, and the DIOR dataset, where the target scale changes greatly and the number of ground object categories is large. The mAP@0.5 on the LEVIR dataset reached 0.935; the mAP@0.5 on the DIOR dataset reached 0.882. Then, the model proposed in this article was compared with the mainstream target detection methods. The experimental results verified the effectiveness of the model in this article. Finally, the model was applied to the disaster remote sensing image scene for detection, again demonstrating the model’s good detection performance. Therefore, the experimental results show that the method proposed in this article can effectively alleviate the scale imbalance problem and achieve a good target detection effect.

To make sure that regional reconstruction goes smoothly, it is important to know how rural construction areas in a river basin change over time and space and what factors affect those changes. This study focuses on the rural construction areas in the Nanxi River Basin. Through geographic information systems’ spatial analysis methods, the construction area morphology, center of gravity migration, and agglomeration degree are analyzed to reveal its spatiotemporal evolution from 1990 to 2020. The geographical detector is used to explore the interaction of multidimensional driving factors such as natural geography, socio-economic development, and cultural heritage protection. The research results show that (1) the rural construction area in the Nanxi River Basin shows an evolution trend of “agglomeration expansion and northward shift of the center of gravity.” (2) Cultural, economic, and natural factors all play a part in how rural construction areas change over time. Cultural factors, like the distance between farms and the layout of educational resources, have the most significant impact, followed by economic and natural factors. (3) The study also suggests a “cultural gene-natural base-economic potential” model that can help us understand how to protect cultural heritage and boost the economy at the same time. This result has direct guiding significance for the implementation of China’s rural revitalization strategy. It can give natural resource planning departments a scientific way to figure out the best way to use land and give cultural heritage management agencies a way to come up with safe development plans. It also provides a reference for the sustainable development path of resource-rich villages around the world.

This study analyzes the spatiotemporal patterns of seven common cancers in the male population using 23 years of data (1999–2021) across 18 counties in Central Serbia. The spatial distribution of cancer incidence and mortality rates and their temporal evolution were examined at the county level using Getis–Ord {G}_{i}^{* } techniques, while trends were analysed with Mann-Kendall statistics. Hot spot analysis revealed a decline in mortality rates, whereas incidence rates increased. New colorectal cancer incidence hotspots emerged in three counties, while consecutive bladder cancer hotspots appeared in two counties. Conversely, new cold spots in mortality rates were found for lung and bronchus cancer in four counties, stomach cancer in two, and laryngeal cancer in one. An increasing trend in both incidence and mortality rates was identified for lung and bronchus cancer and colorectal cancer in three counties. In addition, prostate and pancreatic cancer incidence and mortality rates rose in two counties. In contrast, stomach cancer showed a decreasing trend in four counties, as did laryngeal cancer in two. This research enhances public health efforts by identifying vulnerable areas, assessing current health strategies, and guiding new interventions.

This article investigates the application of a model for calculating sustainable development goal indicator 11.7.1 using the example of Podgorica (Montenegro). Indicator 11.7.1 measures the proportion of open public spaces in relation to the total built-up area of the city, which is a key indicator of quality of life, social integration, and the sustainability of urban areas. Utilizing a methodology based on geographic information systems (GIS) analysis and detailed spatial planning documentation, data on various categories of public and green spaces, as well as street areas, were collected and analyzed. The GIS analysis model enables precise mapping and digitization of areas, while spatial planning documents provide necessary data for verification and compilation. The total area of open public spaces, including parks, squares, green areas, and streets, was calculated to be 1,028 ha. In comparison with the total built-up area of the city, which is 858.49 ha, the proportion of open public spaces is 119.75%. The results of this study highlight the importance of monitoring and improving public spaces for the sustainable development of urban environments. The proposed GIS analysis model and spatial planning methodology can serve as a basis for future research and application in other urban areas, enabling more accurate monitoring and improvement of citizens’ quality of life.

This study investigates the source, environmental impact, and health risks of potentially toxic metal(loid)s (PTMs) in agricultural soil from the Al Lith area along the Red Sea coast in Saudi Arabia. Soil samples were collected from 25 farms and analyzed using inductively coupled plasma–atomic emission spectrometry. Various indices were used to assess the contamination of the samples. Most soil samples belonged to Entisols, specifically Torripsamment, Torrifluvent, and Udipsamment subtypes. It was found that the average concentrations of PTMs follow the order of Zn (43.69) > Cu (21.69) > Ni (18.92) > Co (10.12) > Pb (2.62) > As (1.67). The average values of contamination indices indicated minor enrichment, low contamination, and low risk for all PTMs, with minor enrichment observed in some individual samples. The higher levels of PTMs in soil samples were reported from areas surrounding the Wadi Al Lith mouth. Multivariate statistics suggested that the primary source of PTMs in Al Lith soil was geogenic, derived from the weathering of basement rocks of the Arabian Shield. The mean hazard index (HI) values for humans (adults and children) followed the order of As > Ni > Pb > Cu > Co > Zn. The collective HI for PTMs in the Al Lith soil stayed below 1.0, indicating a non-carcinogenic risk. Additionally, lifetime cancer risk values for humans were lower than 1 × 10⁻⁴, indicating an acceptable or tolerable level of carcinogenic risk and suggesting negligible health hazards.

Aswan broadband seismic network with highly sensitive sensors and good station coverage gave the opportunity to study the seismicity distribution, focal depth, the fault plane solution, the attenuation of seismic wave, the station sites response, and the source spectra of Aswan earthquakes with magnitude \left({M}_{{\rm{L}}}) between 0.8 and 4.2 recorded from 2010 to 2023 comprehensively. Preliminary analysis of Aswan seismicity during the studied period indicated strike-slip mechanism with minor normal sense is dominant, relatively deep seismicity concentrated beneath Gabal Marawa, whereas shallow seismicity are dominant features of other zones in Aswan region, and the epicenter distribution characterized by cluster forms, frequently occurred earthquakes in the same patches, and concentrated in the intersection area between the two orthogonal fault systems. A generalized inversion technique (GIT) constrained by reference site is applied to separate the path effect, the recording station sites responses and the source spectra from the observed P- and S-waves by means of iterative least square analysis. The separated station sites effects show similar trend using P- and S-waves, with flat curve in the low frequency band from 0.8 to 8 Hz, whereas the station sites responses have peak amplitudes deviated from 4 to 10 in the higher frequencies. The attenuation through propagation is evaluated and empirically formulated {{Q}}_{{\rm{p}}}\left=(133\left\pm 2.09){{f}}^{(0.54\left\pm 0.034)} and {{Q}}_{{\rm{s}}}\left=(91\left\pm 1.9){{f}}^{(0.8\left\pm 0.045)} for P- and S-waves, respectively. The given attenuation fitting relation for P- and S-waves indicated the frequency dependence of seismic wave’s attenuation in the study area. The low-quality factor {{Q}}_{0} at reference frequency ( {f}_{0} ) pointed that Aswan region is an active region. Furthermore, the low value of {{Q}}_{0} would indicate that the medium is complex and highly heterogeneous. The third element separated from the observed seismogram is the displacement source spectra which modulated using Brune’s omega square. The advanced earthquake’s source parameters (seismic moment, corner frequency, moment magnitude, and static stress drop and source radius) and its scaling relations are computed using the converted windows of P- and S-waves. The displacement source spectra for seismic events with {M}_{{\rm{L}}}\lt 3 decayed rapidly at 20 Hz in the frequency bands of 0.8–50 Hz, whereas it is decreased rapidly at 10 Hz for seismic events with magnitude 3\le {M}_{{\rm{L}}}\lt 4.2 . The seismic moment, the source radius, and the corner frequency range from 9.50 × 10¹⁶ to 2.18 × 10²¹ dyne-cm, from 28 to 190 m, and from 4 to 36 HZ, respectively. The observed stress drops for the studied earthquakes vary from 0.01 to 12 Mpa, whereas the stress drop for S-portion {\triangle \sigma }^{{\rm{S}}} ranged from 0.03 to 22 Mpa. The low stress drop values may reflect that reservoir–triggered earthquakes may have a lower stress drop than tectonic and crustal ones.

The characteristics of pores and fractures, as well as the diagenetic evolution path, are of great significance for identifying the formation of shale reservoirs and the enrichment mechanism of unconventional hydrocarbons. Compared with mature marine shale, medium-maturity marine shale has the characteristics of high clay content (>30%), high carbonate content (>15%), and low quartz content (<40%). The thermal simulation experiment based on medium-maturity marine shale provides a theoretical basis for understanding the relationship between pore fracture genesis characteristics and diagenetic evolution. Low-temperature N2 adsorption, field emission scanning electron microscopy, and micro-X-ray fluorescence experiments were conducted on marine shale samples of different maturity levels obtained after thermal simulation. The results indicate that (1) When R o < 1.2%, the pore type is inorganic pores, and the fracture type is bedding fractures. The size of inorganic pores rapidly decreases under compaction. (2) When R o is between 1.2 and 2.0%, the cementation and dissolution dominate the development of inorganic pores. Micro-fractures are formed at the edge of organic matter (OM), while the bedding fractures are enlarged. A large number of dissolution pores are formed inside mineral particles, and the development of inorganic pores is highest during this stage. (3) When R o exceeds 2.1%, the hydrocarbon generation process dominates the formation and maintenance of a large number of OM pores. The framework composed of microcrystalline quartz is beneficial for the preservation of OM pores. When R o reaches 2.80%, the interparticle pores between organic matter and rigid mineral particles are further increased.

The Qunji porphyry copper (Cu) deposit, located within the Awulale metallogenic belt (AMB) in the western Tianshan orogenic belt, exhibits distinct geochemical and mineralogical characteristics that have not been fully understood. Despite its contribution to our understanding of Cu mineralization mechanisms in reductive metallogenic systems, the oxygen fugacity and ore-forming potential of this deposit are lower than those of typical porphyry Cu deposits. Therefore, there is a need to further investigate the unique features of this deposit. The primary objective of this study was to analyze minerals and trace elements in zircon to quantify the oxidation states of the magma and investigate the presence of reduced porphyry-type magmas and ore-forming fluids in the western AMB. Through this research, we aimed to provide insights into the metallogenic mechanisms and contribute to the understanding of similar deposits in reductive environments. The zircon grains from the Qunji albite porphyry have a Ce⁴⁺/Ce³⁺ ratio of 37.0, indicating that the deposit likely formed in a reduced magmatic–hydrothermal system, which is common in the western Tianshan orogenic belt. Our analytical methods included the use of a cathodoluminescence scanning electron microscope and laser ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) to analyze trace elements in situ. The results revealed a distinct enrichment of heavy rare earth elements and a relative deficit of light rare earth elements, with a positive Eu anomaly. The zircon crystallization environment was determined to be a continental crust environment. Additionally, the Qunji albite porphyry exhibited an A-type granite geochemical affinity and was formed within an extensional environment following tectonic collisions. The oxygen fugacity of the Qunji albite porphyry was notably low, which is a significant characteristic distinguishing it from typical porphyry Cu deposits. Consequently, the Qunji Cu deposit qualifies as a reduced porphyry Cu deposit with relatively low ore-forming potential.

The radial drainage network, which has a typical spatial distribution pattern, is a crucial component for reflecting regional geographical landscapes. Identification of radial drainage networks mainly involves the extraction of drainage segments that constitute the entire drainage network, which is conducive to enhancing the existing data and obtaining map knowledge. Previous studies on the spatial distribution of drainage networks are primarily focused on pattern identification and generalization for single-connection drainage networks. However, radial drainage networks, which normally contain multiple local drainage networks, have typical regional and combinatorial features. Thus, identifying them using available methods is challenging. In this study, a method for identifying radial drainage networks is proposed by using dual constraints on topography and geometry. First, mountain peaks that satisfy the distribution criteria are identified from the window and contour features. Then, various parameters are designed to distinguish the features of drainage segments and basins, and the components of radial drainage networks are determined. Finally, through topological operation and the distance metric, the boundary segments of the radial drainage networks are divided into different groups, and the corresponding radial drainage networks are identified. The test results demonstrate that compared with manual identification, the proposed method has achieved over 90% identification accuracy, recall rate, and F1 value.

In order to accurately identify and evaluate the interference caused to vegetation environment during the construction process of current power transmission and transformation projects in hilly areas, especially in response to the obvious shortcomings of traditional unmanned aerial vehicles and manual detection methods, this study analyzes the composition of vegetation disturbance environment of power transmission and transformation projects in hilly areas from two aspects of natural environmental factors and human environmental factors. Taking the ±800 kV UHVDC transmission project in a certain area as an example, the multi temporal remote sensing data of the project area are collected by Landsat satellite. Combining the deep learning model with the multi model hierarchical classification algorithm, the remote sensing prediction map based on deep learning is used as the classification base map, and the normalized difference vegetation index threshold is used to classify the uncovered area. Combined with the non-building and water area in the classification base map, the candidate disturbance area composed of the two is obtained. The disturbance area is identified in the candidate disturbance area according to the size of the average reflectivity. In the disturbance area, the vegetation restoration community is analyzed according to the difference of normalized difference vegetation index in remote sensing images of different time phases. The experimental results show that the difference between the intelligently identified disturbance area and the engineering design disturbance area can be controlled within 2%, and the vegetation restoration at different time points in the disturbance area can be effectively analyzed.

Catastrophic debris flows have the potential to devastate structures, infrastructure, and inflict severe economic losses and casualties. Situated within the Xianshuihe fault zone, Yusitong Gully has a watershed area of 25.88 km², with a main channel length of 9.18 km and a gully bed gradient of 310‰. The combination of rainstorms and subsequent runoff makes the formation of debris flow all too common, posing a threat to both Yusitong Village and the Kangding-Mugetso highway on the alluvial fan. This study encompasses a comprehensive investigation of field conditions, calculations of essential parameters, and dynamic process simulations to better understand debris flows in Yusitong Gully. By estimating the magnitudes of debris flow within return periods of once-in-a-century, once-in-fifty-years, and once-in-twenty-years, including the peak discharge and total volume of a single debris flow event, we can accurately assess the potential risks. Additionally, a numerical technique is employed to simulate debris flow occurrences at different frequencies within Yusitong Gully, considering scenarios both with and without implemented control measures. The results demonstrate that the highest hazard level is located at the top of the alluvial fan, but significantly decreases after the execution of control measures. This study serves as a reliable scientific foundation for analyzing hazards and formulating effective mitigation plans, not only for Yusitong Gully but also for other mountainous catchments.

Tight sandstone reservoirs, characterized by low porosity and permeability, have long posed significant challenges for oil and gas exploration and development. This study focuses on the reservoirs in the Chang 6–Chang 8 section of the Yanchang Formation, located in the Heshui area of the Ordos Basin. These reservoirs, with their complex pore structures and diverse genesis, represent typical examples of tight sandstone reservoirs. The primary aim of this study is to systematically investigate the pore structures of these reservoirs, elucidating the mechanisms that govern permeability and thereby providing a scientific basis and technical support for the efficient development of tight sandstone oil and gas resources. Utilizing high-pressure mercury injection and nuclear magnetic resonance techniques, the study emphasizes the crucial role of pore fractal properties in controlling reservoir permeability. The results indicate that the complexity of pore structures directly influences both permeability and mobile fluid saturation. Specifically, smaller pores exhibit lower fractal dimensions, while larger pores show higher fractal dimensions, with significant impacts on both permeability and mobile fluid saturation. Additionally, the study examines the effects of different sedimentary facies and diagenetic stages on the pore structures of sandstone reservoirs. The findings reveal distinct evolutionary patterns of pore structures across various depositional environments within the braided river delta system. Furthermore, diagenetic processes and cementation play essential roles in shaping the diversity of pore structures in these reservoirs. In conclusion, this study offers new insights into the relationship between pore structure and permeability in tight sandstone reservoirs, providing valuable theoretical guidance for the exploration and development of oil and gas resources.