Band 15, Heft 1

This study focused on the deep tight sandstone reservoir (DTSR) of the fourth member of the Shahejie Formation in the Bozhong Sag, Bohai Bay Basin, a special type of reservoir. To reveal the diagenesis and evolution of the reservoir in the study area, cores observation, thin section identification, scanning electron microscopy, grain size analysis, and petrophysical properties measurements are available to analyze the mechanics of diagenesis and densification processes. The recognition is agreed on that (1) the lithology of the fourth member is mainly composed of lithic arkose and feldspathic lithic sandstone with low compositional maturity, and grain sizes vary from middle to coarse; (2) the porosity of reservoir ranges from 4 to 11.5% (av. 6.8%), which belongs to the medium low porosity sandstone reservoir; the pore structure is complex and the type of pore spaces is mainly secondary pore, while original pores are less developed due to the deep distribution of strata; (3) based on the quantitative calculation of porosity of the DTSR, it was identified that compaction is the main reason for sandstone reservoir densification, with an average porosity reduction of 62%, followed by cementation filling intergranular pores with an average pore reduction rate of 25.1%. Dissolution plays a constructive role in improving porosity, with an average increase rate of 18.5%.

In this study, the reconstruction of the formation condition in the Oligocene flysch (Berati and Zhitomi section), in the Berati anticline structure, north-eastern part of the Ionian tectonic zone (Albania), is elucidated using petrographic–mineralogical characteristics and grain size analysis. Outcrops from the Berati and Zhitomi and the drilled wells were selected for sampling based on previous stratigraphic and paleontological studies. The mineralogical study of the flysch deposits made it possible to evidence for the first time three mineralogical zones: (a) quartz–garnet (b) serpentine, epidote with mica, and (c) feldspar zone, and three these petrographic zones: (a) quartz, (b) quartz–serpentine, and (c) quartz with mica and feldspars. The reconstruction of the depositional environment is based on the petrographic study of rock types, their textural characteristics, and grain size statistics. The granulometry coefficients like mean, sorting, skewness, and kurtosis are calculated arithmetically and the C / M diagram as well. Referring to the mineralogical composition of the sandstones and siltstones, the obtained data were used for the correlation of the sections and the delineation of the leaching area and the direction of the sediment movement. The mineralogic and petrographic characteristics show that during the Oligocene, the region has been under continuous paleogeographic change and under intensive orogenic activity, which has influenced the character of the mineralogical–petrographic composition of these deposits. Based on the pebbles petrography present in the slump horizons and on heavy mineral assemblages, it was evidenced that the eastern tectonic zones of Kruja, Krasta, and Mirdita (Albania) were the main suppliers of sedimentary material. The Passega C / M diagram suggests suspension and saltation as the main mode of sediment transport prior to deposition.

During the Late Campanian, sea-level fluctuation occurred in the form of two chert bands and the topmost conglomeratic phosphate beds (CF8a zone). A great transgression event occurred associated with the global warming (CF8b zone) trend indicated by large double-keeled foraminifera as Globotruncana aegyptiaca Nakkady of oligotrophic conditions. Through the event of CF6/CF5 zones, a gradual increase in the relative abundance of Gublerina rajagopalani Govindan and Planoheterohelix planata (Cushman) and other heterohelicids have been shown to tolerate and thrive in a wide range of environmental conditions as in high-stress environments. Sea-level fall at the CF6 zone and the overlying CF5 boundary marked a warming climate for the Middle Maastrichtian Event. In the latest CF4 records, the beginning of the decrease in planktic/benthic ratio, globotruncanids, rugoglobigerinids, and heterohelicids indicating a fall in sea level coincided with the CF4/CF3 and the development of dark grey shales in a regressive regime. The observed low abundance of planktic specimens may be due to the presence of pyrite with black shale interval suggesting low oxygen condition. The latest zones CF3, CF2, and CF1 are generally characterized by heterohelicids blooms specially Planoheterohelix globulosa (Ehrenberg), and a gradual decrease in diversity associated with the warming phase before the K/Pg boundary event, implying high biotic stress to even absent of Guembelitria cretacea species through CF3–CF1 zones. Pseudotextularia elegans (Rzehak) occurs in the zones CF4 and CF2 warming of phases 1 and 2 of Deccan Trap Volcanic. The absence of P. elegans (Rzehak) in the zone (CF3) is postulated due to a tectonic cause (maximum cooling of Deccan Trap Volcanic) whereas its absence in the zone (CF1) was due to regression of phase 2.

With the great discovery of unconventional oil in the Fengcheng Formation in the Mahu sag, the Wuxia fault belt, which shows similar lithological characteristics and lithofacies, is considered the most favorable area for future petroleum exploration. However, the complicated structural patterns remain unclear and restrict the petroleum exploration and development. In this study, combined with new seismic data and some borehole data, we conclude the structural styles in the Wuxia fault belt and analyze their distribution characteristics, and further investigate their implications for tectonic evolution and hydrocarbon accumulation. Five typical seismic sections are captured from the west to the east of the fault belt. Decollement folds and fold accommodation faults superimpose on the underlying basement fault related folds. Structure patterns also show a zonation in S–N direction and a segmentation in E–W direction. The balanced section reveals that the present-day structure features were fundamentally formed by Late Permian. The structural deformation shows distinctive features of a foreland basin which may develop in Early Permian and continue until the Late Permian. The oil reservoirs in the Fengcheng Formation in deeper detachment fold and the autochthonous Fengcheng Formation in fault propagation folds are the most favorable regions for further unconventional petroleum exploration.

This study proposes an approach to identifying carbonate rocks depositional texture utilizing more than 1250 thin-section photos as a data set from shallow-water carbonates of the Kruja zone (Albania). The proposed technique uses a numerical methodology based on digitized images of thin sections. According to the Dunham classification, it permits the user to recognize the carbonate texture automatically. The carbonate rock should not be affected by post-depositional processes. This technique uses as input gray-scale digital images taken from thin sections. Image processing can extract (as output) a set of 22 numerical parameters measured in the entire image, including white areas representing calcite cement. A multi-layer perceptron (MLP) neural network inputs these numerical parameters and produces, as output, the estimated depositional texture. We utilized 654 images of thin sections to evaluate this technique to train the neural network. We used 348 pictures taken from the same data set and 250 from the Burizana section (Kruja zone, Albania) to test the technique. The proposed method has shown 90.5 and 91.3% accuracy in identifying the automatically depositional texture using digitized images on the 348 and 250 test sets. Based on the good results obtained, this technique can be extending not only in identifying carbonate rocks texture but in every type of rock, getting fast and correct results. Python was used as a computer programming language for image processing and displaying images.

The Hongqiling magmatic Cu–Ni sulfide deposit is one of the most important deposits in the easternmost segment of the Central Asian Metallogenic Belt, northeast China. However, the existence or non-existence of magmatic chambers is still not been determined, which is the key to decipher the formation of Hongqiling Cu–Ni deposit. Therefore, this study proposes to adopt long-period magnetotellurics method to image the deep-seated metallogenic system in Hongqiling Cu–Ni deposit. Two-dimensional (2D) nonlinear conjugate gradient inversion technology allows us to describe entire magma plumbing system, including the mantle-derived magma channels (banded low-resistivity anomalies), deep separated chamber (low-resistivity anomaly C2), and shallow magma conduits (low-resistivity anomaly C1). These results indicated that the mantle-derived primitive magma gave rise to the parental magma for the mafic–ultramafic intrusions in Hongqiling Cu–Ni deposit and triggered the segregation of Cu–Ni sulfides in the shallow chamber. By combining the experimental simulation, geochemistry, geochronology, and geotectonics data in the study area, we suggest that the partial melting processes which produced the large magma plumbing system probably have been triggered by lithospheric delamination.

The orthometric height has an essential role in a variety of civil engineering projects and it is defined as the length of the curved plumbline from a point (on the earth surface) to its intersection with the geoid surface. Leveling process is considered as the most accurate technique for obtaining these heights. However, regardless of its potentials, it is tedious, costly, and time consuming. Recently many organizations and research centers have developed multi Global Geopotential Models (GGMs) depending on several types of available gravity and height datasets to estimate orthometric heights from GNSS measurements. In this study, we present an evaluation and assessment of the accuracy of five of recent and popular GGM S : XGM2016, XGM2019e, EIGEN-6C4, GO_CONS_GCF_2_TIM_R6e, and EGM2008 using actual 145 GNSS/leveling points and 96 terrestrial gravity points. The goal of this research is to find the best fit model along the study area located along the coastal zones of Egypt with distances of about 1,970 km for further determination of geoid modeling at regional scale. The selection of these areas basically was due to their developmental, urban, and economical importance and their continuous need for protection works to fight against the coastal erosion caused by climate change and global warming. The results indicated that for geoid undulation, GO_CONS_GCF_2_TIM_R6e model is the best fit GGM for the estimation of geoid model along Mediterranean Sea coastal line, while XGM2019e_2159 model is the best suitable for coastal line of the Red Sea. And regarding the gravity anomalies, the most reliable GGMs for this study area are XGM2019e_2159 and EIGEN-6C4 for Bouguer and free-air gravity anomaly, respectively.

Satellite digital elevation models (DEMs) are used for decision-making in various fields. Therefore, evaluating and improving vertical accuracy of DEM can increase the quality of end products. This article aimed to increase the vertical accuracy of most popular satellite DEMs (i.e., the ASTER, Shuttle Radar Topography Mission [SRTM], Forest And Buildings removed Copernicus DEM [FABDEM], and Multi-Error-Removed Improved-Terrain [MERIT]) using the particle swarm optimization (PSO) algorithm. For this purpose, at first, the vertical error of DEMs was estimated via ground truth data. Next, a second-order polynomial was applied to model the vertical error in the study area. To select the polynomial with the highest accuracy, employed for vertical error modeling, the coefficients of the polynomial have been optimized using the PSO algorithm. Finally, the efficiency of the proposed algorithm has been evaluated by other ground truth data and in situ observations. The results show that the mean absolute error (MAE) of SRTM DEM is 4.83 m while this factor for ASTER DEM is 5.35 m, for FABDEM is 4.28, and for MERIT is 3.87. The obtained results indicated that the proposed model could improve the MAE of vertical accuracy of SRTM, ASTER, FABDEM, and MERIT DEMs to 0.83, 0.51, 0.37, and 0.29 m, respectively.

The geological model plays an important role in geophysics and engineering geology. The data source of geological modeling comes from interpretation data, borehole data, and outcrop data. Due to economic and technical limitations, it is impossible to obtain highly accurate and high-density data sources. The sparsity and inaccuracy of data sources lead to the uncertainty in geological models. Unlike the problem of probability, there is not enough samples for a geological model. Spatial diffusion model and merging model are introduced, which are more satisfied with the cognition of uncertainty than the existing methods. And then, using conditional information entropy, a quantification method of geological uncertainty, is proposed. Compared with the approaches of information entropy, this method took full account of the constraints of geological laws. Based on the uncertainty models and conditional information entropy, a framework of uncertainty assessment in geological models is established. It is not necessary in our framework to create multiple geological models, which is a time-consuming and laborious task. The application of Hashan survey located at north of China shows that the method and framework of this study are reasonable and effective.

Soil stiffness degradation due to dynamic loading may result in damage to engineering structures. Therefore, dynamic soil properties gained importance in recent years in the areas where vibrations of different origins are transmitted to the ground. The aim of the study was to determine the stiffness properties of the Warsaw varved clay (central Poland), as a measure of its response to dynamic loading. A set of triaxial tests were conducted. Undisturbed samples were subjected to initial deviator stress of 100 kPa, reflecting vertical stress due to construction load, and then to three dynamic stages under axial displacement control conditions. Secant shear modulus G was adopted as a parameter of soil stiffness during dynamic loading. Main methodological result of the study is application of coefficient α (gradient of logarithmic change in stiffness with time) indicating type of soil behavior under dynamic loading. Negative α values (ranging from −0.48 to −0.91) indicated a weakening effect of the applied vibrations (decrease in stiffness), while positive α values (ranging from 0.11 to 0.21) indicated soil strengthening (increase in stiffness). Results of the study may be applied to compare an impact of several factors influencing soil stiffness during dynamic loading

To better understand the assimilation contribution and influence mechanism of different satellite platforms and different microwave instruments, the radiance data of Advanced Microwave Sounding Unit-A (AMSU-A) and the Microwave Humidity Sounder (MHS) onboard NOAA-15 and NOAA-18 are assimilated to investigate various assimilation effects on the prediction of path and intensity of Typhoon Megi (2016) based on Weather Research and Forecasting (WRF) three-dimensional variation and the WRF model. The community radiative transfer model is employed as the forward operator. The quality control and bias correction procedures before the radiance data assimilation (DA) are performed to improve the simulations. Impact of AMSU-A and MHS radiances assimilation on Typhoon Megi (2016)’s path and intensity is investigated by six experiments (without and with AMSU-A and MHS DA) with initial conditions at 1200 UTC on 25 September 2016 and 60 h forecast integration. The results are compared to the observational data from the China Meteorological Administration tropical cyclone database. The impact mechanisms of DA adjustments to the initial fields and assimilation increment analysis of each physical quantity field are investigated in detail. The findings show that NOAA-15 AMSU-A assimilation produces the best output over the course of the 60 h simulation, demonstrating that assimilation satellite data from multiple platforms is not always better than assimilation satellite data from a single platform. In comparison, MHS assimilation has a favorable effect on short-term path and strength forecasts, but has a negative impact on long-term forecasts. The effect of MHS DA needs to be further investigated.

The accumulation of dust on the surface of solar panels reduces the amount of sunlight reaching the solar cells and results in a decrease in panel performance. To avoid this loss of production and thus, to improve the performance capacity, solar panels must be cleaned frequently. The West African region is well known for its high solar energy potential. However, this potential can be reduced by the high occurrence of dust storms during the year. This article aims to provide a contribution to the construction of a meteorological information service for solar panel cleaning operations at Diass solar plant in Senegal (Western Sahel). It is based on a full year in situ experiment comparing the power loss due to dust between solar panels cleaned at different frequencies and those not cleaned. The model to determine the cleaning frequencies is based on the deposition rate of airborne particles, the concentration of airborne particles, and the density of the dust that has a major impact on the power loss. Cleaning frequencies are presented at seasonal scale because in the study area, dust episodes differ according to the seasons. A cost–benefit analysis is also performed to demonstrate the advantage of using weather information service to support the dust cleaning operations at Diass plant. As results, it is found that cleaning every 3 weeks is required during the dry seasons, December–January–February and March–April–May. During the rainy season, cleaning every 5 weeks is recommended in June–July–August, while in September–October–November cleaning every 4 weeks is sufficient to maintain an optimal performance of the solar panel. The total costs of cleaning operations based on these results are reduced compared to the current costs of cleaning and the benefits are much higher than without cleaning action.

Research on healthcare accessibility is developing with a focus on multimodal transport modes (MTMs) and multiple time-series variations. A dynamic traffic environment leads travelers to make distinct decisions at different time slots, which impacts spatiotemporal accessibility markedly. Our article proposes a methodological framework to measure spatiotemporal accessibility with multimodal transportation modes and its variation at multiple time series, while accounting for traffic congestion and the probability of residential transport mode choices in a dynamic traffic environment. We selected Nanjing, China, as the study area and pediatric clinic services (PCS) as specific healthcare services to estimate the spatiotemporal accessibility at four representative time slots. The results indicate that the weight estimation of travel time based on MTMs is more propitious than the travel time of single-mode to present real-world travel characteristics and reflects the spatiotemporal distribution and variation of services synthetically. Furthermore, the spatiotemporal accessibility variation of PCS in peripheral suburbs is more pronounced than that in urban centers and rural areas. This work holds pragmatic implications for policymakers in terms of services planning and allocation optimization to improve the equity of resource supply.

In this work, we propose a mathematical model to depict the conversion of groundwater flow from confined to unconfined aquifers. The conversion problem occurs due to the heavy pumping of confined aquifers over time, which later leads to the depletion of an aquifer system. The phenomenon is an interesting one, hence several models have been developed and used to capture the process. However, one can point out that the model has limitations of its own, as it cannot capture the effect of fractures that exist in the aquitard. Therefore, we suggest a mathematical model where the classical differential operator that is based on the rate of change is substituted by a non-conventional one including the differential operator that can represent processes following the power law to capture the memory effect. Moreover, we revise the properties of the aquitard to evaluate and capture the behaviors of flow during the process in a different aquitard setting. Numerical analysis was performed on the new mathematical models and numerical solutions were obtained, as well as simulations for various fractional order values.

As a typical lake in the early stage of eutrophication, the non-point source pollution (NSP) in Erhai Lake was highly concerned. Since 2017, protection and rescue actions have been implemented in the Erhai Lake basin which significantly improved the water quality of Erhai Lake. But little attention has been paid to the interception effects of these actions on NSP. Based on high resolution datasets, including refinement land use/land cover (LU/LC) data, China Meteorological Assimilation Driving Database for the SWAT (CMADS), and Advanced Land Observing Satellite-1 (ALOS-12) data, the interception effects of ecological ponds newly built in 2018 on NSP was discussed with the support of the soil and water assessment (SWAT) model. These three high resolution datasets can meet the needs for simulating NSP by SWAT model, which was conductive to better reveal the interception effects of ecological ponds on NSP. Besides, the pollution load of shrubbery on Total nitrogen (TN)/Total phosphorous (TP), which has never been involved in similar research works in the Erhai Lake basin, was measured. Compared the temporal and spatial variations in TN/TP concentration before and after 2018, the interception effects of ecological ponds on NSP in the Erhai Lake basin were revealed by a sharp decrease in TN/TP concentration and a delayed presence of annual peak value about 1 month late in TN concentration before and after 2018. The interception intensity of NSP was determined by the number and volume of ecological ponds in each sub-basin and their corresponding upstream.

Equilibrium-line altitudes (ELAs) are an important proxy of the fluctuations and mass–balance characteristics of glaciers and have been widely used to reconstruct regional paleoclimatic conditions. The Diancang Massif, which has experienced the well-known "Tali Glacial Stage" was uplifted during MIS 3b (marine isotope stages). With its unique characteristics, the Diancang Massif has become an irreplaceable area for the study of inland paleoclimatic and paleo-environmental changes in China. Nevertheless, despite the considerable amount of glaciological studies on this area, a detailed and systematic estimation of paleoglacial ELAs during the Last Glacial Maximum remains to be performed. In this study, several approaches are employed to estimate the ELAs on the basis of previous studies. The results are compared and analyzed, and the final results are determined using a weighted arithmetic average method. Finally, the weighted root mean square error is applied to evaluate the accuracy of the results. Moreover, two critical parameters, differences between positive and negative effects and the distance ratio between the accumulation area and ablation area, are discussed in detail. In the comprehensive results, the final estimated paleoglacial ELAs of the north slope of “Yuju Peak” and the south slope of “Longquan Peak” are 3,773 and 3,883 m, and their median errors are 18.73 and 45.00 m, respectively. Overall, paleoglacial ELAs in the Diancang Massif could be systematically and scientifically estimated for the first time, which is expected to provide fundamental data for accurate modeling of paleoclimatic changes in this area.

The archaeological site prediction model can accurately identify archaeological site areas to enable better knowledge and understanding of human civilization processes and social development patterns. A total of 129 Neolithic site data in the region were collected using the Xiangyang area as the study area. An eight-factor index system of elevation, slope, slope direction, micromorphology, distance to water, slope position, planar curvature, and profile curvature was constructed. A geospatial database with a resolution of 30 m × 30 m was established. The whole sample set was built and trained in the ratio of 1:1 archaeological to nonarchaeological sites to obtain the prediction results. The average Gini coefficient was used to evaluate the influence of various archaeological site factors. The results revealed that the area under the curve values of the receiver operating characteristic curves were 1.000, 0.994, and 0.867 for the training, complete, and test datasets, respectively. Moreover, 60% of the historical, archaeological sites were located in the high-probability zone, accounting for 12% of the study area. The prediction model proposed in this study matched the spatial distribution characteristics of archaeological site locations. With the model assessed using the best samples, the results were categorized into three classes: low, average, and high. The proportion of low-, average-, and high-probability zones decreased in order. The high-probability zones were mainly located near the second and third tributaries and distributed at the low eastern hills and central hillocks. The random forest (RF) model was used to rank the importance of archaeological site variables. Elevation, slope, and micro-geomorphology were classified as the three most important variables. The RF model for archaeological site prediction has better stability and predictive ability in the case field; the model provides a new research method for archaeological site prediction and provides a reference for revealing the relationship between archaeological activities and the natural environment.

Coastal nuclear power plants discharge large amounts of warm cooling water, which may have environmental impacts. This study proposes a method for determining the long-term impact area based on the average distribution of sea surface temperate (SST) increases. Taking the Daya Bay Nuclear Power Plant as a case study, 101 TM/ETM+ images acquired from 2000 to 2013 were used to obtain SST products. Cross-validation with NR_2P products showed that the accuracy of the SST products, in terms of the systematic error, root-mean-square error, and mean absolute error of 1,000 randomly selected verification points, was all <0.3°C, while Willmott’s index of agreement values was all >0.7. An annual SST cycle harmonic model was established. The mean difference between the modeled and observed SSTs was −2.1 to 2.5°C with a standard deviation range of 0–1°C. The long-term impact area was extracted by the harmonic analysis method and multi-year average method for comparison. The following conclusions can be drawn: 1) with sufficient SST samples, the temperature distributions of the two methods are similar, with the multi-year average method giving less noise and clearer boundaries. 2) When SST data are lacking for some months, the mean and standard deviation of the percentage of pixels belonging to areas of different temperature rise were calculated. The standard deviations of the two methods were both <0.04 in the temperature-rise classes of 1–2, 2–3, 3–4, and 4–5°C, while in the 0–1°C class, the standard deviation of the multi-year average method was 0.461, which is much higher than that of the multi-year average method (0.098). Performing statistical analysis on all pixels of >0°C, the multi-year average method had a standard deviation of 0.506, while the harmonic analysis method had a value of 0.128. Overall, the harmonic analysis method makes it possible to obtain and evaluate the long-term stability impact area of the thermal discharge over a period of time comprehensively and quantitatively. Even though it introduces a small amount of noise, it has less dependence on the input SST products and could improve the stability and reliability of thermal discharge monitoring, providing technical support for precise pollution control.

Understanding the internal structure of specific landforms is a crucial prerequisite for determining their origin and evolution. Near-surface geophysics represents a non-invasive way of subsurface investigation, and it can be used to describe subsurface conditions, especially in protected areas. We tested possible hypotheses of block accumulations origin and evolution by four different geophysical methods (electrical resistivity tomography [ERT], shallow seismic refraction [SSR], ground penetrating radar [GPR], and electromagnetic induction [EMI]) in the Central European Uplands. At the same time, we evaluated the applicability of geophysical methods to determine the internal structure and thickness of block accumulations. Based on the application of two suitable methods (ERT and SSR), we (1) estimated the thicknesses of block accumulations, (2) partially described their internal structure, and (3) presented the most probable hypotheses of block accumulation origin and evolution in two investigated sites. Graphical abstract

Abandoned quarries are valuable as a tourism element, as they exhibit the building material of the buildings built in the geographical area they are located in as historical objects. However, in order to determine how the quarries can be used for tourism purposes, it is necessary to determine the constraints on the choice of solution in spatial arrangements. The aim of this study is to investigate how the ancient limestone quarry of Mardin, which is a natural and cultural geological heritage, can be used for tourism and to develop suggestions. Within the scope of the study, in order to examine the possibilities of how an idle quarry located in Mardin province in Turkey can be used for tourism, the constraints in the selection of the post-use solution will be determined. In order to determine whether the Mardin quarry is accessible and safe to visit, various field studies were carried out in the study area, laboratory experiments and analyses. The caves were scanned with a 3D laser scanner, and its plans and sections were obtained. The findings were evaluated and suggestions were developed for the use of the ancient limestone quarry for tourism.

Objective Human activities and climate change have changed the living environment of species, accelerated the rate of species extinction, and global biodiversity is facing a huge threat. The objective of this study is to determine the resource protection strategy of freshwater planarian by systematically exploring the population genetics and pedigree geography of the planarian population in the four mountain systems of Henan Province and Taihang Mountains. Methods Taking the Japanese planarian in the four mountain systems of Henan Province and Taihang Mountains as an example, DNA was extracted with the help of mitochondrial cytochrome c oxidase subunit I gene ( COI), mitochondrial cytochrome b gene ( Cytb), and nuclear gene internal transcribed spacer-1 ( ITS-1 ), amplified by polymerase chain reaction and sequenced, and genetic diversity, genetic structure, and pedigree geographical pattern were analyzed by single-gene analysis and polygene joint analysis. Results The corresponding length of Cytb , COI , and nuclear gene ITS-1 sequences in the four mountains of Henan Province is 308, 805, and 632 bp, respectively, and the nucleotide diversity and haplotype diversity are 0.00212 and 0.975, respectively. The gene length of ITS-1 and Cytb in Taihang Mountains is 668 and 315 bp, respectively, with a total length of 984 bp. There are 10 shared haplotypes and 36 unique haplotypes. The values of all nucleic acid diversity and haplotype diversity were 0.00156 and 0.965, respectively, and the genetic variation coefficients between populations and groups were 20.28% and 16.40%, respectively ( P < 0.05). Different haplotypes of the four mountain systems in Henan Province and Taihang Mountains are scattered in different geographic populations, and there is no correlation between them and their geographic locations, which is consistent with the results of phylogeny. Conclusion The genetic diversity of Trionychia japonica population in the four mountain systems of Henan Province and Taihang Mountains shows high haploid diversity and low nucleotide diversity, and phylogenetic analysis has not found obvious pedigree geographical pattern.

Accurately grasping the comprehensive cost-benefit and influencing factors of various marine development projects is of great significance to the promotion of high-quality marine development. This work screened and constructed the performance audit evaluation index system of comprehensive cost-benefit of marine development projects from the four aspects including society, economy, resources, and environment. The entropy weight set pair analysis (SPA) was used to audit and evaluate the comprehensive cost-benefit of 15 marine development projects during the construction and operation period. The back propagation (BP) neural network model was used to test the results. The main influencing factors were analyzed by the grey relational analysis (GRA) model. It was found that the comprehensive cost-benefit performance audit evaluation index of the six projects of marine protected area and offshore wind power were higher than the other nine projects of mariculture, sewage dumping, and port industry. The main influencing factors were economic net income, loss of wetland ecological service value, environmental pollution prevention and control cost, new addition employment rate, etc. The countermeasures suggestions were put forward.

Early Cretaceous desert sedimentary system was developed in Northwest Ordos Basin. At present, the research degree of desert sedimentary paleogeography is low. The research on paleogeographic environment of Early Cretaceous sedimentary sandstone has guiding significance for the exploration of uranium resource and underground water resource in Northwest Ordos Basin. Based on the previous basic geological data of the lower Cretaceous in the Northwest of Ordos, through field geological survey, drilling core observation, and paleocurrent measurement, the sedimentary paleogeographic environments in different periods of Early Cretaceous had been studied. The results show that the lower Cretaceous in Northwestern Ordos Basin can be divided into two sedimentary cycles, the lower sedimentary cycle composed of Luohe Formation and Huachi-Huanhe Formation, and the upper sedimentary cycle composed of Luohandong Formation and Jingchuan Formation. Alluvial, Aeolian, and desert lake depositional systems were developed. The main sedimentary facies were alluvial fan, braided river, sand dune, dry valley, and dry lake. Alluvial fan and braided river facies had mainly developed in Luohe Formation. Braided fluvial facies mainly had developed in Huachi-Huanhe Formation, and alluvial fans locally developed around it. The deposits in Luohandong Formation were mainly aeolian sandstone, and the alluvial fan facies were inherently developed at Western and Northern margins. The depositional environment of Jingchuan formation is mainly river and lake. The tectonic evolution of lower Cretaceous had controlled the development of paleogeographic environment, and sedimentary facies had controlled the development of aquifer system. The paleogeographic environment of Early Cretaceous is conducive to the reduction and enrichment of uranium and the development of metallogenic units.

Three-dimensional (3D) city modeling is an essential component of 3D geoscience modeling, and window detection of building facades plays a crucial role in 3D city modeling. Windows can serve as structural priors for rapid building reconstruction. In this article, we propose a framework for detecting window lines. The framework consists of two parts: an improved stacked hourglass network and a point–line extraction module. This framework can output vectorized window wireframes from building facade images. Besides, our method is end-to-end trainable, and the vectorized window wireframe consists of point–line structures. The point–line structure contains both semantic and geometric information. Additionally, we propose a new dataset of real-world building facades for window-line detection. Our experimental results demonstrate that our proposed method has superior efficiency, accuracy, and applicability in window-line detection compared to existing line detection algorithms. Moreover, our proposed method presents a new idea for deep learning methods in window detection and other application scenarios in current 3D geoscience modeling.

Cross sections carry information on the spatial distribution of rock strata and the development of geological structures, and it is an important data source for three-dimensional (3D) geological modeling. However, the interpretation and mapping of geological structures in sections by means of manual interpretation are inefficient and costly, and the performance varies greatly with the experts’ ability and experience. The objective of this article is to develop an automatic recognition and mapping method for folds in cross sections. This method mainly includes identifying folds based on stratigraphic sequence characteristics (symmetrical and repetitive), classifying fold types based on geometric attributes of folds (interval scheduling, strike, and section morphology), optimizing strata based on the superposition principle and area conservation principle, and constructing the polygon features of folds. Based on experiments in the Parallel Fold Belt of Eastern Sichuan and the central Appalachian fold-thrust belt in the Appalachian Mountains, the method presented in this article can effectively be used for automatic recognition and high-quality mapping of folds in the cross sections. The method provides a good source of geological cross-sectional data for the 3D modeling of geologic bodies.

Mixed sedimentation is mainly a phenomenon by which siliciclastic and carbonate are mixed under a similar sedimentary environment. The study of the composition of mixed rock can reflect the sedimentary environment. The mixed sediments of the Canglangpu formation in the eastern Sichuan basin are widely developed and exhibit well exploration prospects. In this study, a classification diagram of mixed sediments suitable for the Canglangpu formation was proposed by combining lithologic characteristics with logging data. Based on the observations of typical outcrop profiles, the identification of thin sections, and drilling and geological logging data, a model was established to identify the electrical responses of the mixed sedimentary rocks in the study area. The results show that (1) the Canglangpu formation can be vertically divided into two complete transgression-regression cycles with the lower part mainly consisting of sedimentary carbonate diamictite and the upper part principally composed of clastic diamictite; (2) mixed sediments in the Canglangpu formation can be divided into six classes, namely carbonate sandstone, argillaceous sandstone, sandy carbonate rock, argillaceous carbonate rock, sandy mudstone, and Carbonate mudstone; (3) the sedimentary environment of the Canglangpu formation be divided into (a) mixed sediments in the shore, which include mixed lagoon and mixed tidal flat, (b) mixed sediments in the shallow marine shelf, which includes mixed beach bar, terrigenous detrital mixed shelf, and carbonate mixed shelf; (4) a mixed shore-mixed shelf sedimentary model has been established; it says that the mixed sediments show obvious characteristics of ring-like development around underwater paleo-heights. The formation mechanism of mixed sedimentation in the eastern Sichuan basin is mainly controlled by the change of sedimentary facies belt, and the development intensity is mainly influenced by early tectonic movement and sea-level change.

Solution pipes are an important geomorphological feature in carbonate rocks formed by the host rock’s dissolution due to water’s focused flow, indicating the phenomena of water focusing in particular areas. However, their visual exposures are often limited by sediment and vegetation cover, making it challenging to understand their spatial distribution and morphology. In this study, we used geophysical methods such as ground penetrating radar (GPR) and magnetic gradiometer to detect and estimate the spatial distribution of solution pipes in a freshly exposed quarry site in Smerdyna, Poland. Our results indicate that both GPR and magnetometric measurements effectively detect most of the solution pipes, particularly those filled with large amounts of clay and silt particles. The GPR method, in particular, proved to be convenient due to the high contrast of the dielectric constant. The information on the positions and shapes of the pipes obtained based on these methods is crucial in understanding the link between pipe morphology and the physical conditions at the time of their formation. Furthermore, our measurements provided quasi-spatial correlations between pipe positions, the distribution of inter-pipe distances, and the potential relationship between alignments of rock joints and pipe locations. Our study demonstrates the potential of geophysical methods in detecting and understanding solution pipes, which are essential from environmental and climatic perspectives. This information can be used for future studies on pipe formation and environmental impact.

Carbonate reservoir has complex pore structures. At present, the influence of pore structure on water flooding mechanism of carbonate reservoirs is insufficient. In this article, a systematic workflow was designed in combination with scanning electron microscope, particle size, physical properties, and water flooding experiments to study the effect of pore structure on water flooding mechanism of fine-grained carbonate rocks. Due to the small particle size and strong heterogeneity, the acid fracturing operations, rather than hydraulic fracturing alone, are necessary to achieve increased production and reservoir reconstruction of carbonate reservoirs. Through this study, the mathematical model of reservoir physical parameters (permeability and porosity) was proposed, and the accuracy of the model was verified by comparing the simulated oil recovery with the experimental results. According to the comparison results, the experimental results are consistent with the simulation results, and their oil recovery efficiency is 33.62 and 31.87%, respectively. Finally, the effect of injection rate on oil production was discussed. It is shown that with the increase in injection rate, the output of displaced oil increases significantly. The cumulative oil production increases from 62.5 to 256.31 mL when the injection rate increases from 100 to 400 mL/min. The findings of this study can help for better understanding of the influencing factors and mechanisms of the development efficiency of carbonate reservoirs.

In order to reduce the adverse impact of debris flow disasters on engineering construction facilities and social security in the lower reaches of the Yajiang River, this article selected 11 risk assessment factors such as elevation, aspect, profile curvature, Relief, and rainfall to study the occurrence rule of debris flow in this area. The data of disaster factors caused by debris flow points were derived and analyzed in ArcGIS. Then, factor correlation test and factor sensitivity level were established. The coupling model of qualitative mathematical model (analytic Hierarchy Process, AHP), quantitative mathematical model (binary logistic regression [LR]), machine learning model (random forest RF), and certainty factor (CF) were, respectively, used to predict the risk of debris flow disaster in the study area. After comparison, it was found that the CF–LR model had the highest accuracy. The results show that the areas with high debris flow risk are mainly concentrated in the first half of the lower reaches of the Yajiang River and distributed along both sides of the river bank. The annual rainfall range of 600–700 mm is the critical water source saturation value of debris flow in the study area.

Seismic activity has complexity and randomness, and its temporal and spatial distribution has complexity, stage, level, and inheritance. The study of the temporal and spatial distribution characteristics of seismic activity is of great significance to the understanding of the law of seismic activity, such as the law that the time series of seismicity in the seismic belt is consistent with the complexity of geographical structure, the prediction of seismic risk, and other research related to earthquake. This article selects the seismic data catalog of the whole Eurasian seismic belt as the research object. Based on the characteristics of the seismic geological environment and tectonic environment characteristics, the multifractal analysis method is used for the seismic data of the seismic activity directory. The results show that the seismic activity of seismic zones has obvious multifractal structure of complex in time series and spatial scales, which can well reveal the seismic characteristics of seismic activity in time and space. In terms of time series, the study area D ∞ {D}_{{\rm{\infty }}} decreases significantly with time and energy before the occurrence of a large earthquake, and the time series of seismic activity in the study area is highly complex and highly correlated with the geological structure. Spatially, the spatial distribution of seismic intensity in the study area is infinite and sparse, showing the characteristics of infinite clustering. Therefore, it can reveal the basic rule of seismic activity effectively and lay a certain theoretical foundation for earthquake prevention and control in this seismic zone. Graphical abstract

The 2022 ( M 6.8) Luding earthquake on the Xianshuihe Fault Zone (XFZ) caused severe casualties and property losses, and surface deformation and damage of which is crucial for studying the earthquake hazard assessment. However, few intensive scientific understanding has obtained to date because of widespread coronavirus transmission, strong vegetation coverage, and post-earthquake paralyzed traffic. By integrating high-resolution satellite images, large-scale geomorphic mapping, and UAV surveys, we constrain coseismic fractures and ruptures along an NW-SE-trending surface deformation zone, with discontinuous geomorphic scarps, en echelon cracks, and bulges concentrated in the areas of Yanzigou, Moxi, Menghugang, and Xingfu villages near the epicenter. Field observation also shows that the zone extends nearly parallel to the pre-existing XFZ with a length of ∼35 km with variable widths and a maximum vertical displacement of ∼100 ± 10 cm. The earthquake-induced surface coseismic effects, such as landslides, rock falls, and collapses, caused damage to the area. The amplification effect of the topography and the improper aseismic design and poor constructions may be responsible for the spatial distribution of MM Intensity IX, which is larger than other previous earthquakes that occurred in the surrounding area with a similar tectonic setting.

Land cover in tropical marine climate zones is important for global climate change. The existing analysis of land cover product consistency mainly focuses on a continental or national scale and rarely takes different geographical zones (such as tropical marine climate zones) as examples to carry out micro-interpretation from the perspective of ecology from the grid scale. In fact, some types of land cover under different zones have poor accuracy due to the standard of cognition and the complexity of the spatial pattern of ground objects. In addition, land cover and its change in tropical Marine climate zones will affect the greenhouse effect, energy balance, water transport, and so on, thus affecting climate change on a regional or even global scale. Therefore, this article presents an evaluation based on GLOBCOVER, CCI LC, and MCD12Q1 data using Malaysia as a case study, through area composition similarity, field sample point validation, and landscape indices. The results showed that (1) the area correlation coefficient between GLOBCOVER and CCI LC is the highest at 0.998. (2) The CCI LC had the highest OA and kappa coefficient of 59.01% and 0.4957, while the GLOBCOVER product had the lowest OA and kappa coefficient of 49.24% and 0.3614, respectively. (3) The consistency of the water landscape index is high between the CCI LC and GLOBCOVE data, the consistency of the artificial surfaces landscape index is high between the CCI LC and MCD12Q1 products, and the consistency of the grassland/shrubland landscape index is high between the GLOBCOVE and MCD12Q1 products. The results of microscopic landscape patterns show that the three product landscape patterns are generally more consistent in East Malaysia than in West Malaysia. The low accuracy of grassland, bareland, and shrubland is the key reason for the wide variation in landscape patterns between the three products.

The Dabanghe River Basin, in the west of Guizhou Plateau, consists of numerous prominent geological structural features, such as the Shuicheng–Wangmo, Yadu–Ziyun, and Yongningzhen Faults, the Huangguoshu Waterfall, and the Guanjiao Knickpoint. The topographic conditions and structural systems are highly complex, making this a suitable area to study neotectonics. However, research on the geomorphology of the region is lacking. Combined with geomorphic parameters, quantitative exploration of tectonic geomorphic and tectonic activity in the Dabanghe River Basin is of great significance to reveal the formation of the Huangguoshu Waterfall, the development of landforms in western Guizhou, and the regularity of uplift of Guizhou Plateau. Therefore, based on a Digital Elevation Model, GIS software extracted and calculated six geomorphic parameters of the basin: Hypsometric Integral, Asymmetry Factor, Basin Shape Ratio, Stream-Gradient, and Valley Floor Width–Valley Height Ratio (VF) indexes. The tectonic geomorphic characteristics of the Dabanghe River Basin were analyzed, combined with the tectonic activity level classification method, and the Index of Relative Active Tectonics (IAT) of each sub-catchment was calculated. The geomorphic parameters of the basin were found to indicate its geomorphic characteristics well. The tectonic activity in the study area midstream is the most active, and the geomorphic evolution of some upstream and downstream reaches is affected by lithology, topography, and structure. The tectonic geomorphology of the basin is significantly affected by the fault system. Under the control of the Yadu–Ziyun Fault, the tectonic activity in the basin gradually weakens from west to east, and the differential tectonic activity (strong in the mid-reach and eastwards decrease) is consistent with observed seismic intensity. It is confirmed that our research results are consistent with the regional geological background and geomorphic characteristics through field geological survey. Therefore, this study confirms that the use of tectonic geomorphic parameters to classify active tectonics can be an important method to evaluate the stability of the crust in the region and further extends the application of geomorphic parameters in tectonics.

Heavy metal pollution of groundwater can have severe potential impacts on human health and the environment. The aim of this study was to evaluate the spatial distribution, pollution, and health risk of heavy metals in groundwater in the main pepper production area of China. A total of 67 groundwater samples were collected, and the concentrations of cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), manganese (Mn), and zinc (Zn) elements were analyzed. The results indicated that the average concentrations of Cd, Cr, Cu, Mn, Ni, and Zn in groundwater are lower than the limits of the Standard for Groundwater Quality of China (Class III). However, the maximum concentrations of Mn, Cd, and Ni surpass the Standard for Groundwater Quality of China. The spatial distribution patterns of the concentrations and pollution levels of the six heavy metals in groundwater to be substantially heterogeneous. Furthermore, the pollution level of heavy metals in groundwater decrease in the following order: Mn > Cd > Ni > Cr > Zn > Cu, and the collected groundwater samples are found to be slightly polluted by heavy metals. Overall, the non-carcinogenic risk of the investigated metals, instigated primarily by oral ingestion of groundwater, are found to be higher than the acceptable range for children, and Cd poses the most significant health risk among the investigated metals.

In order to explore the effect of reconstructing soil quality change after adding Pisha sandstone rich in clay mineral materials to improve sandy soil in the Mu Us Sandy Land. Long-term field monitoring experiments were conducted to study the characteristic changes of the reconstructed soil carbon and nitrogen content and corn yield with different proportions of Pisha sandstone and sand. The results showed that after 9 years of experiment, compared with the original sandy soil, in T1, T2, and T3 treatments the reconstructed soil organic matter content increased by 10, 12, and 11 times, total nitrogen content increased by 5.5, 5.4, and 3.9 times, and corn yield increased by 43.9, 105.9, and 58.5%. Especially, the corn yield of T2 and T3 treatment is greater than or equal to the corn yield of local high-yield fields. In summary, the reconstructed soil quality in different proportions has developed toward a good trend after long-term planting. T2 and T3 treatments have the best effects on reconstructing soil carbon and nitrogen accumulation reconstruction and corn yield increase. T2 and T3 treatments are recommended as the best scientific ratio for improving sandy soil with Pisha sandstone in Mu Us Sandy Land. This method has important reference and guidance for ecological remediation of desertification and degraded land.

Profile sampling, which causes missing or overlapping horizons, has been generally used while studying loess stratigraphy and paleoclimate. Conversely, drill sampling of thick loess can provide a relatively complete and actual record of the Quaternary climate and environmental changes. Here, paleomagnetic chronological analysis and particle size and magnetic susceptibility analyses were performed to accurately reveal the loess stratigraphy characteristics of Luochuan loess tableland in Fu County, Shaanxi Province, China. The FX core revealed that the Quaternary loess layer was 167.03 m thick and consisted of 33 layers of developed loess/paleosol sequences and 37 loess/paleosol assemblages. The paleosol horizons indicated relatively warm and humid climatic period, while loess/sand reflected cold and arid climate. Since 2.6 Ma, the climate of the region has undergone 37 warm and cold cycles trending toward an increasingly dry and cold climate. During this time, 10 paleoclimate cycles occurred during 2.6–1.6 Ma, 15 climate cycles occurred during 1.6–0.8 Ma, and 12 loess–paleosol cycles have occurred from 0.8 Ma to the present day. Our study provides a basis for accurately and comprehensively interpreting the paleoclimate and paleoenvironment during loess deposition formation.

It is essential to analyze the dynamic characteristics of regional groundwater levels and their driving factors for the rational development of groundwater in irrigated areas. This article explores the spatial distribution characteristics of the amplitude of groundwater level change in the Shihezi irrigated area by using the ArcGIS interpolation method and contrast coefficient variance method and analyzes the influence factors of dynamic change of groundwater levels by integrating the grey relational degree and path analysis methods and obtaining the sensitivity of each influencing factor to changes in groundwater levels and the relative importance of the influencing factors. The following results are obtained: (1) the groundwater level of the Shihezi irrigated area showed an overall increasing trend from 2012 to 2019, with a fluctuation range of 12.26–14.14 m. The groundwater level in the southeast of the irrigated area showed an upward trend, while the groundwater level in the northwest area showed a downward trend. (2) The groundwater level in the irrigated area first increased, then decreased, and then increased again. The variance of the contrast coefficient in the irrigated area ranged from 0.04 to 11.31, and the fluctuation range of the groundwater level in the central area was higher than that in the northern and southern areas. (3) The irrigated area of cultivated land and evaporation are the main factors affecting groundwater level change in the Shihezi irrigated area. The grey relation analysis shows that the irrigated area of cultivated land has the highest grey correlation degree with the evolution of the groundwater level, which is 0.947, and the average grey correlation index is between 0.74 and 0.95. Path analysis showed that the irrigated area of cultivated land, surface water usage, and evaporation were the main factors affecting groundwater levels. Human activities are one of the main driving forces of groundwater level change, and the research results provide a theoretical basis for the rational utilization and sustainable development of groundwater resources in the Shihezi irrigation area.

This article investigates creating digital maps for physical and geotechnical characteristics of soil based on Geographical Information Systems (GIS) technology and remote sensing for one of the most important areas in Egypt, namely, Delta Nile region, which is characterized by its agricultural and cultural resources. To create accurate digital maps for the soil characteristics of this area, data are collected mechanically, manually and in the laboratory and loaded up with the help of GIS technology using Modified Inverse Distance Weighted as a spatial interpolation technique throughout using 119 soil samples inside Kafr El-Sheikh Governorate, Egypt. A digital elevation map of the Delta region has been downloaded using remote sensing technology to obtain the reduced levels of the different points for the studied area. Data were analyzed and studied well to produce six digital maps describing the important physical and geotechnical characteristics of soil such as groundwater level, pH water −Log (H + ); the percentage of salts and chlorides (NaCl); Sulfate ratio (SO 4 ); average appearance of the sand layer and average appearance of the clay layer. The results indicate a significant increase in the percentage of chlorides and sulfates, as the percentage of chlorides increased at a rate ranging between 2,000 and 6,000 mg L −1 up to 86.95% of the study area. It was noted that the percentage of sulfates increased at a rate range between 1,000 and more than 2,000 mg L −1 up to 91.5% of the study area. The final groundwater level ranges between 1.5 and 3 m under ground level, but the largest percentage is at a level of 1.5 m with a percentage up to 70% of the area of the study area. When conducting tests on water to determine the acidity and alkalinity aspect, we concluded that most of the values are between 6.8 and 7.3, with 44.62% for the first and 52.63 for the latter.

The effect of contamination with petroleum substances (A1 jet fuel and 15W40 mineral oil) on the compressibility and consolidation of mixtures of ice-dammed clay and aeolian sand was determined in a Barden–Rowe consolidometer adapted for liquid-phase contamination tests. The deterioration of the filtration capacity of the contaminated soil medium relative to the non-contamination condition is reflected by the mobilization of higher values of pore pressure u b and pore water pressure parameter C CL in the course of consolidometer tests. As a consequence, lower values of the compressibility modulus M 0 and the consolidation coefficient c v are obtained in relation to the results of uncontaminated samples. This generally indicates changes in the consolidation parameters of the soil medium in the presence of the tested contaminants. Methodologically, a delay in the onset of the steady-state phase of constant loading (CL) consolidation was observed in contaminated soils. This provides a rationale for programming the tests at lower values of the CL rate. At the same time, the unified model characterization of C CL – T CL allows us to assess the reliable nature of the results. This allows one to recommend CRL (constant rate of loading) tests as a reliable tool for determining the consolidation properties of cohesive soils in the design of soil isolation barriers.

The build-up and occurrence of earthquakes are due to the accumulation and release of stress in fault zones. When subjected to tectonic extrusion stress, the crystal structure of the minerals within a fault zone will change. In this study, Raman spectroscopy analysis was conducted on the concurrently deposited quartz veins from Shenxigou, along the Yingxiu-Beichuan fault, and from Niyang River mouth, in the southern section of the Milin fault. The test results reveal a 3.29 cm −1 shift in the characteristic 464 cm −1 peak of the quartz in the veins along the fault plane of the Yingxiu-Beichuan fault, which was significantly lower than the shifts in the quartz peaks of the quartz on both sides of the vein. The 464 cm −1 peak shifts of the samples collected 10 m to the NW and 21 m to the SE of the fault plane were approximately 4.40 and 4.62 cm −1 . In the veins from the Milin fault, considerable shifts of the 464 cm −1 quartz peaks occurred at the fault plane and to both sides within 5.5 m of the fault plane. No significant change in the 464 cm −1 Raman peak of quartz was observed for the samples 5–28 m to the SE of the fault plane. These results indicate that the tectonic extrusion stress accumulated more easily in proximity to the fault plane, resulting in significant changes in the crystals near the fault plane. We conclude that there is a correlation between the degree of change in the crystal structures of the minerals in thrust fault zones and fault activity, and such a correlation can provide a new method for studying the activity of thrust faults in areas with bedrock.

Qiang religious culture is the result of its adaptation to the natural environment and socio–economic development. The Upper Reaches of Min River has been the main inhabiting district of the Qiang ethnic group in China. Based on the construction of the resource system for Qiang religious culture, this study quantitatively illustrated the cognitive characteristics of this culture in the basin and the main factors influencing its regional differentiation using statistical methods, Moran’s I method, Getis-Ord Gi* method, and the Geo-detector model. The results suggested that the respondents’ cognitive degree (RCD) in relation to the religious culture in the study area was 0.258 ± 0.031, and the cognitive degrees for religious buildings, supplies, literature, and beliefs were as follows: religious literature (0.332) > religious supplies (0.287 ± 0.076) > religious buildings (0.222 ± 0.037) > religious beliefs (0.193 ± 0.023). This result was mainly related to the dissemination methods of religious cultural elements, the status of their preservation, and changes in the production and lifestyle of the people. Furthermore, the respondents’ cognition presented significant regional differentiation characteristics. Two natural factors, namely, humidity and elevation, were the major ones that influenced cognitive regional differentiation with influences values of 0.293 and 0.280, respectively. Elevation and average night light index exhibited significant correlations with cognition ( p < 0.05). Meanwhile, the influence was enhanced when various factors interacted with one another. This study contributes to the quantitative research on the sustainable development of the Qiang religious culture and national culture inheritance.

Iron is one of the most important basic materials in infrastructure development, spatial and temporal variation characteristics analysis of infrastructure iron stocks is conducive to revealing its distribution and change patterns from different scales, which can provide a scientific basis for sustainable urban development and iron resource management in China. In this article, we first calculated provincial infrastructure iron stock data from 2000 to 2020. Then, fitting equations between nighttime lighting data and infrastructure iron stock are constructed to simulate the spatial distribution of China’s infrastructure iron stock at 500 m resolution from 2000 to 2020. Finally, the spatial and temporal dynamics of China’s infrastructure iron stock is analyzed from four scales: national, regional, provincial, and urban agglomeration. The results show as follows: (1) China’s infrastructure iron stock grew at an average annual rate of 26.42% from 2000 to 2020, with China’s infrastructure iron stock increasing 6.28 times over the 21 years. Construction facilities are the most important part of the infrastructure iron stock, and its share is still increasing. (2) On a regional scale, the high-growth type of infrastructure iron stock is mainly distributed in the eastern region, while the no-obvious-growth type is mainly distributed in the western region. The high grade of infrastructure iron stock is mainly distributed in the eastern region, while the low grade is mainly distributed in the western region. (3) On a provincial scale, the highest share of no-obvious-growth type of infrastructure iron stock is in Xinjiang. The highest proportion of infrastructure iron stock of high-growth type is in Jiangsu. The highest proportion of low-grade infrastructure iron stock is in Xinjiang. The highest proportion of infrastructure iron stock of high grade is in Beijing. (4) In terms of urban agglomerations, the high-growth type of infrastructure iron stock is mainly located in Shanghai–Nanjing–Hangzhou, while the no-obvious-growth type is mainly located in the Middle south of Liaoning. The high-grade infrastructure iron stock is mainly distributed in Shanghai–Nanjing–Hangzhou, while the low grade is mainly distributed in Sichuan–Chongqing.

The need for mineral resources for economic development is key in both developing and developed countries. However, miners usually resort to random excavation of mineral deposits without proper investigation to identify structures of interest in target areas. This usually leads to land depletion and abandonment. The aim of this study is to assess the mineral potential in part of the Benin-arm of the Anambra basin by investigating the geophysical characteristics of the area using remote sensing and aeromagnetic data. Surface and subsurface regional structures, including faults and zones of mineralisation, were mapped by integrating aeromagnetic and remote sensing data. The mineral bearing zones that show high prospects of mineral deposits in the region were identified. The rose diagram revealed that the surface lineaments are aligned in the NW–SE, N–S, NE–SW, E–W, NNE–SSW, ENE–WSW, and ESE–WNW directions. The orientations of the subsurface lineaments are aligned mostly in the NE–SW, N–S, and E–W directions. The magnetic intensity ranged between −431.38 and 399.82 nT, while reduction-to-pole magnetic intensity ranged from –416 to 664.45 nT. The first vertical derivative showed magnetic intensity which ranged from –0.5863 to 0.9060 nT/km 2 . The total horizontal derivative magnetic intensity ranged from –0.00031 to 0.762691 nT/km 2 , while the analytic signal showed magnetic intensity ranging from 14.0664 to 394,607.3438 nT/cm 2 . The windowed Euler deconvolution depth to magnetic source showed depth range of <20 to 2,000 m. Many of the features delineated in the study area were characterised by shallow magnetic source depths (<500 m); this is a common characteristic of basement complex terrains. Deeper magnetic source depths (>1,000 m) were observed in the sedimentary terrain. Mineral exploration should be focused in areas with high lineament concentration, as lineaments are potential conduits for economic minerals deposition.

The reconstruction and analysis of building models are crucial for the construction of smart cities. A refined building model can provide a reliable data support for data analysis and intelligent management of smart cities. The colors, textures, and geometric forms of building elements, such as building outlines, doors, windows, roof skylights, roof ridges, and advertisements, are diverse; therefore, it is challenging to accurately identify the various details of buildings. This article proposes the Multi-Task Learning AINet method that considers features such as color, texture, direction, and roll angle for building element recognition. The AINet is used as the basis function; the semantic projection map of color and texture, and direction and roll angle is used for multi-task learning, and the complex building facade is divided into similar semantic patches. Thereafter, the multi-semantic features are combined using hierarchical clustering with a region adjacency graph and the nearest neighbor graph to achieve an accurate recognition of building elements. The experimental results show that the proposed method has a higher accuracy for building detailed edges and can accurately extract detailed elements.

To study the characteristics of the present crustal movement in the Tibetan Plateau and explore its relationship between strong earthquakes with magnitudes of 8 and above, the velocity field size was analyzed based on the global position system (GPS) campaign observations and the time series of site north-ward displacement and long baseline were discussed using the GPS continuous observations. The results show that the velocity field size in the Tibetan Plateau decreases from southwest to north, northeast, and southeast, and the value of the velocity in the west is significantly greater than that in the east in the same dimension. The maximum value is located in the southwest and the minimum value is located in the east. The Wenchuan earthquake is located in the mutation region, where the rate and the direction of the crustal movement are quite different. The crustal deformation extent is large in the region close to the seismic source before the earthquake, reflecting that the regional stress accumulation is fast and its required time is relatively short. However, the crustal deformation extent is relatively small in the region away from the seismic source before the earthquake, reflecting that the regional stress accumulation is slow and its required time is relatively long. The N-ward movement became significantly strong after Nepal M S 8.1 earthquake; the occurrence of this earthquake may have caused the unlocking of large-scale faults near the seismic source, which further intensified the NE-ward subduction and collision of the Indian Plate. The compression of the Indian Plate to the Tibetan Plateau slowed down after the 2008 Wenchuan M S 8.0 earthquake, and increased significantly after 2015, which boosted strain accumulation in the Tibetan Plateau, and attention needs to be paid continuously to strong earthquake risk in this region.

The southwestern Ordos Basin is located at the junction of several stable plates, where faults and fractures are relatively developed, and the influence of fractures on the distribution of tight oil reservoirs in the Yanchang Formation is not clear. To solve this problem, the characteristics of fracture development of the Yanchang Formation, southwestern Ordos Basin and its control on hydrocarbon accumulation have been systematically studied using the core, thin section, well logging, productivity, fault and sand body distribution data. The results show that vertical and horizontal bedding fractures are much more developed in the Chang 8 Member compared with the Chang 6 and 7 Members. For horizontal bedding fractures, they are mainly developed in fine sandstone, followed by siltstone, while no horizontal bedding fractures are observed in medium sandstone. This is because horizontal bedding fractures are more common in fine-grained sediments. For vertical fractures, they are also mainly developed in fine sandstone. The controlling factors of fractures include lithology, sand body thickness, sedimentary microfacies and fault–fracture coupling relationship. Fractures are well developed in the fine-grained sandstone of the wing parts of the main river channel due to small compacted space. In the area where multiple river channels intersect, the sand is pure and easy to break. Based on the comprehensive study of sedimentation, structure and fracture, the classification criteria of sweet point reservoir of the Yanchang Formation are determined: sedimentary microfacies of the main river channel and its wing, tectonic location within 1.5 km from the main fault, plane arrangement of right-lateral and right-order faults and developed fractures. The sweet point reservoir can be identified effectively using the developed sweet point screening criteria.

Soil quality is the key to the success or failure of the gully land reclamation project. Studying the variation characteristics of soil nutrients and evaluating the nutrient classes in the gully after the implementation of gully land reclamation project in the loess hilly and gully region can provide a basis for adjusting the spatial layout of gully crops, rational planning and utilization of land resources, and soil nutrient management. In this study, a typical gully in Yan’an City, Shaanxi Province, China was taken as the research object. Based on the data of soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK) before 0 year (0a) and after 2, 4, and 8 years (2a, 4a, and 8a) gully remediation. From the spatial distribution characteristics of soil nutrients and its levels, the classical statistical analysis, geostatistical analysis, and matter-element model were used to reveal the variation characteristics of soil nutrients in the gully before and after the gully land reclamation project. The results showed that (1) before remediation, except for AK which reached the level of 1–3, the rest of the nutrients content was generally low and the degree of variation was large, after remediation the degree of variation decreased and the coefficient of variation was between 0.23–0.54, the distribution tended to be uniform. (2) SOM content showed a “decrease–increase” change process, reaching the highest after remediation (8a); TN and AP increased first and then decreased; AK showed a “downward–upward–downward” change process. (3) The soil nutrient grade belongs to the appropriate level. After the implementation of the project, only the gully head is reduced to the poor level. After 4a of remediation, the soil nutrient grade is restored and has the potential to continue to improve. Compared with the slope land remediation, the soil nutrient recovery time of gully land creation is shorter, the spatial layout of crops can be adjusted according to the soil nutrient characteristics of different locations in gully, and different levels and methods of management measures can be implemented to increase food production.

With balanced training sample (TS) data, learning algorithms offer good results in lithology classification. Meanwhile, unprecedented lithological mapping in remote places is predicted to be difficult, resulting in limited and unbalanced samples. To address this issue, we can use a variety of techniques, including ensemble learning (such as random forest [RF]), over/undersampling, class weight tuning, and hybrid approaches. This work investigates and analyses many strategies for dealing with imbalanced data in lithological classification based on RF algorithms with limited drill log samples using remote sensing and airborne geophysical data. The research was carried out at Komopa, Paniai District, Papua Province, Indonesia. The class weight tuning, oversampling, and balance class weight procedures were used, with TSs ranging from 25 to 500. The oversampling approach outperformed the class weight tuning and balance class weight procedures in general, with the following metric values: 0.70–0.80 (testing accuracy), 0.43–0.56 ( F 1 score), and 0.32–0.59 (Kappa score). The visual comparison also revealed that the oversampling strategy gave the most reliable classifications: if the imbalance ratio is proportionate to the coverage area in each lithology class, the classifier capability is optimal.

The current cultivated land quality (CLQ) evaluation method fails to consider the determination of soil nutrients, resulting in the low efficiency of soil nutrient message extraction. In an effort to effectively solve the above problems, combined with the spatial variation of soil nutrients (SVSN) at the field scale, a CLQ evaluation method is proposed. The soil nutrients were determined according to the soil spatial variation analysis, and the soil color was standardized. The characteristic bands were determined by soil fertility and nutrients such as nitrogen, phosphorus, and potassium, and the soil nutrient message was preprocessed. On this basis, the soil nutrient message extraction model was constructed. According to the damage principle of subsoiling shovel, the limit value of the membership function of the CLQ exponent is determined, and the weighted sum method is used to calculate the CLQ exponent, so as to realize the SVSN and the evaluation of CLQ at the field scale. The experimental results show that the dimensional autocorrelation of soil bulk density and soil water content in different soil layers is high and that of capillary porosity, non-capillary porosity, and total porosity in different soil layers is strong.

In this work, a sediment core collected from the Jiulong River estuary in southeastern China was subjected to 14 C dating of foraminifera, as well as lignin, total organic carbon, and stable carbon isotope (δ 13 C) analyses in order to determine the impacts of climate change and human activities on the sedimentary organic matter in this area from around 2,000 to 1,000 years ago. The ratios of lignin parameters syringyl/vanillyl and cinnamyl/vanillyl ranged from 1.60 to 8.63 and 0.11 to 0.45, respectively, and the lignin phenol vegetation index ranged from 25.14 to 1740.14, indicating the presence of non-woody angiosperms. The ratio of vanillic acid/vanillin ranged from 0.42 to 2.04, indicating medium to high degrees of oxidative degradation. The vertical distribution profile showed a similar historical sedimentary trend with locations at higher latitudes along the Zhejiang-Fujian Mud Area, with the lower abundance of total lignin from around 2400 to 2000 BP being attributed to the decreasing temperature during this period. However, all the lignin parameters showed higher values and greater fluctuations due to increasing temperatures after 2000 BP, and human activity has probably had the greatest impact in the most recent 1,000 years.

Evidence shows how disasters caused by extreme weather events are surely becoming more frequent at all latitudes, and are definitely representing an ever-growing risk in the floods- and landslides-prone territory of Burundi. The still present inequalities of its society and the vulnerable economy make this African country a very relevant and particularly complex case for hazards risk management. A fundamental step in this task is to correctly map the so-called exposure elements to risk, which most notably comprise the population and households, the critical infrastructure, and the transportation network. In this article, we assess the quality of the OpenStreetMap (OSM) roads database in Burundi at national level, with a perspective in its fitness-for-use in the assistance for disaster risk mitigation purposes, which were adopted in the context of a recent multi-hazards risk assessment and mapping exercise on behalf of the International Organisation for Migration. Despite not touching all aspects of volunteered geographic information data quality that are commonly found in literature for a comprehensive assessment, we believe the information provided in this study can be of help for stakeholders in their decision to use the OSM dataset in an otherwise data-scarce area.

This article explores how natural language processing techniques can be applied to extract information from spatial planning documents and how this information can be represented in a knowledge graph. The proposed method uses named entity recognition to extract relevant information from text and structure it into labels and corresponding values. The extracted information is represented in the form of a knowledge graph, which allows for better understanding and management of complex relationships between different elements in spatial planning documents. For this purpose, a dedicated ontology was developed. The research demonstrates that the proposed method achieves good results with high precision, recall, and F 1 scores for all entity types, with particularly remarkable results for biologically active area predictions. The practical application of this method in spatial planning can contribute to improving decision-making processes and streamlined collaboration between different entities involved in spatial planning.

Global warming has caused changes in various ecological processes and has potential to change ecosystems’ stability. In spite of comprehensive studies to investigate air temperatures under global warming, much less is known about changes in soil temperatures, particularly in deep layers. Herein, we used 30 years of soil temperature data from a temperate steppe region to assess vertical characteristics and their changes in soil temperature from the surface to a depth of 3.20 m. We determined, apparently for the first time, that the soil temperature is the lowest at 0.2 cm layer at an annual level. Furthermore, the vertical variation of soil temperature (temperature variation with soil depth) strictly conformed to composite exponential function curves, and there were two composite exponential function curves that are symmetric to each other, to represent soil temperature in a pair of months with a difference of 6 months. Parameters in the functions changed as the soil warmed over 30 years. This finding explored the pattern of soil temperature in deep layers depending on the mathematics model. Model building and understanding is beneficial for predicting vertical and temporal extensions of soil temperature and their impact on below-ground processes in regional ecosystem.

The landslide susceptibility assessment is an essential part of landslide disaster risk identification and prevention. However, the binarization of the hidden layer limits the parameterization ability of the conditional probability of visible layer, making the training process of restricted Boltzmann machine more difficult and further limiting the accuracy and efficiency of deep belief network (DBN) model in landslide susceptibility assessment. Therefore, this study proposed a landslide susceptibility assessment method based on Auto-Encoder (AE)-modified DBN. Zhouqu County, Gansu Province in the People’s Republic of China, was selected as the study area. Historical landslides in Zhouqu County were identified using small baseline subset interferometric synthetic aperture radar technology and optical image. Landslide factors were screened based on a geographical detector and stepwise regression method. The Logcosh loss function and determinant coefficient R 2 index were used to evaluate the training process of the AE model, and the balanced cross entropy loss function was used to evaluate the entire network training process. In addition, the area under the curve (AUC) of the synthetical index model (SIM), support vector machine (SVM), and multilayer perceptron (MLP) were compared and evaluated. The results indicated that the proposed model could significantly improve the accuracy of landslide susceptibility assessment. The AUC value of the proposed model was 0.31, 0.12, and 0.11 higher than that of SIM, SVM, and MLP, respectively. Therefore, the improved DBN model based on AE proposed is reliable for early landslide identification and prediction. Graphical abstract

Displacement monitoring method of reservoir dam is a key research topic at present. In order to better display the overall efficiency of horizontal displacement and vertical displacement monitoring, a numerical simulation analysis method of ecological monitoring of small reservoir dam based on the maximum entropy algorithm is proposed. The virtual value is calculated by the maximum entropy algorithm, and the probability distribution function of random variables is obtained. The comprehensive prediction model of ecological monitoring results is constructed by the probability distribution function, and the daily monitoring values of ecological history of small reservoir dams are obtained. The maximum entropy probability density function is used to calculate the initial moment of small reservoir displacement samples, calculate the abnormal probability of the dam, get the maximum entropy probability density, realize the unbiased distribution of simulation values, and complete the dam deformation monitoring of small reservoirs. The simulation experiment is verified by numerical simulation. The results show that this method can effectively monitor the horizontal and vertical displacement of the dam; monitor the water-level hydrograph of pressure pipes at each measuring point; and obtain the changes of ecological runoff, temperature difference, and sediment discharge around the dam of small reservoirs in real time, which provides data guarantee for improving the ecological added value of small reservoirs.

Aeolian dunes have been widely identified in the European Sand Belt, which was formed during the Pleniglacial and Late Glacial when cold and dry climatic conditions were favorable for intense Aeolian processes. In this study, we mapped and analyzed the fixed Bory Stobrawskie Dune Field (SW Poland) to determine factors that drive the evolution of dunes, expressed by the occurrence of different dune types and their spatial patterns. The study identified the longitudinal zonation within the dune field, as shown by the changeable proportion of specific dune types comparable to low-latitude dune fields. However, climatically controlled periodic and low sand supply combined with a changing vegetation cover caused the non-continuous and multi-phase evolution of the dune field. Additionally, we found that a dense pattern of streams has controlled the extent of the dune field. The trapping of sand by rivers led to a limitation of the dune field expansion; on the other hand, the supply of sand into rivers led to overloading of the fluvial system, affecting their transformation into braided rivers. Graphical abstract

Every year, hundreds of people go missing in the wilderness of Saudi Arabia. There is an urgent need to examine modern geographic techniques for finding such people. Geographical information systems, for example, play a crucial role in wilderness search and rescue (WiSAR), not only in mapping probability areas but also in applying further analysis and modeling methods to reduce time and effort and to guide life-saving task forces in the right direction. In this study of a hypothetical missing-person case in Saudi Arabia, two standard WiSAR models are compared: ring and mobility. In the presented study situation, both models can be used. However, the new approach used in the mobility model drastically reduces the extent of the possible search area, from 101,787 km 2 in the ring model to 335.34 km of likely trails and unpaved roads, and also provides exact directions to where the missing person may be found.

The lack of clarity regarding slip distribution within heterogeneous rupture areas has a significant impact on characterizing the seismic source and the role of heterogeneities in determining ground motion. One approach to understand the rupture process is through dynamic simulations, which require substantial computational resources, thereby limiting our comprehension of seismic rupture processes. Consequently, there is a need for methods that efficiently describe the spatial complexities of seismic rupture in a realistic manner. To address this, the statistics of real self-arrested ruptures that conform to the asperity criterion are investigated. This research demonstrates that power law distributions can describe the final slip statistics. Regarding the computational efficiency, a simple heterogeneous energy-based (HE-B) method is proposed. The HE-B method is characterized by the spatial correlation between the rupture parameters, such as the final slip or the rupture velocity, and the distribution of residual energy which determines the zones where the rupture could occur. In addition, the HE-B method defines the rupture area in those zones of the fault where the coupling function exceeds the energy required for rupture initiation. Therefore, the size of the earthquake is directly influenced by the distribution of coupling within faults. This method also leads to the successful reproduction of the statistical characteristics of final slip and generates slip rates that match the kinematic behavior of seismic sources. Notably, this kinematic rupture simulation produces seismic moment rates characterized by f − 1 {f}^{-1} and f − 2 {f}^{-2} spectra with a double corner frequency. Finally, it is observed that the maximum fracture energy value within the ruptured area is strongly correlated with both the magnitude and peak seismic moment rate. Thus, by employing this method, realistic rupture scenarios can be generated efficiently, enabling the study of spatial correlations among rupture parameters, ground motion simulations, and quantification of seismic hazard.

Layered rock slopes are the most widely distributed slopes with the simplest structure. The classification of layered rock slopes is the basis for correctly analyzing their deformation and failure mechanisms, evaluating their stability, and adopting reasonable support methods. It is also one of the essential indicators to support the evaluation of urban and rural construction suitability and the assessment of landslide hazards. However, the present-day classification methods for layered rock slopes are not sufficiently automated. In the application process of these methods, a lot of manual intervention is still needed, and sufficient strata orientation data obtained through field surveys is required, which is not effective for large-scale applications and involves high subjectivity. Thus, this study proposes a semi-automated classification method for layered rock slopes based on digital elevation model (DEM) and geological maps, which greatly reduces human intervention. On the basis of slope unit division, the method extracts structural information of slopes using DEM and geological maps and classifies slopes according to their structural characteristics. An experiment has been carried out in the northern region of Mount Lu in Jiangxi Province, and the results demonstrate the effectiveness of this semi-automated classification method. Compared to the existing manual or semi-automated classification methods, the method proposed in this article is objective and highly automated, which can meet the requirements of classification of layered rock slopes over large areas, even in the case of sparse measured orientation data.

The Tak Batholith is located in the western part of Thailand’s eastern granitoid belt. To better understand the geochemical characteristics of granitoid and identify their occurrence, rock samples collected from the eastern part of the Tak Batholith were used for petrographical, mineralogical, and geochemical analyses. According to field investigation and lithology, petrography classifies these granitic rocks as medium-grained granodiorite and granodioritic dike. The granodiorites are composed chiefly of plagioclase, orthoclase, quartz, hornblende, and biotite, with tiny amounts of zircon, apatite, and opaque minerals. Meanwhile, the granitic dike shows a highly porphyritic texture, presenting mostly plagioclase phenocrysts, with a small amount of orthoclase and unidentified mafic phenocrysts sitting in a fine-grained groundmass comprising K-feldspar and quartz with a small amount of plagioclase and present granophyric intergrowth. Geochemical data of the amphiboles classified them as Ferro-edenite symbolizing the I-type granite. Whole-rock geochemistry indicates that these rock suites are I-type metaluminous granodiorite, and diorite fractionated from the high K calc-alkaline magma melted from the mafic crust of arc magmatism agreeable with the enrichment of large ion lithophile elements and depletion of highfield-strength elements, and rare earth element patterns.

Distinguishing different kinds of igneous rocks is difficult because of their subtle differences. Synthetic aperture radar (SAR) is sensitive to rock surface morphology, which can help a lot in classification. Dual-pol SAR data have the advantages of low cost, but few articles are using only dual-pol SAR data for igneous rock classification. In this study, we explored the performance of dual-pol SAR data in distinguishing granitoid, tuff, and syenite porphyry. Backscatter coefficients, polarization decomposition parameters, and texture features from gray-level co-occurrence matrix extracted by Sentinel-1 or PALSAR were classified using several machine learning algorithms. The results are as follows. First, the texture information has greater potential for igneous rock classification, but the polarization decomposition parameters contribute less. Second, after comparing machine learning algorithms, AdaBoost algorithm has the highest overall accuracy for either C-band or L-band SAR data. C-band SAR data provide better classification results than L-band. Finally, tuff is the easiest igneous rock to be successfully classified, and L-band dual-pol SAR data have advantages in the discrimination of syenite porphyry. This study outlines the effectiveness of dual-pol SAR data for igneous rock classification, which will help to select SAR data of appropriate wavelengths for specific types of lithology discrimination.

The geological condition of Ho Chi Minh (HCM) City is soft soil and high groundwater and includes two main structural layers such as Pleistocene and Holocene sediments. Therefore, deep excavation of all the high-rise buildings in the city is usually supported by concrete retaining walls such as the diaphragm or bored pile retaining walls. The system limits the excavation wall deflection during the construction process which could pose a potential risk to the construction and neighborhood areas. To estimate wall deformation at a highly accurate and efficient level, this study presents several machine learning models including feed-forward neural network back-propagation (FFNN-BP), long short-term memory (LSTM), bidirectional long short-term memory (Bi-LSTM), and support vector regression (SVR). The database for the experiment was obtained from a high building in HCM City, Vietnam. The database is deployed to implement the proposed algorithms in walk-forward validation technique. As a result, the Bi-LSTM model reduced prediction errors and improved robustness than the LSTM, FFNN-BP, and SVR models. Bi-LSTM, LSTM, and FFNN-PB could be used for predicting deep excavation wall deflection. In the meantime, not only could the estimated results support safety monitoring and early warning during the construction stages but also could contribute to legal guidelines for the architecture of deep excavations in the city’s soft ground.

The middle Permian Maokou Formation in the Longnüsi area in the central Sichuan Basin is currently a key formation for exploration and development. The evaluation of the current in situ stress in this area is of great significance for fracture prediction, well pattern deployment, drilling and construction, and fracturing stimulation. This study clarifies the current direction and magnitude distributions of the in situ stress by evaluating the Maokou Formation in the Longnüsi area using finite-element numerical simulation, acoustic emission experiments, and logging data (including data from imaging logging, array acoustic logging, conventional logging, and cross-dipole acoustic logging). Specifically, the current maximum horizontal stress of the Maokou Formation in the Longnüsi area is mainly in the NW‒SE direction, and the stress direction is greatly affected by the local fault zone. The current minimum horizontal stress magnitude of the Maokou Formation obtained by acoustic emission experiments is between 96.29 and 114.36 MPa, the current maximum horizontal stress magnitude is between 126.01 and 145.10 MPa, and the current horizontal stress difference is between 25.59 and 32.58 MPa. The current minimum and maximum horizontal stress magnitudes both decrease from north to south. The current horizontal stress parameters calculated by Huang’s model are not significantly different from those experimentally measured: there is a difference of less than 8% in the current minimum horizontal stress magnitude, a difference of less than 9% in the maximum horizontal stress magnitude, and a difference of less than 15% in the current horizontal stress difference. Therefore, Huang’s model has good applicability in terms of calculating the current horizontal stresses in the Longnüsi area. The current horizontal stress parameters, which are numerically simulated with the finite-element method, are also not much different from those experimentally measured: there is a difference of less than 11% in the current minimum horizontal stress magnitude, a difference of less than 10% in the maximum horizontal stress magnitude, and a difference of less than 20% in the current horizontal stress difference. The numerically simulated current horizontal stress also decreases from north to south. Therefore, the simulated results are highly accurate. This study clarifies the directions and magnitudes of the current in situ stress state of the Maokou Formation in the Longnüsi area of the central Sichuan Basin and provides a basis for the formulation of exploration and development plans for the Maokou Formation reservoir in the study area.

Geological outcrop is usually the first-hand evidence to cognize the probable geometry, lateral extent, and other properties of conglomeratic channels. If there is no exposure of formation, however, it is hard to recognize elaborate architectural elements just based on poor coverage cores and low-resolution conventional logs vertically. In order to understand vertical distributions of conglomeratic channel architectural elements in the Lower Triassic Baikouquan Formation in southern slope of Mahu Sag, ultrahigh-resolution microresistivity image logs are used to recognize elements under the concept of conglomeratic channel architectures in this article. The microresistivity images were calibrated with cores in different grain-sizes and sedimentary structures. According to microresistivity image fabric, subaerial channel-fills consisted of granules to cobbles; subaqueous channel-fills were composed of well-sorted sandstones to granules. Subaerial channel-margins comprised sandstones to pebbles; subaqueous channel-margins were granules and sandstones. Bypass drapes, deposited from the tail of bypassing flows, were commonly eroded by overlying channel-fills. Convergent drapes, accumulated on top surfaces of channel-margins, preserved well without reworking. Overbank drapes, formed outside the channel, were thick-bedded. Combined with dipmeter pattern of microresistivity image log, six channel story sets were recognized depending on abrupt changes in dip azimuths. In each channel story set, per unit thickness of mud drapes ranged from 0.1 to 0.6 m. Mud drapes in channel story set 1 could be correlated horizontally. In channel story sets 3, 4, and 5, thickness of mud drapes ranged from 0.05 to 2.59 m and averaged at 0.59 m, and channel conglomerates and mud drapes alternated frequently. These understandings would provide important insights on the production potential of petroleum.

Deep sandstone reservoirs in the Paleogene Enping Formation of A-Oilfield, Pearl River Mouth Basin, are significant offshore petroleum targets for this basin. Compared with adjacent water zones and shales, the pays are of low resistivity and low contrast (LRLC). Without new unconventional well-logging techniques, conventional well-logging interpretation has encountered difficulties in these LRLC pays. In this article, based on the Simandoux water–oil saturation equation, influence factors of formation resistivity in sandstone LRLC pays are simulated theoretically. Resistivity cutoff is calculated at average reservoir conditions and proved by oil-testing results. It is applied to oil and water in LWD, and the possible genesis of LRLC is discussed. In sandstone LRLC pays, the resistivity of the oil zone is larger than the resistivity cutoff; the resistivity of the water–oil zone approximates the resistivity cutoff and the resistivity of the water zone is lower than this threshold. At average shale volume and porosity of pays in Enping Formation, the resistivity cutoff is referenced at 4.2 Ω·m overall. In sandstone reservoirs, low formation resistivity in the Enping Formation of A-Oilfield might result from high formation water salinity, complicated pore-throat structure, well physical properties, and the presence of conductive and clay minerals. The resistivity cutoff offers important information in real-time tracking of LWD. The proposed method is demonstrated to be beneficial for identifying hydrocarbons and monitoring trajectory in LRLC pays.

Evacuation routes are necessary to guide people to avoid hazardous and dangerous zones and to prevent the loss of human lives, especially in the event of volcanic eruptions. This article attempts to examine the evacuation routes of the sister village program by using the ant colony optimization (ACO) algorithm. Model simulations and calculations of the ACO algorithm were done by aggregation of the five determined parameters including distance, speed, hurdle, density, and secure point. The validation of the model was carried out by the examination of the five most prone disaster villages located in Mount Merapi that are interconnected as sister villages in Sleman Regency, Yogyakarta Province, and Indonesia. This research is important to ensure that the sister village evacuation system is effective in reducing the impact of the risks posed by the eruption of Mount Merapi. Based on the results, sister village evacuation systems are proven to be the fastest and safest routes by the ACO examination

This article presents a novel method for classifying spatial objects by learning node representations via a spatial walk algorithm. The findings show that considering both the attributes of objects and their topological relationships enables more efficient and precise spatial objects’ classification than methods that only consider the objects’ characteristics. The method emphasizes the importance of spatial dependencies in learning representations for spatial data. A distinctive feature of the method is its focus on local analysis of the neighborhood structure of the node under investigation. The spatial walk algorithm offers a defined path generation scheme, facilitating a deeper understanding of local spatial dependencies between objects. This approach provides a more accurate representation of the essential relationships between spatial objects than random path generation and enhances the classification results, as demonstrated in three different classification scenarios. The method proves particularly effective in the context of spatial objects, where proximity and a limited number of neighbors play a significant role. This is exemplified in the classification of planning areas in spatial development plans.

The study of the distribution of cementitious materials in soil aggregates is important for understanding the formation of aggregates in soil due to the addition of soft rock rich in clay. Soft rock and sand in the ratios of 1:1(C1), 1:2(C2), 1:5(C3), and 1:0(CK) were collected in a test field, and the wet sieve method was used to separate large water-stable soil aggregates. The microstructures of the aggregates and the amounts of iron–aluminum compounds and clay minerals were measured. The result shows that the addition of soft rock improves the ability to create effective soil formations in sand. The order of the amounts of >0.5 mm sized water-stable aggregates based on the different treatments is C1 > C3 > C2 > CK. In the later stages of improvement, iron–aluminum oxides, clay minerals, and calcareous cements in modified soil were important for the formation of water-stable aggregates. The enhancing effect of minerals gradually increases, among which amorphous alumina and complexed iron oxide promote the formation of large water-stable aggregates in improved sandy soil. It is concluded that the engineering technique of compounding soft rock and sand is a new technology that can promote sand-forming soil and permanently change the properties of aeolian sand soil.

The road network is the basic facility for transportation systems in the city. Every day, a large number of vehicles move on the road and exert different pressure on the ground, which leads to various problems for the road surface, such as the bump features of the road surface (BFRS). However, traditional methods, such as detecting BFRS manually or with professional equipment, require a lot of professional management and devices. Based on the mobile sensor and the bidirectional long short-term memory (Bi-LSTM), a detection method for BFRS is proposed. The BFRS detection method proposed in this article solves the problem that other BFRS detection methods cannot detect large area road surface efficiently and provides an algorithm idea for efficient detection of large area road surface BFRS. The mobile phone with multi-sensors is carried on vehicles, and the BFRS information is logged during the movements. The orientation of the mobile is computed according to the gyroscope. The actual posture of the acceleration sensor is adjusted with the reference coordinate system, whose z -axis is vertical to the ground. This article uses the adjusted acceleration data as the training dataset and labels it according to time stamps and videos recorded by the driving recorder. Finally, the Bi-LSTM is constructed and trained, followed by the BFRS detection. The results show that it can detect BFRS in different regions. The detection accuracy of the campus section and the extended experiment was 92.85 and 87.99%, respectively.

This study provides an in-depth analysis of fluid inclusions (FIs) and stable isotopes from the Manondo-Choma gold prospect in southern Malawi to understand the ore-forming mechanisms, genesis, and evolution of the hydrothermal fluids responsible for gold mineralization at the Manondo-Choma gold prospect. FIs and microthermometry studies were carried out on mineralized quartz veins from the area. The Manondo-Choma gold prospect is located in the southern Malawi within the Kirk range. Gold is mostly found in quartz veins within metamorphic rocks, such as gneiss and schists, and is structurally controlled by the NE–SW ductile shear zones. Gold mineralization is linked to quartz sulfide veins. Mineralization occurs in the following three stages: early, middle, and late, of which the middle stage is more plorific. The following three FI types were recognized in the quartz veins: pure carbonic, aqueous carbonic (CO 2 –H 2 O) and aqueous (H 2 O–NaCl) inclusions. Gold and associated mineralization were likely precipitated due to the lowering of pressure and fluid immiscibility. Oxygen isotope data indicate that the source of ore-forming fluids at the Manondo-Choma gold prospect was largely metamorphic in origin with minor magmatic input.

The geochemical sampling work in the difficult and dangerous areas is very hard; hence, it can be greatly improved by combining with the remotely sensed data. Thus, a retrieval model is proposed by Kernel Principal Component Analysis and Artificial Bee Colony (ABC) optimized Support Vector Machine (SVM) models based on Landsat 8 remotely sensed data and the geochemical data in the study area. The analysis results show that the geochemical data delineate the areas with relatively enriched elements, but indicate the low-abnormal ore (chemical) points, and the anomalies delineated by the inversion data are better for this purpose, for better indication. At the same time, the distribution and intensity of the corresponding abnormal areas found that the abnormal areas delineated by the inversion data basically contain the abnormal areas delineated by the original data, and the anomalies located at the ore spots are obviously enhanced; it shows that the SVM model of ABC Optimization can establish the relation between geochemistry data and remote sensing data, can supply the original data effectively, and can also provide the direction for the next prospecting work.

Examining the spatial characteristics and accessibility of cultural facilities, such as art institutions, is crucial for understanding the lifestyles of citizens. With the increasing utilization of multi-source data in geographical studies, new opportunities have arisen for investigating the development of cultural facilities in urban areas. Consequently, this article investigates the spatial dynamics of art institutions in urban development, using Nanjing, a historic city, as a case study. The study obtained a total of 260,392 points of interest data for Nanjing in 2018 and 2022 from the GaoDe map API console. By employing network analysis and the two-step floating catchment area method, the geostatistical findings reveal that the distribution of art institutions in Nanjing has become more balanced over time. For instance, the research indicates that the proportion of residents able to reach art exchange institutions within a 30-min travel time increased from 75% in 2018 to 90% in 2022. However, the distribution of art training institutions remains more concentrated compared to art exchange institutions. Furthermore, the spatial arrangement of art institutions does not entirely align with the distribution of demand points, indicating the potential for further optimization. In conclusion, this study has significant implications for understanding the accessibility, social justice, and urban planning in Nanjing. The government should pay attention to the cultural demands of marginalized communities, promote social justice and cultural inclusiveness by increasing the accessibility of cultural facilities.

Quantitative studies of the pore-throat structure (PTS) characteristics of tight sandstone reservoirs and their effects on fluid mobility were proposed to accurately evaluate reservoir quality and predict sweet spots for tight oil exploration. This study conducted high-pressure mercury injection (HPMI) and nuclear magnetic resonance (NMR) experiments on 14 tight sandstone samples from the Chang 7 member of the Yanchang Formation in the Jiyuan area of the Ordos Basin. The HPMI was combined with the piecewise fitting method to transform the NMR movable fluid transverse relaxation time ( T 2 ) spectrum and quantitatively characterize the PTS characteristics and the full pore-throat size distribution (PSD). Then, movable fluid effective porosity (MFEP) was proposed to quantitatively evaluate the fluid mobility of tight sandstone reservoirs and systematically elucidate its main controlling factors. The results showed that the PTS could be divided into four types (I, II, III, and IV), which showed gradual decreases in average pore-throat radius ( R a ), continuous increases in the total fractal dimension ( D t ), and successive deterioration of reservoir fluid mobility and percolation capacity. Moreover, the full PSD (0.001–10 μm) showed unimodal and multi-fractal characteristics. According to the Swanson parameter ( r apex ), the reservoir space types can be divided into small and large pore-throat and the corresponding fractal dimension has a relationship where D 1 < D 2 . Large pore-throat had higher permeability contribution and pore-throat heterogeneity but a lower development degree and MFEP than small pore-throat, which had a relatively uniform and regular PSD and represented the primary location of movable fluids. Moreover, the development degree and heterogeneity of small pore throat controlled the flowability of reservoir fluids. MFEP can overcome the constraints of tiny throats and clay minerals on movable fluid, quantify the movable fluid content occupying the effective reservoir space, and accurately evaluate the reservoir fluid mobility. The combination and development of various pore-throat sizes and types in tight sandstone reservoirs results in different PTS characteristics, whereas differences in the mineral composition and content of reservoirs aggravate PTS heterogeneity, which is the main factor controlling the fluid mobility.

Shale gas development requires the use of hydraulic fracturing, and the relationship between fracturing fluid drainage and production is not clear. Therefore, it is necessary to adopt the method of core experiment combined with engineering validation to achieve the description of the seepage-absorption-return mechanism of shale and to optimize the selection of fracturing fluids and the testing work system in engineering. In this study, a “seepage experiment → sampling test → engineering validation” working procedure is proposed, and it is found that seepage occurs only on the surface of the fracture where the liquid medium intrudes into the fracture and that the amount of water absorbed is directly proportional to the area of seepage; the rate of return is inversely proportional to the production rate in the same secondary tectonic unit; and the absorption rate per unit area of four types of cores with the same surface area is directly proportional to the yield of the fractured shale in the same medium. Under the premise of the same medium, the water absorption per unit area of the four types of cores varies with the rate of change with time, but the general trend is the same. Under the premise of different secondary tectonic units, when the time of good closure is similar, the correlation between the return rate and the test production is weak.

As an ecologically fragile plateau and major water source in Asia, the Tibetan Plateau (TP) has grown warmer over recent decades, contributing to frequent occurrence of extreme climate events. It is urgently needed to find a suitable option to mitigate climate change impacts in the TP. The marine cloud brightening (MCB) scheme is proposed to mitigate global warming through the increasing cloud droplet number concentration of low marine clouds to reflect some solar radiation back into space. Until now, impacts of MCB scheme on the TP have not been investigated. In this study, we utilized 13 Expert Team on Climate Change Detection and Indices to assess the evolution of climate extremes over the TP with/without MCB implementation. We found that although the MCB is implemented over ocean only, it would cause significant changes on climate extremes in the TP which is very far from oceans and much higher than sea level. During 2030–2059, MCB implementation can decrease warm temperature extremes, leading to a significant decrease in the TXx index by 6–18°C, the TX90p index by 15–45 days, and the TN90p index by 15–50 days. MCB implementation would also have some cooling effects on cold temperature extremes, leading to an increase in the ID index by 30–80 days, the TX10p index by 22–32 days, and the TN10p index by about 12 days and a decrease in the TNn index by 0.5–1.5°C. Although MCB implementation would not have much impacts on precipitation extremes, it would significantly increase the area of the region with <10% drought frequency, and increase the drought intensity in the west of Lhasa city.

The economic and ecological implications of infrastructural development in the west coast of Taiwan Strait are critically important for both financial stakeholders and policymakers. This study explores the intricate balance between economic development and ecological sustainability in Yueqing, located on the Western Taiwan Strait. Leveraging remote sensing data for fiscal years 2005, 2010, 2015, and 2020, the analysis reveals stable land use patterns. The data shows that between 2005 and 2020, the predominant land use categories in Yueqing were forestry and agricultural assets, making up 53.30%, 52.81%, 52.85%, and 52.42% of the total study area, respectively. Both asset classes demonstrated an upward trend, contrasting with the diminishing trends observed in grasslands, aquatic zones, and areas allocated for construction. To address the challenges posed by population pressure and limited land resources, the Yueqing government has implemented policies like the “Implementation Measures for Yueqing’s Farmland Protection and Compensation” in 2016 and the “Land Greening Action Plan” in 2020. These policies have effectively managed land transitions and contributed to sustainable development.

In the deep rock excavation process, the rock will produce deformation and damage under multiple dynamic disturbances, while there is also unrecoverable time-dependent deformation. In order to research this deformation characteristic, a sine wave disturbance triaxial loading test was carried out on red sandstone to simulate the failure process of deep underground rock mass under dynamic disturbance loads with low confining pressure. Based on the results that the deformation of the rock increases suddenly during dynamic disturbances and varies with the number of disturbances, a novel disturbance damage model relating the number of disturbances to the deformation of the disturbances is created to describe the deformation and damage accumulation of the rock under multiple disturbances and an operator is developed to ensure that the model works. In order to describe the time-dependent deformation of rocks, the elasticity model in the traditional Bingham model was improved to a nonlinear elasticity model that varies with time, and its viscous and plasticity models were retained. The time-dependent deformation and damage constitutive model is obtained by combining the improved Bingham model with the disturbance damage model. The model parameters were identified according to the test data, and the finite-element calculation of the model was realized with the secondary development program. The results show the strain of rock increases suddenly under multiple disturbances, and the main reason for rock damage is the action of dynamic disturbances. The fitted curves and finite-element results are consistent with the experimental results. The time-dependent deformation and damage constitutive model of rock not only reflects the decaying rheological and steady-state rheological properties of rock under static loading but describes the characteristics of strain surge and disturbance damage accumulation caused by dynamic disturbances. This article contributes to the characteristics of the deformation of deep rock mass.

The spatial form of the rural ecological landscape and the vulnerability of the water ecological environment are evaluated to understand the status of the rural ecological system and provide a scientific basis for improving and protecting the rural ecological environment. With the acceleration of the urbanization process, rural areas in urban fringe areas have become an important carrier of urban space expansion and function allocation due to their advantages in transportation and resources, and have been included in the urban production and consumption system. The fast change in country capabilities and the consistent change in land use structure show a differentiated and enthusiastic improvement pattern. According to the point of view of provincial rejuvenation and new urbanization, this study discussed about the time-space qualities of provincial change and land use change, examined the coupling connection between rustic change and land use change, and set forward commonsense country improvement procedures and land guideline measures, which can not only stimulate the vitality of rural development but also consolidate the foundation of rural revitalization. Through the investigation and analysis of rural ecological land, it was found that the rural ecological land decreased from 95.14 to 89.84% from 2015 to 2019, then rose to 92.94%, and finally fell back to 91.74%, which is relatively stable on the whole. It can be seen that the spatial form, coupling, and coordination of the water ecological environment in rural ecological landscape presents a stable trend.

Leucogranites of Kalebalta in Central Anatolia are composed of plagioclase, quartz, orthoclase, and biotite and contains mafic microgranular enclaves (MME) in sizes ranging from few cm to 70 cm. In the total alkali-silica diagram, they fall typically in the granite field and show a calc-alkaline nature in the alkalis-iron-magnesium diagram whereas enclaves are Medium K series calc-alkaline, which represents the transition from tholeiitic to calc-alkaline. Leucogranites which have A/CNK (mol%) > 1 are strong peraluminous and seen as the products of magma derived from a metasedimentary source. Signs of magma mixing expressing the mantle inputs are also observed in many bivariation diagrams. Zircon and apatite saturation temperatures calculated on the basis of whole rock chemistry are 744–829°C for leucogranites and 761–832°C for their enclaves. According to the Raman spectra, biotite and plagioclase minerals in leucogranites and their enclaves show similar Raman spectrums. The biotite minerals have Mg–O and/or Fe–O translational (transformation) bonds between 182 and 552 cm −1 , Si–O–Si bending between 552 and 1,100 cm −1 and Si–O–Si vibrational bonds between 1,100 and 1,200 cm −1 . The results of this study suggest that the leucogranites and enclaves are most probably derived from different magmas. In addition, according to geochemical and spectroscopic data, they may also have fractional crystallization, which is effective after the mixing process.

Producing accurate spatial data with stereo photogrammetric techniques is a challenging task, and the central projection of the space needs to be defined as closely as possible to its real form in each image taken for the relevant production. Interior camera parameters that define the exact imaging geometry of the camera and the exterior orientation parameters that locate and rotate the imaging directions in a coordinate system have to be known accurately for this correct definition. All distortions sourcing from lens and sensor planes and their recording geometry are significant as they are not suitable for detection with manual measurements. It is of vital importance to clearly understand the camera self-calibration concept with respect to the lens and the sensor plane geometry and include every possible distortion source as an unknown parameter in the calibration adjustments as they are all modellable systematic errors. In this study, possible distortion sources and self-calibration adjustments are explained in detail with a recently developed visualization software. The distortion sources investigated in the study are radial, tangential, differential scale, and axial skewing distortion. Thanks to the developed software, image center point, distorted grids, undistorted grids, and principal points were visualized. As a result, the most important element of obtaining accurate and precise photogrammetric productions is the correct definition of the central projection of the space for each image, and therefore, the study explains an accurate and robust procedure with the correct definition and use of correct camera internal parameters.

Dolines are depressions in the soluble ground that indicates the degree of karstification. They may also act as connection points (vulnerability spots) between the surface and underground for the transmission of runoff, sediments, and pollutants. The delineation of these spots (dolines) is a crucial step in environmental management through land use planning to protect the karst underground, which is rich in flora and fauna. This requirement can benefit from a cost-effective, accessible, and non-invasion high-resolution investigation generating digital elevation models (DEMs) from unmanned aerial vehicle (UAV) imagery and automated object detection techniques. This study examines the capabilities of UAV-based DEM in detecting dolines across 50 km 2 in the environmentally protected area of river Vermelho (APANRV – Área de Proteção Ambiental das Nascentes do Rio Vermelho). Initially, an automatic objects (doline and no-doline) detection algorithm was applied to the DEM, followed by a visual inspection to differentiate doline from possible dolines in orthomosaic photos, topographic profiles, and shaded UAV-based relief (digital terrain model; DTM and DSM). For the redundancy checking, a cluster analysis with four tests was conducted. The objects generated from the best clusters and morphological analysis were gathered in the same base for visual inspection. Out of a total of 933 objects identified, 41% were obtained from the DSM base, 25% from the perimeter-to-area ratio, and 34% through convergence between the two-analyses. Subsequently, the resulting doline typologies are discussed in reference to their proximity to hydrogeological features and their impacts on underground vulnerability. The findings aligned with the previous research as dolines were highly concentrated near sites where carbonates come in contact with siliciclastic sediments.

In response to the problems of lack of planning in management and high difficulty in law enforcement in urban and rural planning (URP for short here) and construction, this article proposes to apply the concept of low-carbon ecology (LCE) to URP and construction and reasonably optimize URP and construction. This article provided a relevant analysis of urban and rural energy planning issues and applied the concept of LCE to URP and construction. This article constructed a framework for evaluating urban and rural carbon emissions, which is used to evaluate carbon emissions issues in URP and construction. This article also combines artificial neural network algorithms to further conduct experimental analysis on the scale of URP and construction land. In contrast, during the same period, the construction land scale of our algorithm increased by 179,800 acres less than that of the machine learning algorithm. The per capita area of urban and rural construction land decreased by 16.5 m 2 , and the gross domestic product (GDP) output of urban and rural construction land increased by 1.95 billion yuan. The algorithm in this article has increased by 155,200 acres compared to the construction land scale under deep learning. The per capita area of urban and rural construction land decreased by 7.1 m 2 , and the GDP output of urban and rural construction land increased by 915 million yuan. In summary, this algorithm can effectively increase the GDP output of urban and rural construction land, slow down the expansion of construction land scale, and play a good auxiliary role in URP and construction.

Gravity measurement is a basic geophysical method for non-destructive exploration of mineral resources and hydrocarbons and also for geological studies. The quality of gravity data measured is constantly degraded by a low signal-to-noise ratio. Noise attenuation thus plays a vital role in processing and interpreting gravity field data. The non-local means (NLM) filtering was first and successfully introduced to attenuate randomly distributed noise situated in seismic records in geophysical community. However, less attention has been drawn to apply NLM to denoise potential field data, since the success of NLM is guaranteed by carefully tuned parameters and large computational costs. Here we propose the modified NLM (MNLM), based on unweighted Euclidean distance and integral image method, to denoise gravity datasets. The unweighted Euclidean distance is used to reduce the uncertainty and complexity of tuning the control parameters involved, and the integral image strategy is applied to avoid the enormous computational cost of the NLM. Since these filtering properties are desirable to mitigate noise in gravity datasets, we test and evaluate the MNLM filter on noisy synthetic gravity models with uniform and normal distributions and on real data from the Mariana trench and Slovakia, and compare it to other standard and representative denoising filters. The results on synthetic and field datasets confirm the high speed of this modified algorithm and show that, it removes noise most effectively while clearly preserving and not blurring structural details with less tuned parameters. The MNLM filter can therefore be considered as a promising and novel algorithm for denoising gravity data.

As people’s living standards improve, tourism has become an important way for people to spend their time on leisure and entertainment. The growing number of tourists in recent years has given rise to the creation of tourism-related ancillary services. Travelers need to choose a travel route that suits their needs and expectations and do it in a way that does not cause a waste of time, whether it is an emerging self-driving tour or a traditional tour group. Therefore, the optimization of tourist routes is of great significance to the majority of tourists. Given the planning requirements of tourist attractions in the post-epidemic era, an ant colony-based optimization algorithm is proposed to resolve the planning problem of optimal tourist routes. An optimized pheromone update strategy is also proposed based on the basic ant colony optimization algorithm. The optimized ant colony algorithm tries to balance two conflicting concepts, namely, flows into tourist attractions and the carrying capacity of destinations. To analyze the performance of the proposed optimization algorithm, the effects of different optimization algorithms on the route planning of tourist attractions were compared in the experiment, and the acceleration ratio of the optimized ant colony algorithm was tested using the graphics processing unit parallel computing program. The results show that the proposed algorithm provides certain advantages and has certain potential in parallel computing. To sum up, this study provides a better scientific basis for optimal tourist route planning and has a good reference value.

Normalized difference vegetation index (NDVI) is a conditioning factor that significantly affects slope stabilization, as the low vegetation coverage can create conducive conditions for landslide occurrence. In previous studies, NDVI was often calculated from long-term average NDVI maps or specific yearly NDVI maps. However, this approach is unsuitable due to the time-varying nature of these data, influenced by numerous factors, including human activities. To solve this problem, this study uses NDVI as a time-varying factor. NDVI maps are generated from Sentinel 2 and Landsat_8 imagery at the onset of each rainy season between 2015 and 2020 in the mountainous region of Quang Ngai Province. Moreover, the landslide events that occurred within this 5-year period (2016–2020), along with a set of conditioning factors, are utilized to develop landslide susceptibility models based on three algorithms: logistic regression, support vector machine, and extreme gradient boosting (XGBoost). The obtained results demonstrate that using time-varying NDVI shows superior performance compared to using only NDVI from 2015. The outcomes also indicate that XGBoost is the most effective model. Selecting suitable NDVI maps can improve the predictive accuracy of landslide susceptibility mapping.

Multiple uplifts of the Qinghai-Tibet Plateau since the late Cenozoic have generated large effects on the geomorphology and environment over Asia. However, how the basin responded to the uplifted Tibetan Plateau remains unknown. Here, we examined the digital geomorphology of the Bahe River basin, the greatest first-order tributary in the southern Weihe River basin. The geomorphogenesis of the watershed, the far-field effects, and the long-range consequences of the elevation from the Tibetan Plateau were thoroughly discussed. We found that there were five layers of terraces, which were mainly controlled by tectonic activity. The geomorphological characteristics suggested that Bahe basin was influenced by a severe tectonic activity prime, with intense river erosion. The Lishan-North Qinling Mountains uplift, facilitated by the horizontal expansion of the northern Qinghai-Tibet Plateau, was also responsible for the development of the Bahe River basin.

Currently, information processing of tunnel engineering has mainly adopted conventional mathematical statistics-based methods. Moreover, some nonlinear processing methods are implemented to derive more insights, even though the degree of research is not deep enough. In the research, the rock mechanics test is carried out by drilling a method and taking samples in situ according to the construction technology of tunnels in complex geological conditions and implementing computer information-based methods. Also, rock mechanics tests are carried out in the excavation test area of the flat tunnel. Based on the tests using physical properties, such as deformation, tensile, uniaxial compression, triaxial compression, and longitudinal wave velocity, the physical and mechanical characteristics of the surrounding rock in the tunnel area are comprehensively evaluated, and the stability of the tunnel rock mass is assessed to devise convenient conditions for the subsequent research of the complex geological tunnels based on green excavation. The particle density of sandy mudstone, the bulk density, the porosity, and the natural water content are represented by 2.67 ± 0.61 g/cm 3 , 2.56 ± 1.42 g/cm 3 , 7.45%, and 2.86%, respectively, in terms of physical characteristics. These indicate that the sandy mudstone structure is relatively loose, with relatively large pores, micro-fractures, and a high degree of natural water content. The representative deformation test curve of the rock block shows that the ratio of deformation modulus to the compressive strength of the rock block is 650 on average, and Poisson’s ratio ranges from 0.21 to 0.38. These show that sandy mudstone has deformation properties after compression. The tensile strength of sandy mudstone, the shear strength, and c are represented by 1.25 ± 0.23 MPa, f = 1.32, and = 2.35 MPa, respectively. The stated test results can provide a scientific basis for selecting engineering design and its construction parameters in similar areas. In addition, the measurement results show that the surrounding rock will gradually increase, and the tunnel space will gradually become shorter with the increase of buried depth when the gravity stress field occurs. The linear elastic displacement of soft rock is smaller than that of elastic–plastic analysis, and the deeper the tunnel is buried, the larger the displacement difference would be. Therefore, establishing a stable and orderly monitoring and detection system could fully understand the intrinsic law between surrounding rock stress release and surrounding rock pressure and obtain accurate monitoring and measured data to evaluate the grading management standard of a tunnel at the ultimate displacement. In a word, this research provides a feasible idea to study the decision process of green excavation and deformation control technology of tunnels in complex strata.

This article presents an in-depth analysis of the spatial and temporal evolutionary characteristics of the environmental protection industry in Jiangsu Province and analyzes the dynamics of changes in the spatial pattern of the environmental protection industry as a whole using spatial visualization methods. Attribute data of environmental protection enterprises in Jiangsu Province from 2000 to 2022 were selected for this article, with spatial analysis methods. From 2000 to 2005, the industry expanded to include Suzhou, Changzhou, and other areas, forming a multi-core pattern, supported by a Moran’s I value of −0.049837. This clustering trend continued from 2006 to 2010, with Moran’s I values of −0.115285 in 2011–2015 and −0.117398 in 2016–2022. By 2022, new clusters emerged in the coastal areas of Xuzhou, Yancheng, and Nantong, reflecting industry growth. By detecting with multiple factors, it is found that such pattern evolution is a result of a combination of factors, which is mainly influenced by environmental and employment factors in the early stages of development, while also significantly driven by market factors in the later stages of development as the dynamics of the spatial pattern continue to evolve with the economy.

The risk of flooding is a destructive natural hazard, and it is increasing due to heavy rainfall and anthropogenic factors. Hydrologic–hydraulic models serve as valuable tools for flood forecasting and predicting future flow patterns. These models evaluate and simplify processes in ungauged basins. In this study, three hydrologic models (soil conservation service [SCS], Snyder, and Temez) were used to calculate synthetic unit hydrographs for the Humaya and Tamazula River (H-T-R) basin. Additionally, the flows derived from the three models were simulated in Hydrological Engineering Center River Analysis System for various return periods (2, 5, 10, 25, 50, and 100 years). The accuracy of the models SCS, Snyder, and Temez was evaluated using the root-mean-square error (1162.44, 144.76, and 2890.6); Nash–Sutcliffe efficiency (−51.12, 0.19, and −312.28); R 2 (0.97, 0.94, and 0.94), and kappa index (0.8534, 0.9895, and 0.7155), respectively. The data used in this study were obtained from a hydrometric station located on the Culiacan River. The main findings indicate that the Snyder model demonstrated a better predictive capability compared to the Temez and SCS models, albeit with a tendency to overestimate. Simulated flood depths are deeper in the upstream areas, particularly upstream from the Musala Island bifurcation on the Tamazula River, with values of 11.82 m for SCS, 9.76 m for Snyder, and 13.5 m for Temez. The simulation revealed potential overflow zones along the Tamazula River, particularly at the channel bifurcation and near the confluence with the Humaya River, during the 100 year return period simulation. Graphical abstract

This article focuses on studying the spatial distribution and evolution of the aquaculture industry in Jiangsu, a significant coastal province in China, within the context of the blue transformation. By collecting spatial data on the aquaculture industry and using ArcGIS software, this article analyses the characteristics of spatial changes and the driving forces behind them in Jiangsu’s aquaculture industry while providing predictions for future pattern evolution. The findings reveal that the overall distribution of the aquaculture industry in Jiangsu Province exhibits strong directionality but weak density, primarily oriented in the northwest–southeast direction. There is an evident trend of the industry shifting from the northern to the western regions and from the central to the northwest areas of the province. This indicates that initially, the aquaculture industry was primarily concentrated in the inland regions, while marine aquaculture gradually influenced the industry structure after 2010. Although the aquaculture industry shows signs of diversification, industry agglomeration is only observed in approximately 30.8% of the cities that exhibit a positive spatial correlation, which is a relatively small proportion compared to the total number of cities. However, despite the overall negative correlation in spatial distribution, the absolute difference between Moran’s I of all cities and zero is less than 0.4. This suggests that the spatial differences are not significant, regardless of the spatial autocorrelation characteristics of the overall distribution of a city. Based on the findings, this article recommends the urgent need for the development of policies that promote industry agglomeration in order to achieve effective regulation and pollution control in aquaculture.

Applying community detection algorithms in spatial interaction networks constructed from modern human communication records is an essential means of evaluating urban territorial subdivisions. Previous studies have usually involved qualitative rather than quantitative interpretations of community detection results. This article proposes a method of quantitatively and qualitatively interpreting community partition results by map overlaying the spatial regions corresponding to the detected communities with the related geographical features and by calculating the distribution of the geographical features contained in the regions and the entropy value of each distribution. The interpretation of the communities detected from the spatial interaction networks is carried out from the perspective of multi-temporal and multi-spatial scales and multi-geographical features. Extensive experiments were conducted with Milan, Italy, as the study area. The spatial interaction records reflected by telephone calls, land use, and point of interest (POI) data were used as the experimental data. Experimental results demonstrated the effectiveness of our method, and the specific results include: (1) Qualitative interpretation of multi-spatial resolution scale communities detected from the long-term aggregated spatial interaction network. The cohesiveness, homogeneity, and heterogeneity of the detected communities were qualitatively interpreted by the spatial distribution patterns of the land use dataset and the POI dataset. (2) Quantitative interpretation of multi-spatial resolution scale communities detected from the long-term aggregated spatial interaction network. The low spatial resolution scale community partitions and the high spatial resolution scale community partitions were interpreted through the statistical distribution of the land use dataset and the POI dataset, respectively. (3) Qualitative interpretation of the stable and active regions discovered from the community time series. Regardless of the community partitions’ spatial resolution scales, the stable and active regions were distinguished with the statistical distributions of the land use dataset and the POI dataset.

Soil nailing reinforces soil slopes and retaining walls by installing reinforcing elements into the soil, which rely on bonding strength with surrounding soil to transfer axial forces. This study focuses on the pullout capacity evaluation of grouted soil-nailing, which is conventionally determined through costly and time-intensive site-specific field pullout tests or simplified design methods, Federal Highway Administration (FHWA), and Effective Stress Method (ESM). However, these methods neglect important soil nail configuration parameters governing the pullout capacity. To address this limitation, we present a parametric study on a validated Finite-Element model using PLAXIS 3D to comprehensively investigate the pullout characteristics of grouted soil nailing. The study considers various factors such as sand relative densities, lengths, diameters, and inclination angles of the soil nails. The results reveal that the pullout capacity is significantly influenced by the sand relative density, diameter, and the length of the nailing, while the angle of inclination has only a marginal effect. The comparison with FHWA and ESM methods shows significant scatter, attributed to their lack of consideration for these governing parameters in determining pullout capacity. These findings provide valuable insights into the design and optimization of grouted soil nailing pullout capacity for geotechnical applications.

In the present research, a statistical analysis of all pollution incidents occurring from 2015 to 2019 in the cities of the urban agglomeration centered on Shenyang was performed. The results indicated that heavy pollution mainly occurred during the heating season, and the main pollutants were (particulate matter) PM 2.5 and PM 10 . It was also determined that the heavy pollution that occurred during the heating season in Shenyang was of the soot type. The weather research forecast-chemistry (WRF-Chem) was used to simulate the meteorological elements and particle concentration during the two heavy pollution periods in 2019 and compared the simulation data with the monitoring data to verify the simulation performance of the model. Results demonstrated that the model had a better simulation effect on temperature and pressure than on wind speed and wind direction. By comparing the hourly particle concentration data, it was found that the simulation results for pollutants obtained with the WRF-Chem model were lower than the measured values. The simulation effect on PM 2.5 was better than that on PM 10 , and the simulation results were basically consistent in the high- and low-value areas, and the time of peak and valley was basically synchronous. It was proven that the selected parameterization scheme properly simulated the weather situation and changes in pollutants during heavy pollution events in the Shenyang area. These results verified the application value of the WRF-Chem model during the investigation of heavy pollution events.

Slope instability has been identified as one of the most natural and man-made disasters that can lead to the life of humans in danger and enormous loss of capital. The roads which pass on the hilly and mountainous terrains are frequently affected by slope failures since hilly and mountainous areas are characterized by variable topographical, geological, hydrological, and land-use conditions. Slope stability analysis was carried out using FEM (plaxis 2D) and LEM (slide software). The stability analysis covers both static and dynamic (in pseudo-static analysis) loading conditions on soil and rock material along selected critical slope sections. Two soil-critical slope sections and two rock-critical slope sections are analyzed in this study. The strength reduction method and method of the slice with Mohr–Coulomb model were used in FEM and LEM, respectively. The slope stability analysis was carried out for both dry and wet states of the soil and rock material along the critical slope sections (i.e., static dry, dynamic dry, static wet, and dynamic wet). The analysis result shows that the total displacement of the slope along soil critical slope section one is (0.58703, 0.58755, 2.35, and 2.38 m), along soil critical slope section two is (0.6574, 0.6621, 1.2841, and 1.2872 m), along rock-critical slope section one is (4.8624, 4.8672, 17.8463, and 17.8512 m) and total displacement along rock-critical slope section two is (3.8365, 3.8391, 11.437, and 11.6275 m) during static dry, dynamic dry, static wet, and dynamic wet loading conditions, respectively. In general, the result shows soil critical slope sections one and two are stable in dry conditions and unstable in wet conditions. Rock-critical slope sections are stable during the dry and wet states of the slope.

Forests offer high potential for the fight against climate change. However, forests are faced with increased deforestation. REDD+ is a financial mechanism that offers hope to developing countries for tackling deforestation. Aboveground (AGB) estimation, however, is necessary for such financial mechanisms. Remote sensing methods offer various advantages for AGB estimation. A study, therefore, was conducted for the estimation of AGB using a combination of remote sensing Sentinel-1 (S1) and Sentinel-2 (S2) satellite data and field inventorying. The mean AGB for Sub-tropical Chir Pine Forest was recorded as 146.73 ± 65.11 Mg ha −1 , while for Sub-tropical Broadleaved Evergreen Forest it was 33.77 ± 51.63 Mg ha −1 . Results revealed weak associations between the S1 and S2 data with the AGB. Nonetheless, S1 and S2 offer advantages such as free data resources that can be utilized by developing countries for forest biomass and carbon monitoring.

The Mongolia-Okhotsk tectonic regime had a significant impact on the tectonic evolution of Northeastern (NE) China. However, there is no consensus on the role of this regime in the geological evolution of the Xing’an Massif during the late Mesozoic. This article presents the results of zircon U–Pb geochronology, whole-rock major and trace-element geochemistry, and zircon Hf isotopic compositions for granites in the Haobugao area of the southern Great Xing’an Range, NE China, to determine their petrogenesis, source, and tectonic setting. The zircon U–Pb ages indicate that the granites crystallized at 152.7 ± 0.5 Ma. The granites exhibit high SiO 2 (70.75–73.19 wt%) and K 2 O + Na 2 O (8.00–8.65 wt%) contents and extremely low MgO (0.40–0.59 wt%) and TiO 2 (0.24–0.33 wt%) contents. They belong to the metaluminous, high-K calc-alkaline, and ferroan series, with mostly right-inclined REE curves, flat heavy rare earth element patterns, high 10,000 Ga/Al ratios, and intensely negative Eu anomalies. The Zr/Hf ratios are 24.2–27.7, Nb/Ta ratios are 6.4–8.9, and Y/NbN ratios are >1.2. These characteristics suggest an A 2 -type granite affinity. The zircon εHf values of the rocks range from +5.62 to +9.12, corresponding to T DM2 values of 621–906 Ma, indicating that juvenile materials in the Neoproterozoic may be a source of these granites. Geochemically, these Late Jurassic A 2 -type granites are similar to those from post-collision extension settings. The primary magma was likely derived from the partial melting of a delaminated region of the lower crust.

The petrogenesis of Sukadana Basalt remains an enigma till present. Major and trace element data are analyzed from Sukadana Basalt lava, located at East Lampung, Sumatra, to study the processes involved in the petrogenesis of the erupted magmas and the origin of mantle source compositions. The Sukadana Basalt display SiO 2 (48.1–52.5 wt%), MgO (5.3–9.3 wt%), TiO 2 (1.3–2.6 wt%), P 2 O 5 (0.2–0.6 wt%), and Fe 2 O 3 T (8.9–11.3 wt%) contents. The Sukadana Basalt enriched in light rare earth elements with weak negative Eu anomalies (Eu/Eu* = 0.8–1) and show Ocean Island Basalt (OIB)-like characteristics. There are two different petrogenesis groups, namely group A and group B. Group A samples show enrichment of Hf, Pb, K, and Sr and depletion of Nb. Group B samples show enrichment of K, Sr, and depletion of Pb. These differences are closely related to the mechanism of slab roll-back and normal fault activity. This study shows that Sukadana Basalt has Nb = 7.4–29.8 ppm, Nb/U = 18–060.3, and Nb/La = 0.8–1.6. These characteristics were similar to those found in typical Nb-enriched basalts. Geochemical analyses suggest that the Sukadana Basalt have experienced minimal crustal contamination and Olivine plagioclase, clinopyroxene, and magnetite fractional crystallization. The chemical features, together with high incompatible-element ratios, are consistent with low degrees of partial melting of a dominantly a partial melting of garnet–peridotite mantle source. The trace-element patterns suggest a mantle source influenced by an enriched component. The occurrence of OIB-like basalt suggests significant upwelling of the asthenosphere in response to slab roll-back. These processes occured in the above of a Paleo Indo-Australia subducting N–S beneath the southern part of Sumatra. Graphical abstract

As a new type of foundation, the nodular diaphragm wall (N-D wall) has large transverse stiffness and high bearing capacity, with low noise and low vibration, which is suitable for high-rise buildings in cities with limited land area. The reduction coefficient of each load composition under the same displacement conditions and the ABAQUS finite element numerical analysis software are introduced to analyze the group effect of N-D wall foundations. The results show that the compressive group wall effect coefficient is greater than 1, while the uplift group wall effect coefficient is less than 1. Under the same displacement condition, the group effect of the compressive wall is more obvious than that of the uplift wall, and the group effect of the middle wall is more obvious than that of the sidewall. The wall group effect gradually develops downward with the increase in displacement. The ultimate compressive capacity is mainly controlled by the friction resistance, which is especially obvious in the sidewall. The cap resistance load-sharing ratio decreases first and then increases with the settlement. The cap resistance is not evenly distributed, the stress at the corner is the lowest, and the stress is mainly concentrated in the middle. The influence of wall spacing, length, and width on the uplift bearing capacity is highly significant, while the influence of nodular part angle is slightly significant. The influence of wall width, length, and spacing on compressive bearing capacity is highly significant, while the influence of nodular part angle is weak. The influence of nodular part angle on the uplift bearing capacity of group wall foundation is stronger than that of the compressive bearing capacity.

Purpose With population growth and economic development, global Water Resources (WR) are becoming increasingly scarce. As an important consumer sector, the tourism industry is increasingly consuming and polluting WR. How to reasonably utilize WR and protect the water environment has become an important issue for the sustainable development of the current tourism industry. Methods Based on the Water Footprint of WR utilization and tourism environment assessment, this article used four different WR management schemes in different tourist areas to compare with the traditional scheme. Result According to the experimental results, it could be concluded that the wastewater discharge and environmental risk index under low Water Consumption technology in a certain mountainous tourist attraction were approximately 90,000   m 3 and 0.25, respectively; the wastewater discharge and environmental risk index of a certain tourist city using renewable water technology were approximately 600,000   m 3 and 0.5, respectively. The impact of adopting different WR management schemes in different regions has also varied. Conclusion This also indicated that when formulating WR management plans for various tourist areas, it was necessary to fully consider the impact of the tourism environment and develop scientific and reasonable management measures. The research in this article has broad application prospects in practice, which helped to promote sustainable economic development and progress in social civilization.

The increasing demand for energy and global commitment to reduce CO 2 emissions to mitigate climate change has spurred countries to pursue unconventional hydrocarbon generation for power production. The investigation of the carbonaceous shale from the Permian Mikambeni Formation of the Tuli Basin in South Africa aims to assess the potential for gas generation. The Rock-Eval 6 pyrolysis of the studied samples shows total organic carbon (TOC) content ranging from 10.10 to 37.61 wt%, indicating an excellent source rock quality since it exceeds the threshold limit of 5 wt%. The produced gas that emanated from the thermal breakup of remaining hydrocarbon (S2) ranged from 14.30 to 65.55 mg HC/g rock while the hydrogen index (HI) ranged from 56.55 to 198.22 mg/g TOC. The plot of the HI against T max indicates the predominance of type-III kerogen, prone to gas generation. The thermal maturity parameters, T max (430–466°C), and vitrinite reflectance, VRo (0.6–1.2), showed a matured organic material. The production index value (0.06) of the samples indicates a moderately mature source generating a biogenic gas. The carbon isotopic composition, δ 13 C (−20.0 to −23.4‰), indicates a predominant influx of organic matter derived from a vascular higher plant. The studied samples showed relatively depleted values of oxygen isotopic composition δ 16 O (14.1–18.8‰), suggesting a brackish water depositional environment. Additionally, the Ba concentration (303.15–331.27 ppm) exceeds the 200 ppm threshold for the marine environment, indicating a non-marine environment characterised by low marine paleo-productivity and high detrital influx. Based on the evaluation, the studied coaly-shale is found with a matured and type-III kerogen that is prone to gas generation in a fluvial, paleo-depositional environment.

In Cameroon, the drying up of wells and boreholes during the dry season is characterized by a lack of knowledge about the surface structures of the subsoil and the spatial distribution of groundwater. In this study, we propose to use gravity data to detect and characterize the surface structures of the south-west (SW) Cameroon and to analyze their hydrogeological implications. The application of the normalized standard deviation method on the data obtained from the stable downward continuation of the Bouguer anomalies led to the detection of 71 lineaments that characterize the tectonic events of the study area. The statistical analysis of the lineament directions shows that the near-surface structures were mainly affected by a tectonic of direction east–west followed by that oriented SW-north-west. These two directions are consistent with the megastructures in the region like the Ngoro-Belabo Shear Zone and the Sanaga Fault stretching from the Gulf of Guinea to the Central African Republic. In addition, the application of the Euler deconvolution method permits us to evaluate the interval in which lies the depth of each lineament hosting Euler solutions. The analyses showed that 12 lineaments, whose roof depths are between zero and 250 m, are very favorable for hydrogeological prospecting.

Identifying the classification of tourism landscape resources and accurately studying their spatial pattern are of great significance to the ecological environment protection, industrial transformation, and economic growth of the Yangtze River Economic Belt. Taking Zixi County of Jiangxi Province as the research area, based on field survey and network collection, the scientific statistical classification of tourism landscape resources data in the county is conducted, and the nearest neighbor index, nuclear density analysis, average passage time, and accessibility coefficient are used to quantitatively analyze the classification, spatial agglomeration, spatial structure pattern, and spatial correlation of tourism landscape resources. The results show that: (1) Zixi County tourism landscape is complete in terms of natural resources, physical resources, and humanistic resources; (2) the spatial agglomeration analysis of tourism landscape resources in Zixi County shows an overall agglomeration distribution trend; (3) the density of tourism landscape resources varies significantly, with the spatial distribution characteristics of “large concentration at the nucleus and small dispersion at the poles”; and (4) landscape resources are well correlated, with a “strong center – weak periphery” spatial pattern. Accordingly, it is proposed that protection and development should be given equal importance, strengthening advantages, making up for shortcomings, and accelerating the development of tourism industry and economic growth, and promote the high quality and green development of the Yangtze River Economic Belt with points and lines, and help the coordinated development of the Yangtze River Economic Belt.

In this study, an aggregate quarry was investigated in order to understand the impact of weathering phenomenon on the drillability of dolomite stones, respectively. Samples were collected from the study area and analyzed in terms of physicomechanical tests (specific gravity, dry unit weight, uniaxial compressive strength, point load index (Is50), and Brazillian tensile strength). The drillability of the rocks was investigated using the drilling rate index method. Based on the analysis results, significant relationships were obtained between physicomechanical properties and drillability of dolomites at different weathering grades. Initial evaluations can be interpreted as an increase in the weathering degree would result in an increase in drillability. This understanding of weathering's impact on drillability is actually the main purpose of this study. This article could be a tool as regards initial evaluations of the drillability of dolomites combined with the weathering mechanism, since successful evaluations and meaningful relations were achieved.

Near-surface velocity variations are the main cause of seismic scattering in exploration seismology. Many studies create the near-surface heterogeneity as velocity models that have random velocity distribution, random objects, or irregular subsurface topography to study and mitigate the resultant scattering effects of the near-surface layer. Von Kármán (self-similar) method is a known method in the literatures for modeling heterogeneous earth in a statistical way. This research modifies the self-similar method, and throughout the work, it has proven that the self-similar provides a robust method for generating realistic near-surface velocity models with different spatial velocity distributions. This study creates four-velocity models with simple subsurface layering and structure, three of which include a near-surface layer in three different degrees of velocity heterogeneity. Synthetic acoustic seismic reflections are produced for the four-velocity models to investigate the resultant scattering effects of the near-surface velocity heterogeneity on the quality of seismic waveform coherency. Spectacular negative observations are witnessed of the near-surface layer involvement to the quality of seismic reflection coherency that increases as velocity dramatically varies. Subtracting the scattering noise, which is modeled using an exact heterogeneous model, enhances seismic reflection coherency for the subsurface layers, but waveforms that are affected by scattering must be reconstructed for true amplitude and seismic waveform analysis. Graphical abstract

In order to reduce the resource occupancy and retrieval efficiency of geological drilling databases, this study proposes a distributed horizontal expansion method for query optimization of geological drilling databases by constructing a comprehensive geological data subtree, analyzing the characteristics of distributed databases and elements in geological databases, and quickly retrieving data resources based on element attributes. In addition, this study has designed a method to horizontally extend the database designed for drilling holes using a multi-constraint model in order to achieve extension optimization of the distributed geological drilling database. Experiments are conducted to verify the performance and applicability of the proposed method. The experiment shows that when the geological data capacity is 80 GB, the capacity level of the geological database can be extended to 41 × 105TB using the method proposed in this study. The retrieval efficiency is higher than 89% and the resource occupancy rate is lower than 12% after the horizontal expansion of the database. By using this research method, the horizontal expansion of the geological drilling database is more effective, and can effectively reduce the resource occupancy rate and retrieval efficiency of the geological drilling databases. This has value significance for geological drilling with efficiency improvement and development.

The Miocene tectonics of Papua New Guinea, where subduction, arc-continent collision, and changes in subduction direction are considered to have occurred, is very complex and various tectonic models have been proposed. The Maramuni arc, active in the Miocene, is composed of a chain of granitoid bodies. As the chain-like distribution indicates the generation of igneous activities in a wide range of the same tectonic settings, the study of the Maramuni arc magmatism is important for elucidating the geologic events of the time. We provide data on the petrological and geochemical characteristics of the Morobe Granodiorite that form part of the Maramuni arc. The Morobe Granodiorite consists of metaluminous I-type granitoids, belonging to the medium-K to high-K series. The whole-rock major element variations in the granitoids can be explained by the fractionation of hornblende and plagioclase. They are generally within the composition range of experimental partial melts of amphibolites, and the whole-rock trace element compositions have characteristics of slab failure magma rather than arc. This suggests that the granitoids were generated by partial melting of the torn slab after slab failure. The mafic microgranular enclaves (MMEs) in the granitoids are classified as shoshonite, and their trace element compositions suggest that they were formed by partial melting of phlogopite-bearing mantle. The occurrences of native gold and barite within the MME show that MMEs transport Au from the mantle metasomatized by slab-derived sediment melt and/or fluid to the crustal magma chamber.

Water pollution and protection of water resources have become an urgent task for humanity today and are also important components of environmental risk assessment. In response to the problems of high risk level and low risk credibility in the current environmental health risk assessment of urban water sources, this article aims to use fuzzy set theory to comprehensively evaluate the environmental quality and quickly monitor the safety of urban water sources. Therefore, this article analyzed the health factors of the urban water source environment and then studied the content and uncertainty analysis of health risk assessment. Finally, it constructed a health risk assessment system and proposed corresponding water environment protection strategies. In the experimental section, the risk level and risk credibility of the water environment were analyzed. Through comparison, it was found that the risk level in the new water environment health risk assessment was 0.16 lower than that in the traditional water environment health risk assessment, and the risk credibility was 0.11 higher than that in the traditional water environment health risk assessment. The water quality monitoring effect in the new water environment health risk assessment was 7.3% higher than that in the traditional water environment health risk assessment, The health hazard effect is 8.2% lower than traditional water environment health risk assessment. In summary, water environment health risk assessment plays an important role in protecting the water source environment. Health risk assessment of the water environment helps to reduce water pollution, improve water quality, and ultimately improve human health. Moreover, using fuzzy set theory makes it easier to comprehensively and efficiently evaluate the water environment. The innovation of this article lies in paying attention to the importance of fuzzy set theory in water pollution risk assessment and applying fuzzy technology to water pollution control strategies, to better improve water quality and optimize water source environmental health risk assessment methods.

This article focuses on Shanghai as a case study and utilizes various factors such as points of interest, nighttime lights, land use, road networks, and Digital Elevation Model to examine the spatial distribution of population. A random forest model is constructed to decompose the population of streets in 2022 into a 100-m grid. The study then assesses the spatial accessibility of basic education resources using a cost-weighted distance method and evaluates the supply-demand match of these resources using an improved potential model. The findings reveal the following: (1) At the street level, the spatialization of population distribution achieves a superior fit ( R 2 = 0.7679) with statistical data compared to the WorldPop dataset. The overall population distribution in Shanghai exhibits a spatial pattern characterized by “one main area, two sub-areas, and multiple scattered points,” effectively capturing the distribution characteristics. (2) The overall spatial accessibility of basic education resources in Shanghai is favorable, with 100% of residents able to reach the nearest primary school, junior high school, and high school within a 30-min travel time. However, significant urban–rural disparities are observed, as areas with dense facilities and well-developed transportation exhibit better accessibility. Streets with poorer accessibility tend to be concentrated in larger jurisdictional areas with abundant forests near the sea. (3) The main urban area of Shanghai and the districts of Songjiang and Fengxian demonstrate a relatively balanced supply and demand of basic education resources in several areas. However, there are still regions within these areas where resource allocation could be further strengthened.

This research investigates the dynamic interplay between land use changes and landscape ecological risks in China’s Jiangsu Province, specifically focusing on the Huai River-Gaoyou Lake region. Leveraging multi-temporal remote sensing data from 2000 to 2020, we conducted a comprehensive analysis of shifting land cover patterns and their implications. Employing geostatistical techniques, we developed a landscape ecological risk assessment model to quantify ecological vulnerabilities. Additionally, we conducted a resident satisfaction survey aligned with the “Production–Living–Ecological” framework to gain insights into societal perceptions of land use dynamics. Our findings reveal significant land use shifts driven by urbanization, industrialization, and agricultural modernization. While farmland areas have decreased, water bodies and artificial surfaces have expanded, reflecting societal demands and economic growth. The landscape ecological risk assessment model highlights localized vulnerabilities, emphasizing the intricate relationship between land use changes and ecological risks. The resident satisfaction survey indicates overall contentment with various aspects of land use, especially in terms of residential comfort and transportation convenience. However, ecological concerns underscore the need for a balanced approach to land management that prioritizes ecological sustainability alongside economic development.

Walkaway vertical seismic profiling (WVSP) is known for its high level of credibility in obtaining the relationship between first-arrival traveltime and detector depth through first-arrival picking. This relationship can be utilized for seismic velocity model inversion to improve velocity model accuracy and rationality. Here, we present a WVSP first-arrival velocity model with velocity structure constraints, by utilizing layer and fault data interpreted by ground seismic structure technique. We constructed a geological structure and layer sequence models based on sedimentary patterns to obtain complex velocity structures. Furthermore, we introduced a smooth regularization term based on the velocity structure into the inversion model to enhance its consistency with geological laws and compensate for the reduced inversion accuracy owing to the regularization term based on flat structures. This approach addressed the limitations of the regularization term based on flat structures, resulting in more accurate and reliable inversion results. Through simulation analysis, the proposed method realized the WVSP first-arrival velocity inversion, with results being closer to those of the real velocity model.

The risk factor of the receiving water body is one of the important factors that affect the self-purification ability of the water body. Analyzing the concentration and removal rate of the target substances such as suspended solid (SS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) in the receiving water body during the life cycle can trace the risk factor. Based on this, this article takes a sewage treatment plant and its receiving water body in Nanjing as the research object, sets up five sampling points, and calculates the target concentration and removal rate using the cellular automata-Markov chain Monte Carlo method. Thus, risk assessment of water bodies can be achieved. The results show that: (1) the concentration of the target substance in each process stage has obviously decreased during the life cycle, with an average concentration of 3–18 mg/L; (2) in the life cycle, the highest removal rate of target concentration in each process section can reach 85%; (3) the concentration of target substances SS, COD, TN, TN, TP, and TP at the outlet of the sewage treatment plant is relatively high. Practice has proven that this research method can assess the risk factors of receiving water bodies, so as to improve the scientific, refined and standardized environmental management.

The Kalatag Ore Cluster Area, located in the Eastern Tianshan metallogenic belt of Xinjiang, stands out as a notable copper polymetallic mineralization zone, recognized for its diverse ore types and untapped potential. Despite the foundational nature of traditional exploration methods, they have not fully exploited this potential. Addressing this, our study leverages modern geospatial technologies, especially ArcGIS, combined with multi-source geoscience data to refine ore formation predictions in Kalatag. We identified key ore-controlling factors: the ore-bearing strata of Daliugou and Dananhu Groups, buffer zones around faults and intrusions, and geophysical anomalies. From these, a conceptual model was developed using the weight of evidence model. This model pinpointed four ‘A’ class and three ‘B’ class targets for mineral exploration, highlighting the central role of faults in ore control. Significantly, all known ore deposits were encompassed within these targets. Our approach not only paves the way for improved ore prediction in Kalatag but also offers a blueprint for other mineral-rich areas. Merging traditional geology with advanced technology, we elevate mineral exploration’s precision, emphasizing the synergy of an integrated method, especially in geologically complex areas. The effectiveness of our model provides insights for future exploration, particularly in mining areas’ deeper zones.

The social function and the ecosystem services provided by green urban areas (GUAs) have long been acknowledged by both the scientific community and the public. They become even more relevant to urban sustainability and human welfare in the post-pandemic world, which still has to confront social, environmental, and energy-related issues. This study aims to provide an example of how to perform a temporal dynamics-focused analysis of GUAs in an unsatisfactory data context by comparing the results obtained via spatial and statistical datasets of 35 cities in Romania considering the 2006–2018 period as a reference. This integration represents a compromise solution that should offer insights into the GUA’s dynamics in difficult monitoring conditions determined by the absence of both high-resolution spatial datasets and metadata-enhanced statistical datasets. Specific patterns of the GUA’s dynamics are identified, and the differences between the spatial data and statistical data-based findings are discussed. For at least 78% of the analysed cities, the official statistical data show that the GUAs are larger than the ones computed via GIS, in all reference periods. The findings call for the improvement of the GUA quantification and mapping regulations and programmes, which target, among other elements, their transparency and validation.

The existing scenic spot passenger flow prediction models have poor prediction accuracy and inadequate feature extraction ability. To address these issues, a multi-attentional convolutional bidirectional long short-term memory (MACBL)-based method for predicting tourist flow in tourist scenic locations in a location-based services big data environment is proposed in this study. First, a convolutional neural network is employed to identify local features and reduce the dimension of the input data. Then, a bidirectional long short-term memory network is utilized to extract time-series information. Second, the multi-head attention mechanism is employed to parallelize the input data and assign weights to the feature data, which deepens the extraction of important feature information. Next, the dropout layer is used to avoid the overfitting of the model. Finally, three layers of the above network are stacked to form a deep conformity network and output the passenger flow prediction sequence. In contrast to the state-of-the-art models, the MACBL model has enhanced the root mean square error index by at least 2.049, 2.926, and 1.338 for prediction steps of 24, 32, and 60 h, respectively. Moreover, it has also enhanced the mean absolute error index by at least 1.352, 1.489, and 0.938, and the mean absolute percentage error index by at least 0.0447, 0.0345, and 0.0379% for the same prediction steps. The experimental results indicate that the MACBL is better than the existing models in evaluating indexes of different granularities, and it is effective in enhancing the forecasting precision of tourist attractions.

Sheet erosion is a complex multi-factor-dependent process with high spatial heterogeneity on hillslopes. Although the individual factors have been well studied, their aggregated effect on size-selective erosional processes is highly uncertain. Therefore, this study concentrates on the aggregate size distribution and effective particle size distribution (PSD) of the aggregates in the soil loss, collected from different simulated hillslope positions and surface conditions. These simulated hillslope positions combine moisture content from the extremely dry to the saturated with related slope positions of 2, 5, and 12% steepness and different surface roughness (tilled and crusted surfaces) modelled in a laboratory rainfall simulator. Using hierarchical cluster analysis, the PSD of the aggregates was separated into three groups based on the differences in the 59–116 µm range of the PSD histograms, namely, macro-aggregates, 50–250 µm sized micro-aggregates, and <50 µm sized fractions were classified into distinct groups, although some micro-aggregate samples were classified into the macro-aggregate group. PSDs from the 50–250 µm aggregate size fraction were clustered into a group of macro-aggregates if the PSD changed with time (during the rainfall event), notably on rough surfaces. The role of the specified size range in the classification is believed to be due to the parallel presence of aggregates and single particles in this range. As aggregates have a lower density than mineral particles, they tend to be enriched in soil loss under low-energy runoff conditions. Moreover, all samples in the <50 µm fraction clustered into the macro-aggregate group were eroded from the smooth/crusted surface, probably due to the presence of larger particles. The results indicate that the combined effect of erosional factors is not apparent, and the impact of the crust and extreme moisture content on the selectivity and size distribution of the sediment requires further investigation.

Soil erosion is the major environmental risk that causes topsoil loss, which decreases fertility in agricultural land. Spatial estimation of soil erosion is essential for conserving land resources and for developing control plans. This study evaluated soil erosion in 17 sub-basins of the Wadi Hanifa catchment using the Gavrilović model. The soil erosion rate is categorized into three classes based on the annual volume of rainfall and runoff. About 21% of the drainage area of Wadi Hanifa is affected by erosion severity, and 33% of the area is affected by severe erosion. The correlation obtained between the annual soil erosion and annual volumes of rainfall and runoff is significant. It is concluded from the results that the drainage area of the north-western part suffers from a high soil erosion risk. The NRCS-CN and erosion predict that the Gavrilović model can be applied for estimating and analyzing the spatial distribution of soil erosion over more drainage watersheds in Saudi Arabia. Now, the GIS techniques are one of the best tools for developing the conservation and management planning processes of soil resources.

This work presents an in-depth examination of the Carboniferous volcanic reservoir within the CH471 well area, situated in the central portion of the Hongche fault zone on the northwestern margin of the Junggar Basin. Leveraging seismic data and well connection comparisons, we scrutinize the tectonic evolution model and elucidate the impact of the nappe structure of the Hongche fault zone on the volcanic reservoir. The study has obtained the following understanding: after the formation of Carboniferous volcanic rocks, affected by the Hongche fault structure, a series of structural superpositions from extension to extrusion and finally thrust occurred, resulting in a northwestward tilt of the volcanic rock mass, and a large number of cracks were generated inside the rock mass. At the same time, the top was uplifted and affected by weathering and leaching to form a weathering crust, eventually forming a reservoir. The northern part is located in the edge area of the eruption center, and the rock mass has good stratification. The rock strata have certain constraints on the reservoir distribution, and the reservoir is inclined along the rock mass. The southern part is close to the eruption center and features large volcanic breccia accumulation bodies with strong internal heterogeneity. The reservoir developed mainly in the superposition of the range of control of the weathering crust and dense fracture development, and the rock mass morphology does not control the area. Structure is the key to forming a volcanic rock reservoir, mainly reflected in the following aspects. First, tectonic activity is accompanied by fracture development, and fractures are densely developed in areas with strong activity, which can effectively improve the physical properties of volcanic reservoirs. Second, tectonic activity leads to the strata uplift and weathering denudation, forming a weathering crust. Within the range of control of weathering and leaching, the physical properties of volcanic rocks are improved, and it is easier to form high-quality reservoirs. Third, the distribution of volcanic rock masses is controlled by tectonic activity, which affects the reservoir controlled by the dominant lithology.

Extensively used Mechanically Stabilized Earth (MSE) walls in Rail Transportation System (RTS) are vulnerable to surface vibrations generated by moving vehicles. Hence, it is necessary to consider the effects of surface vibrations during the design of MSE walls for RTS. Steel-reinforced panel-type MSE walls are shown to perform well during vibration loading, but costly steel materials have led to greater reliance on affordable and readily available geosynthetics for reinforcement. Limited research exists on the behavior of panel-type MSE walls with geosynthetics considering RTS-induced vibrations frequencies. Thus, this study employs Finite Element software PLAXIS 3D to simulate the impact of surface vibration frequencies on panel-type MSE walls. The qualitative study encompasses two reinforcement cases (geogrids and steel strips) of 4 m MSE wall height and four harmonic loading frequencies representing RTS-induced surface vibrations for simulation. The dynamic responses of MSE wall are presented in terms of lateral wall displacements and lateral earth pressure distributions. Furthermore, the distributions of tensile strain and the identification of potential slip surface locations are presented. The findings indicated that MSE wall and reinforcement responses are governed by RTS-induced vibrations and fundamental frequency of backfill soil. This highlights the need for consideration of both the fundamental frequency of the backfill soil and RTS-induced vibrations in the design of MSE walls.

The Lower Units of Alpine Corsica, France, are fragments of continental crust strongly deformed and metamorphosed under high-pressure metamorphic conditions. Three slices of Lower Units are well exposed in the area between the Asco and Tavignano valleys, Central Corsica. Despite their complex structural setting, they provide the opportunity for a reconstruction of the pristine stratigraphic setting of the Lower Units. In our reconstruction, these units consist of a Paleozoic basement topped by Triassic to Early Jurassic sedimentary rocks unconformably covered by Middle to Late Eocene foredeep deposits. However, the three units exposed in the study area display strong differences mainly in the thickness of the Mesozoic sequence. These differences are here interpreted as acquired during the first stage of the rifting process in a setting controlled by normal faults. During the collision-related tectonics and the accretion of the Lower Units to the Alpine orogenic wedge, these normal faults were probably reactivated with a reverse kinematics. The stratigraphic logs of the Lower Units strictly resemble those of the Pre-Piedmont Units from Western Alps. This similarity indicates a common origin of the Lower Units and the Pre-Piedmont Units from the same domain (i.e., the European distal continental margin).

The plant and animal wealth of a place, region, or state represents a significant component of the geographic-natural tourist offer. Tourist routes are concentrated specifically on areas with a variety of plants, rich vegetation, and diverse animal world. The Balkan Peninsula in general, and Kosovo in particular, is characterized by high geodiversity and biodiversity value. This feature can serve as an important recreational and tourism potential for Kosovo and, consequently, in sustainable tourism development. For this reason, this article deals with the content of natural diversity, the size and time of introduction of geo and biodiversity values under protection, and, above all, it brings arguments if the same contributed to the increase of tourist motivation for local and foreign tourists. Results were achieved using both quantitative and qualitative methods, with the latter being more effective in the lack of the formal system of data collection and tourism management in Kosovo. According to official statistics, protected areas (PAs) of Kosovo occupy roughly 12% of the total area (2021). There was a significant rise (8%), from 4.26 to 12.25% in 2003 in the last 20 years (2021). The study shows that this desirable level of representation did not attract enough tourists. Furthermore, it is argued that immediate reformation of policies is required for the management of natural diversity values of the country. In order to achieve this, the government must implement more comprehensive measures in order to manage PAs more intricately, where the interaction with tourism is a key issue and not just a simple one, as it has been up until now.

Toplica district represents an area in Southern Serbia with significant forms of geoheritage that have not been valorized yet. The aim of this pioneering study is to systematically analyze and evaluate all manifestations of the geodiversity in the Toplica district. Based on the geological importance, degree of attractiveness, and size, a total of six geosites were selected. The main goal of the study is to emphasize the insufficient utilization of huge geotourism potentials of the Toplica district and to determine the current geotourism development and geotourism potential of evaluated geosites. The geotourism suitability of each geosite is defined through comparative analysis. The Geosite Assessment Model (GAM) is used to assess the current state of the various elements of geodiversity in the study area. Positioning within the GAM matrix is defined by the values of the investigated parameters. Visualization of the distribution of the GAM indicators is an innovative approach for the interpretation of the obtained results. As a projection of the geotourism potential, the study presents the results of the traffic accessibility of geosites using the Geographic Information System (GIS)-based isochronous method. GIS and Digital Terrain Models are used in the visualization of the research area. The results of GAM apostrophize the current tourist value of Devil’s City, while the isochron analysis of GIS highlights the great geotourism potential of publicly little-known and touristically unaffirmed geosites. The results represent a basis that can support the affirmation of geotourism, the improvement of existing, and the development of new geotourism strategies in the Toplica district.

Underwater biological detection is of great significance to marine protection. However, the traditional target detection techniques have some challenges, such as insufficient feature extraction for small targets and low feature utilization rate. To address these challenges, an underwater biological detection model IG-YOLOv5 based on the idea of feature reuse is proposed. An Improved-Ghost module with feature reuse is designed. The module adds batch normalization operations to the identity mapping branch using the Add operation with feature fusion and the Sigmoid Linear Unit activation function with smoother zeros. The proposed model uses the Improved-Ghost module to reconstruct the CSPDarknet structure of YOLOv5, so as to realize the lightweight and accuracy improvement of the model. In addition, in order to solve the problem of target size and shape change in underwater environment, the optimized loss function is Wise-IoU v3, which is used to evaluate the accuracy and robustness of detection results. The results show that the IG-YOLOv5 model performs well in the 2021URPPC data set, with 0.5 mAP reaching 74.2, 4.3% higher than that of YOLOv5 model, and 2.7 less floating-point operations. In a word, IG-YOLOv5 model has high accuracy and robustness in underwater target detection, and Wise-IoU index can evaluate the quality of target detection results more accurately, which is suitable for underwater robots, underwater monitoring, and other fields and has a practical application value.

Remote sensing-based approaches have gained widespread usage in drought monitoring studies. However, relying on single-variable drought indices may be inadequate to provide a comprehensive understanding of drought dynamics. In this study, principal component analysis was employed to derive a combined index, namely, the combined drought index (CDI), from multiple indices such as vegetation condition index, temperature condition index, precipitation condition index, and soil moisture condition index. The CDI was subsequently employed to analyze drought occurrences in the Ergene Basin-Türkiye period from 2001 to 2020 (May to October) using MODIS data. Correlations were computed with standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) at 1-, 3-, and 6-month scales and crop yield. The results revealed that drought incidents transpired in the Ergene Basin for at least 1 month annually. May exhibited the wettest, while September stood as the driest month. The severity of drought and its spatial extent displayed an increasing trend followed by a subsequent decline during the aforementioned period. The CDI demonstrated stronger correlations with the 1-month standardized indices than the 3- and 6-month SPI-SPEI. A robust correlation of 0.79 was also observed between the CDI and the crop yield. In general, the CDI performed well in determining the spatial and temporal patterns of the historic droughts. As a result, the CDI could be leveraged to develop effective drought monitoring and management, which could help mitigate the negative impact of drought in the fragile environment of the Ergene Basin.

Official data, including national geodetic and cartographic resources, are integrated in a spatial reference system. This study outlines national resources in Poland as an important part of the spatial information infrastructure in the European Community. They also provide reference data, including: geodetic control networks, base map, and topographic maps, for other resources of spatial data infrastructure. The study presents changes in the methods of sharing geo-data and technical standards for their collecting in the last few years, and additionally also presents some aspects of progressing geodetic and cartographic resources and legislation in Poland. It was noted that modern national geoportal or regional and district resources and progress, especially in the form of their standardization of presentation, enable to promote the use of spatial data in Poland and their popularization among the international community.

Mining still plays a vital role in providing various sectors with essential materials since many industries depend heavily on mined minerals. Moreover, the mining industry is the primary driver for many economies worldwide. On the other hand, new mining projects face many challenges, the most important of which are risks related to the economic aspects, e.g., the significant uncertainty about mineral resources compared to other engineering projects. Therefore, many jurisdictions worldwide depend on detailed engineering studies conducted according to internationally recognized standards to assess the new mining projects from an economic and technical perspective. In the same context and due to the significant lack of published research in this field, as the literature review revealed, this article reviewed and discussed the different main stages of engineering studies to evaluate new potential mining projects, including scoping, pre-feasibility, and feasibility studies, to ensure that the engineering study report complies with all the recognized main requirements. Results indicated the necessity of adhering to the needs of the engineering tasks while preparing reports of evaluation studies for new mining projects to reduce potential uncertainty risks and thus raise the level of confidence in these types of projects. Furthermore, they showed direct progress between the investigation details conducted in the evaluation studies and the value of the new mining project.

Grain size is a fundamental physical property of sediments, and its parameters are crucial indicators of the provenance, transport processes, and depositional environments. However, owing to the availability of graphic and moment method choices for the determination of grain size parameters, the associated data are characterized by inconsistencies, and these issues restrict the utilization of such data. Compared to other regions, comparative analyses of grain size parameters determined using the graphic and moment methods for aeolian sediments in the Tibetan Plateau are scant. To obtain more accurate information and optimize and integrate historical data, in the present study, sediments in the Yahecun section of the Menyuan Basin in the northeastern Tibetan Plateau were investigated. Data for the Menyuan loess show that the mean grain size, sorting, skewness, and kurtosis data obtained from the two methods can be converted using linear equations. However, differences in the descriptions following the establishment of relationships should be considered. Owing to its sedimentary characteristics, the moment method is more suitable for determining grain size parameters for the Menyuan loess. The results from the moment method indicate that the Menyuan loess originated from multiple sources involving varying dynamics, and the sediments recorded changes from a cold, dry to a warm climate.

Flood forecast models have become better through research as they led to a lower risk of flooding, policy ideas, less human death, and less destruction of property, so this study uses Scientometric analysis for floods. In this analysis, citation-based data are used to uncover major publishing areas, such as the most prominent keywords, top best commonly used publications, the most highly cited journal articles, countries, and authors that have achieved consequent distinction in flood analysis. Machine learning (ML) techniques have played a significant role in the development of prediction systems, which have improved results and more cost-effective strategies. This study intends to give a review of ML methods such as decision trees, artificial neural networks, and wavelet neural networks, as well as a comparison of their precision, speed, and effectiveness. Severe flooding has been recognized as a significant source of massive deaths and property destruction in several nations, including India, China, Nepal, Pakistan, Bangladesh, and Sri Lanka. This study presents far more effective flood forecast approaches. This analysis is being used as a guide for experts and climate researchers when deciding which ML algorithm to utilize for a particular forecasting assignment.

Rainfall is one of the leading causes of transportation embankment failure. Similarly, the fill material properties and the loading conditions of the embankment serve as principals for assessing the mechanisms of potential failures that are derived from rainfall-related events. These events affect the hydro-mechanical behaviors of embankment fills and cast doubt on the construction and service life of most transportation-infrastructure. This article presents a review, of existing available records to critically examine rainfall-induced transportation embankment failures, causes, mechanisms, existing measures, and prevention techniques. Consequently, a review of the susceptibility assessment of infrastructures due to rainfall-induced failures, particularly in China, and embankment characteristics and their effects on the duration, magnitude, and safety of the infrastructures was carried out. The study was able to classify rainfall conditions as they influence embankment stability. We suggest the development of local and global rainfall-embankment fill material relationships that will give unique information on how rainfall-events change the behavior of fill material and to what extent they trigger failures. A summary of some of the active processes leading to transportation embankment failures is presented. Finally, we concluded by identifying future and prospective rainfall-induced transportation embankment failures that will enhance monitoring and mitigation of instability in embankments.

One outcrop of the NE–SW-trending fault with a steep occurrence and grown gouge was discovered in the north segment of the Tangshan fault zone during a field survey near Jujialing village on the Kaiping-Guye boundary of Hebei province, North China. This zone has received less attention in seismic geologic surveys. In addition, three neighboring and parallel NE trending scarps with heights in the range of 1–1.5 m were discovered on the generally flat terrain close to the fault outcrop. The geochemical and multi-electrode resistivity surveys revealed sudden huge fluctuations in the Hg concentration within short distances from the fault outcrop and the three surface scarps. The multi-electrode resistivity survey also revealed a resistivity structure with extreme horizontal discontinuity, indicating the presence of a subsurface fault zone with a width of 40–50 m and a SE dip. This finding confirmed that the three surface NE trending scarps were late Quaternary fault scarps. Following an examination of the focal mechanism solutions and survey findings, it is suggested that the newly detected fault trending toward the northeast could be an unexplored branch fault in the flower structure of the northern section of the Tangshan fault zone. It is marked by recent activity that is mainly controlled by the right-lateral strike-slip. The discovery of this active fault is critical for an accurate assessment of the seismic hazard of north segment of the Tangshan fault zone.

The geological data of the mineral resource potential evaluation results (MRPERs) are diverse and extremely large; efficiently retrieving data remains a challenging problem. In this work, a new way of using the Hadoop platform is proposed. The Hadoop distributed file system is used to store the massive data and construct the data storage model of geological and mineral resources. Using a distributed Hadoop database (HBase) that supports the fast query of a single record, it manages its metadata and retrieves the data of MRPERs quickly. At the same time, a multi-level index directory is designed to support the non-main key query on the HBase. This overcomes the shortcoming that the HBase only supports the simple index based on the main key and realizes the intelligent, efficient retrieval of MRPERs. The validity and feasibility of the proposed method are further verified by experiments using the MRPER data in the Institute of Mineral Resources, Chinese Academy of Geological Sciences.

“High-quality development” is an important objective for China’s current development projects. For the betterment of the current situation of the underdeveloped regions, high-quality development is necessary. The comprehensive index method is one of the most widely used methods for evaluating high-quality development works, and indicator weighting is its key and at the same time the most controversial step. Among many weighting methods, the entropy weighting method is widely applied due to its easier understandability and use. This article focuses on the problem of weight distortion when the entropy values of indicators are close to 1 and the improvements to this problem. To verify these improvements, this article deduces with mathematical analysis, the underlying assumptions of the problem and evaluates the level of high-quality development in Qinghai Province, which is assumed to be an appropriate example of the underdeveloped regions in western China. Our mathematical deductions demonstrate that these underlying assumptions do not theoretically exist. In addition, both the improved and the original methods have similar performances in practice or, more specifically, have shown an overall upward trend in the level of high-quality development in Qinghai Province. Because the “problem” is extremely stringent and difficult to reproduce, we conclude that further improvements on the entropy weighting method should not be a focus of future research. To address the subjectivity or objectivity issues of weighting, weightless methods may be of use and should be developed.

The use of loess as a resource for paleoclimatic research is quite well established. In Serbia, a significant number of loess sequences have been preserved in old brickyards. The results of the previously conducted research indicate extremely valuable data that enable a better understanding of the mid- to late Pleistocene climatic evolution in this part of Europe, as well as human dispersal from Africa to Europe via the so-called Danubian migration corridor. The aim of this study is to evaluate the geotourism potentials of the loess profiles in Požarevac (northeastern Serbia). The goal is to determine their geotourism potential for paleoclimate interpretation. The Modified Geoheritage Assessment Model method has identified exceptional geotourism potentials that can be implemented in the tourism market. Paleoclimatic data can serve as indicators for the development of scientific visitor centers for the promotion and popularization of paleoclimate science and museums, which will affirm sustainable socio-economic development through multidisciplinary interpretation. By combining geological, paleoclimatic, archaeological, biological, and other values that reveal natural and anthropogenic events from the distant past, it is possible to create a very competitive geotourism destination, whose sustainability can be passed on to future generations.