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To address the problem of ignoring unpaved roads when planning off-road emergency rescue paths, an improved A* algorithm that incorporates road factors is developed to create an off-road emergency rescue path planning model in this study. To reduce the number of search nodes and improve the efficiency of path searches, the current node is classified according to the angle between the line connecting the node and the target point and the due east direction. Additionally, the search direction is determined in real time through an optimization method to improve the path search efficiency. To identify the path with the shortest travel time suitable for emergency rescue in wilderness scenarios, a heuristic function based on the fusion of road factors and a path planning model for off-road emergency rescue is developed, and the characteristics of existing roads are weighted in the process of path searching to bias the selection process toward unpaved roads with high accessibility. The experiments show that the improved A* algorithm significantly reduces the travel time of off-road vehicles and that path selection is enhanced compared to that with the traditional A* algorithm; moreover, the improved A* algorithm reduces the number of nodes by 16.784% and improves the search efficiency by 27.18% compared with the traditional 16-direction search method. The simulation results indicate that the improved algorithm reduces the travel time of off-road vehicles by 21.298% and improves the search efficiency by 93.901% compared to the traditional A* algorithm, thus greatly enhancing off-road path planning. [ABSTRACT FROM AUTHOR]

The ecological and environmental problems of arid zones have become an urgent global concern. Current research on ecological risk is based mainly on the dominant functions of land use, with a primary focus on land use landscape projections and less consideration of potential risks to ecosystems, system resilience and interactions between nature and future sustainable development. In this study, a potential–connectivity–resilience ecological risk assessment model based on the SDGs was constructed using multisource data to spatially quantify indicators at the grid scale in the Turpan and Hami regions of Xinjiang, China. This model was used as a basis for studying ecological risk in arid zones from a production–living–ecological space (PLES) perspective. The results revealed that, during the period 2000–2020, PLESs in the Turpan and Hami regions presented significant spatial similarity, with an increasing trend in overall risk. The production space in the Turpan and Hami regions showed a parabolic trend of increasing and then decreasing, whereas the living space and ecological space in the Hami region showed continuous linear upward trends. The state of ecological security in the Turpan and Hami regions is gradually deteriorating, and comprehensive ecological protection and restoration measures are urgently needed to rationally allocate the structure and layout of the production-–living-–ecological space. The study of ecological risk from a PLES perspective not only helps in fully understanding the development trend of the arid zone; it also provides new ideas and methods for evaluating regional ecological environmental safety and scientific references for formulating regional sustainable development, ecological risk prevention and control and the rational allocation of resources. [ABSTRACT FROM AUTHOR]

Ecologically fragile areas are confronted with the contradiction between economic development and ecological protection, especially in the Tuha region (Turpan and Hami), where the extremely vulnerable ecological environment limits local sustainable development. To address this, this study utilizes POI (Point of Interest) data, land use, and socioeconomic statistical data to achieve spatial quantification of indicators on a kilometer grid scale, constructing a multi-factor, multi-dimensional evaluation system for the socioeconomic and ecological effects of sustainable development based on SDGs (Sustainable Development Goals). The entropy method, comprehensive evaluation method, coupling coordination degree model, and geographical detector method are used to analyze the coupling relationships between systems at different scales and the factors influencing the system's coupling coordination degree. The results indicate that from 2010 to 2020, the economic, social, and ecological systems of the Tuha region, as well as their comprehensive scores, exhibited spatial similarity. The economic system showed an upward trend, the social system displayed an inverted U-shaped trend of rising then declining, while the ecological system presented a U-shaped trend of declining then increasing. At the county scale, the coupling coordination degree closely approximates the trend of the comprehensive coordination index, showing a continuous upward trajectory. Compared with Turpan city, Hami city, especially Yizhou district, exhibits the best development in coupling coordination degree, while the growth in coupling coordination degree is most significant in Gaochang district. The main factors influencing the degree of coupling coordination are grain production and GDP (gross domestic product). This study provides a new perspective on the quantification of sustainable development indicators, which is of great significance for balancing economic and social development with ecological protection and promoting the coupled and coordinated development of society, economy, and ecology in ecologically fragile areas. [ABSTRACT FROM AUTHOR]

In recent years, rapid urban expansion and increasing ecological sensitivity in arid zones have led to extreme imbalances in ecosystem development. Therefore, there is an urgent need to balance the dual goals of synergistic development of ecosystem services (ESs) and increased urbanization. Previous studies have analyzed the impacts of urbanization on ESs but have selected a limited number of indicators and have not focused on the impacts of urbanization on ES pair interactions. In this study, six key ESs (water yield, habitat quality, soil conservation, carbon storage, carbon sequestration and oxygen production, and food production) and total ecosystem services (TESs) were selected, and trends in the temporal and spatial relationship between trade-offs and synergies were analyzed over 20 years. This study refined the living standards urbanization indicator and evaluated the impact of urbanization and multiple drivers on ESs and ES pair interrelationships based on geo-detectors and segmented linear regression. The results show that there is heterogeneity in the overall and regional ES trade-offs and synergistic relationships, and water yield (WY)-related ES pairs generally exhibit synergistic relationships at the overall level. Spatially, however, the trade-off ratio exceeds the synergy ratio. Segmented linear regression results show that the relationship between all the urbanization indicators and TESs demonstrates an upward trend followed by a downward trend. Measures such as the increase in man-made oases in the early stages of urbanization did have some positive effects on TESs. However, as urbanization increased, these positive effects were quickly offset by the negative effects of overdevelopment and environmental degradation, leading to an overall decline in TESs. Urbanization of construction land (CL) had the most direct impact on ecosystem services. In summary, due to special climatic constraints, arid zones are more sensitive than other ecosystems, and urban development is strictly limited by oasis capacity. As cities expand, attention needs to be focused on protecting ecological land and limiting the expansion of CL to promote the synergistic development of urbanization and ecosystem services in arid zones. [ABSTRACT FROM AUTHOR]

Current road extraction models from remote sensing images based on deep learning are computationally demanding and memory-intensive because of their high model complexity, making them impractical for mobile devices. This study aimed to develop a lightweight and accurate road extraction model, called Road-MobileSeg, to address the problem of automatically extracting roads from remote sensing images on mobile devices. The Road-MobileFormer was designed as the backbone structure of Road-MobileSeg. In the Road-MobileFormer, the Coordinate Attention Module was incorporated to encode both channel relationships and long-range dependencies with precise position information for the purpose of enhancing the accuracy of road extraction. Additionally, the Micro Token Pyramid Module was introduced to decrease the number of parameters and computations required by the model, rendering it more lightweight. Moreover, three model structures, namely Road-MobileSeg-Tiny, Road-MobileSeg-Small, and Road-MobileSeg-Base, which share a common foundational structure but differ in the quantity of parameters and computations, were developed. These models varied in complexity and were available for use on mobile devices with different memory capacities and computing power. The experimental results demonstrate that the proposed models outperform the compared typical models in terms of accuracy, lightweight structure, and latency and achieve high accuracy and low latency on mobile devices. This indicates that the models that integrate with the Coordinate Attention Module and the Micro Token Pyramid Module surpass the limitations of current research and are suitable for road extraction from remote sensing images on mobile devices. [ABSTRACT FROM AUTHOR]

Mineral Prospectivity Mapping (MPM) is shifting toward intelligent deep mineralization searches in the era of big data and the increasing difficulties of surface deposit detection. Comparative analysis of two forms of mineralization prediction based on the Apriori algorithm was performed in the Meiling South mining area in the eastern Hami region of Xinjiang, China. In comparison 1, we use the Apriori algorithm to mine ore-forming information and determine the ore-forming voxel positions based on spatial distance and angle analysis. Then, we compare the ore-forming voxel positions determined by Apriori with the ore-forming voxel positions predicted by the mathematical model based on the conceptual model of mineralization, and these mathematical models include Gaussian Naive Bayesian (GNB) and Support Vector Machine (SVM). In comparison 2, the optimal prediction model is SVM, which is trained using the elements of mineralization prediction determined by the conceptual model of mineralization. Then, two sets of new elements of mineralization prediction are extracted from the original elements of mineralization prediction using the Apriori and Chi-square methods and then input into the SVM model for training. After we obtain the mineralization prediction results, we compare them with the original mineralization prediction results. The preceding comparison produced the following results. (1) Using the Apriori algorithm, the distribution characteristics of the high and low-grade ore bodies and the association rules between ore-bearing information were determined. (2) The prediction results of the GNB and SVM models displayed corresponding trends on the high and low-grade ore-bearing voxels identified by Apriori, which matched the rules mined by Apriori. (3) In comparison to the mineralization prediction elements screened by Chi-square and the original mineralization prediction elements based on the conceptual model of mineralization, the elements of mineralization prediction chosen based on Apriori have the best prediction effect in SVM when tested in new drill holes. Based on the mineralization prediction elements screened by Apriori, the number of accurate ore-bearing voxels (prediction probability greater than 0.5) predicted by the SVM model is 6, 5, and 1 in drill holes V1, V2, and V3, respectively. The collective results demonstrated that Apriori is explicit, intuitive, and interpretable for mineralization prediction and has a certain reference value for refining the determination of mineralization prediction elements and discovering mineralization mechanisms and laws. [ABSTRACT FROM AUTHOR]

Natural vegetation on both sides of the Tarim River Basin (TRB) is the only barrier—a critical ecological niche—between the economic belt in the artificial oasis and the Taklimakan Desert. To understand the impact of human activities on the TRB, we explored the spatial and temporal variations in land use/land cover change (LUCC) and landscape pattern evolution from 2000 to 2020. These variations were simulated for 2030 with the 20 years of data using the cellular automata–Markov model and geographical information system analyses. The results predicted substantial LUCCs in the lower reaches of the Tarim River (TRlr), with 3400 km2 (20.29%) of the total area (16,760.94 km2) undergoing changes. Wetland, artificial land, grassland, farmland, and forestland areas increased by 578.59, 43.90, 339.90, 201.62, and 536.11 km2, respectively, during the period from 2020 to 2030. The only decreases were in the Gobi/other deserts and bare soils (1700.13 km2). We also determined current and future changes in TRlr landscape pattern indices at the class and landscape levels. Combined with a field survey and hydrological data, theoretical support for effective land use management strategies is provided. The findings offer a scientific basis for future ecological civilization construction and sustainable development in the TRB. [ABSTRACT FROM AUTHOR]

Full‐waveform inversion of surface waves can provide high‐resolution S‐wave velocity (Vs) of the shallow subsurface and is becoming a popular shallow‐seismic method. We propose a misfit function based on instantaneous‐phase coherency, which can measure the amplitude‐unbiased coherency between measured and synthetic data. The instantaneous‐phase coherency was once the key component that was used in the phase‐weight stacking technology to enhance the weak but coherent signals. Using synthetic data, we show that our full‐waveform inversion approach based on the proposed misfit function is robust in reconstructing subsurface anomalies from data contaminated by random noise. We also show that our misfit function is robust against the errors in the estimated source wavelets. We then choose to use published field data acquired at an archaeological site as a benchmark dataset to test the performance of our full‐waveform inversion in a real environment. Subsurface structures identified in our inversion results are verified by an independent archaeological excavation, while the results from conventional full‐waveform inversion are dominated by artefacts. The results of synthetic tests and field data experiments demonstrate the robustness of our full‐waveform inversion approach in reconstructing the shallow subsurface structure from field data, where amplitude information of recorded wavefield may not be correctly recorded. [ABSTRACT FROM AUTHOR]

Mechanical vibration constitutes a valuable cue for performing fault diagnosis as it is directly related to the transient regime of rolling machinery. This study establishes a multidomain feature fusion network (MFFN) to extract and fuse multidomain features through a novel multistream architecture. Three primary features are simultaneously extracted from the time, frequency, and time-frequency domains. Then, highly representative features are extracted via three convolutional branches in one- or two-dimensional spaces. A novel squeeze-connection-excitation (SCE) module is proposed to adaptively fuse features in the three domains. The advantage offered by the proposed method is that it can leverage cues from the raw vibration signal, resulting in accurate fault diagnosis. Experimental results comprehensively demonstrate and analyze the high accuracy and generalization achieved by this MFFN-based fault diagnosis method. [ABSTRACT FROM AUTHOR]

Downward continuation is a useful tool for improving the resolution of potential field data. It reconstructs the field at a lower observation height from the observed field to highlight detailed anomalies of the field source distribution and to distinguish overlapping anomalies of multiple targets. However, downward continuation is unstable and sensitive to noise in the data; thus, influencing the popularity of this method. Here, we present an iterative filtering method in wavenumber domain based on improved Gaussian function to accomplish downward continuation of potential field data. In this method, multiple corrections are implemented on the continuing plane by downward continuing the difference between the observed and the calculated field data to compensate for the precision of the downward continuation. The wavenumber responses of downward continuation operators of the proposed filter function were analyzed, and the performance and stability of the method were tested on a synthetic model. Satisfactory results were obtained, as the method yielded more accurate anomaly amplitude and demarcated boundary of field sources in the model as compared with other downward continuation methods. In addition, the technique was implemented on aeromagnetic data acquired from the Kalatag polymetallic district, NW China, and we further verified that the proposed method has stable convergence, which revealed accurately the shallow magnetic source features in this district. [ABSTRACT FROM AUTHOR]

We have carried out microseismic forward modelling in orthorhombic poroelastic medium. The seismic response to isotropic (ISO) source, double couple (DC) source and compensated linear vector dipole (CLVD) source was solved by finite-difference algorithm in time domain, respectively. We used analytical solution to test our numerical algorithm and find that the match between the analytical solutions and numerical solutions is sufficiently close. We then designed several different models to calculate the seismic response and analyse the effect of medium parameters and source mechanism on the propagation of seismic waves. We observed from the modelling results that ISO source excites two kinds of waves in isotropic medium, which are fast longitudinal wave and slow longitudinal wave, while the DC and CLVD sources excite three kinds of waves in isotropic medium, including a transverse wave in addition to the fast and slow longitudinal waves. All of these three kinds of sources generate four kinds of seismic waves in orthorhombic poroelastic medium. These are two separable transverse waves in addition to the fast and slow longitudinal waves. The fluid viscosity and medium tortuosity has an effect on the propagation of the slow longitudinal wave. The slow longitudinal wave appears in propagating mode under the effect of low fluid viscosity and appears at the source location in a static mode under the effect of high fluid viscosity. The wavefield snapshot of the slow longitudinal wave has a circular shape when the tortuosity is isotropic, whereas it has an oval shape when the tortuosity is anisotropic. As far as the anisotropic parameters are concerned, the anisotropy of the fast longitudinal wave is more sensitive to the value of |$\varepsilon ({{\varepsilon _1},{\varepsilon _2}})$|⁠ , while the value of |${\rm{\delta }}({{{\rm{\delta }}_1},{{\rm{\delta }}_2},{{\rm{\delta }}_3}})$| has more effect on the anisotropic behaviour of the two separable transverse waves. [ABSTRACT FROM AUTHOR]

Quantitative determination of the physical properties of natural granite has been attempted from remotely sensed information, for which the Hapke model is a popular method. However, using the model to retrieve the photometric properties of terrestrial rocks (slab or particulate samples), especially for those with complex surface conditions such as natural granite, remains a challenge. In this study, we have approached the dilemma by coupling both radiative transfer (Hapke’s isotropic multiple scattering approximation (IMSA) model) and an empirical relationship between particle sizes with its critical parameter, the single-scattering albedo (SSA, $\omega$), determined from bidirectional reflectance (BDR) measurements. The results clearly indicated that the particle size of natural granite systematically controlled the BDR, which can be well fit by the Hapke model with varying parameters. The retrieved photometric parameters of the coefficients in the phase function ($b$ and $c$) can effectively indicate the scattering behavior of natural granite, but the variations in their values did not strongly correlate with the change in particle sizes. Instead, a good linear relationship between the SSA values and particle sizes has been established. By coupling the relationship into the Hapke model, we found a practical approach to estimate the particle size for measured samples from inversely retrieved SSA. Through this method, we are able to retrieve the physical properties of granite under natural surface conditions, and we foresee that the approach will be widely used in the future. [ABSTRACT FROM AUTHOR]

Remote sensing phytochemistry has been proven by many studies to be an effective method for the detection of hidden minerals in vegetation-covered areas. In this study, we determined whether Seriphidium terrae-albae, a small shrub distributed widely in arid deserts, could be an effective sampling medium for application in remote sensing plant geochemistry. The absorption and aggregation characteristics and spectral changes in Seriphidium terrae-albae transplants at varying soil concentrations of copper (Cu), nickel (Ni), gold (Au), and zinc (Zn) were studied via simulation testing using artificial transplant cultivation. The results showed the following. (1) There exists a good logarithmic relationship between Cu and Zn contents in Seriphidium terrae-albae and the corresponding contents in soil, with coefficients of determination (R2) reaching as high as 0.936 for Cu and 0.9568 for Zn, while a linear relationship is observed between Au and Ni contents in the plant and the corresponding contents in soil, with R2 values as high as 0.9524 for Au and 0.9177 for Ni. (2) The accumulation of Cu and Ni in Seriphidium terrae-albae transplants grown in soil with high Cu and Ni contents is higher than in controls grown in normal soil, demonstrating the ability to clearly indicate abnormal Cu and Ni contents. (3) The ratio vegetation index based on the reflectance at 747 and 742 nm can be adopted to estimate Cu content in Seriphidium terrae-albae. These results suggest that Seriphidium terrae-albae exhibits great potential as an effective geochemical remote sensing plant sampling medium for concealed Cu deposits. This study provides proof of concept for the hyperspectral remote sensing technique in the exploration of hidden minerals in arid deserts, a quick measurement means of Cu content anomalies in the Seriphidium terrae-albae plant and a reference for the identification of prospective metallogenic areas, which could not only expand the existing prospecting space but could also improve the prospecting efficiency in arid deserts. [ABSTRACT FROM AUTHOR]

The Xiaotian–Mozitan Shear Zone (XMSZ) is the boundary of the Dabie High‐grade Metamorphic Complex (DHMC) and the North Huaiyang Tectonic Belt. It was deformed in ductile conditions with a top‐to‐NW/WNW movement. Geothermometers applied to mineral parageneses in mylonites of the shear zone give a temperature range of 623–691°C for the predeformation and 515–568°C for the syndeformation, respectively, which indicates a retrograde process of evolution. A few groups of zircon U‐Pb ages were obtained from undeformed granitic veins and different types of deformed rocks in the zone. Zircons from the felsic ultramylonites are all magmatic, producing a weighted mean 206Pb/238U age of 754 ± 8.1 Ma, which indicates the time of magmatic activities caused by rifting in the Neoproterozoic. Zircons from the granitic veins, cutting into the mylonites, are also of magmatic origin, producing a weighted mean 206Pb/238U age of 130 ± 2.5 Ma, which represents the time of regional magmatic activity in the Cretaceous. Zircons from the mylonitic gneisses are of anatectic‐metamorphic origins and are characterized by a core‐mantle interior texture, which yielded several populations of ages including the Neoproterozoic ages with a weighted mean 206Pb/238U age of 762 ± 18 Ma, similar to that of the felsic ultramylonites and the Early Cretaceous ages with a weighted mean 206Pb/238U age of 143 ± 1.8 Ma, indicating the anatectic metamorphism in the Dabie Orogenic Belt (DOB). Based on integrated analysis of the structure, thermal conditions of ductile deformation and the contact relations of the dated rocks, the activation time of the Xiaotian–Mozitan Shear Zone is constrained between ∼143 Ma and 130 Ma, during which the DOB was undergoing a transition in tectonic regime from compression to extension. Therefore, the deformation and evolution of this shear zone plays an instrumental role in fully understanding this process. This research also inclines us to the interpretation of it as an extensional detachment, with regard to the tectonic properties of the shear zone. It may also be part of a continental scale extension in the background of the North China Block's cratonic destruction, dominated by the subduction and roll‐back of the Paleo‐Pacific plate, but more detailed work is needed in order to unravel its complicated development. [ABSTRACT FROM AUTHOR]

A high resolution aeromagnetic survey of Kalatage area was carried out, aimed at providing detailed geological structures information and guiding for further mineral prospecting. The recently acquired data was processed and interpreted to better understand the mode of occurrence of the Cu-Au polymetallic deposits and associated structural features. Several analysis techniques, such as reduction to the pole, spectral analysis, low-pass filtering, were applied to process the aeromagnetic data to understand the distribution of magnetic sources. The depth of magnetic sources was estimated by spectral analysis, and the shallower and deeper sources anomalies were analyzed. The Euler deconvolution, total horizontal derivative, tilt angle derivative and theta map were used to study lineament structures. The new structural scheme was established by comparison of above derivative results and geological data of the Kalatage area. The results show that the study area is affected by sets of NWW-SEE/NW-SE, NNE-SSW/NE-SW and nearly E-W directions faults structures; various probable magmatic rocks may be the results of the ascent and intrusion of magma along these regional fractures in the process of large-scale and deep tectonic-magmatic activities. The polymetallic ore deposits are mainly distributed within the eastern portion of the study area and are confined probably along structure lineament suggesting that it is structurally controlled. Furthermore, the favorable area for mineralization was proposed. These analyses help the recognition of structure features of differing magnetizations, interpretation of tectonic evolution, which could have important reference for further mineral prospecting. [ABSTRACT FROM AUTHOR]

Geochemical pattern recognition and anomaly mapping are always involved in the fields of environmental and exploration geochemistry. Principal component analysis (PCA) and factor analysis (FA) are most commonly used to reveal underlying geochemical associations for the purpose of spatial distribution pattern analysis. However, the methods of PCA and FA cannot eliminate correlations between different principal components/factors, meaning that geochemical associations revealed by PCA or FA could be simultaneously influenced by two or more principal components/factors, as can be observed from biplot analysis. Such problem provides a challenge for interpretation of geochemical/geological processes. In the present study, we demonstrated a simple method, termed compositional balance analysis (CoBA), to interpret critical geochemical/geological processes. Comparative studies between CoBA and compositional factor analysis, as well as data- and knowledge-driven CoBA, were considered to discuss the advantage and practicability of the CoBA in geochemical pattern recognition and anomaly mapping based on a case study in the Nanling belt, South China. The results indicate that the CoBA has greater efficiency in enhancing weak or concealed geochemical anomalies and suppressing spurious geochemical anomalies relative to multivariate dimensionality reduction analysis; especially, knowledge-driven CoBA provides more robust interpretation of geochemical/geological processes relative to data-driven CoBA. [ABSTRACT FROM AUTHOR]

With the rapid development of hyperspectral technology, estimating metal content in plants by establishing the relationship between vegetation indices and metal content has become popular. However, few researchers have studied whether the vegetation index can be used to estimate the metal content in Seriphidium terrae-albae. It is essential to estimate the metal content in S. terrae-albae because the geochemical information gathered in its body can provide reference for the exploration of concealed deposits. To propose a new vegetation index with which to estimate copper content, this study first analyzes the relationships between three types of vegetation indices, including the ratio, difference, and normalized vegetation index, constructed by the combination of two arbitrary bands in the range of 400–1300 nm and the copper content in S. terrae-albae. The results show that (R747.5 − R572.5)/(R747.5 + R572.5) and R752.5/R517.5 have greater relationships with copper content than other vegetation indices. This method's applicability for estimating copper content using these two types of vegetation indices is compared from three different angles: the accuracy of the metal content estimation, the sensitivity of the vegetation index to the metal content, and the influence of spectral scale. The results reveal that R752.5/R517.5 has a more stable spectral width than (R747.5 − R572.5)/(R747.5 + R572.5), and it can also be used to easily detect subtle changes in copper content. Finally, we determine that R752.5/R517.5 is the best vegetation index for estimating the copper content in S. terrae-albae. [ABSTRACT FROM AUTHOR]

Rock geochemical information is important for mineral exploration and provides a theoretical basis for the rapid delineation of hidden minerals. Remote sensing technology provides the possibility of rapid and large-scale extraction of geochemical information from the earth's surface. This study analyzed the relationship between copper concentration and rock spectra by first collecting 222 rock samples, and then measuring the copper concentration of rock samples in the laboratory and reflectance spectra using an ASD FieldSpec3 portable spectrometer. It finally established quantitative relationships between the original spectra, first-order derivative spectra and second-order derivative spectra and copper concentration, respectively, using the partial least squares support vector machine method (PLS-SVM). The results show that 1) The estimation accuracy of using second-order derivatives spectra as input parameters to establish a model for estimating copper concentration is the highest, and the determined coefficient (R2) between the predicted value and real value reaches 0.54. 2) When the copper concentration is less than 80 mg/kg, the inversion model of copper concentration established using PLS-SVM obtains a good result. The R2 between the predicted copper concentration and the real copper concentration reached 0.70248. When the copper concentration is greater than 80 mg/kg, the inversion model of copper concentration established using partial least squares (PLS) obtains a good result. The R2 between the predicted copper concentration and the real copper concentration reached 0.49. The R2 between real copper concentration and copper predicted by the method of piecewise separate modeling reaches 0.816. Therefore, the method of segmental modeling has great potential to improve the accuracy of copper concentration inversion. [ABSTRACT FROM AUTHOR]

The timing of the initial opening and subduction of the Palaeotethyan Ocean is currently highly debated, in particular regarding the Jinshajiang Ocean in the central Tibetan Plateau. This study presents four well‐constrained U–Pb zircon ages (422.4 ± 6.1, 336.4 ± 7.4, 272.3 ± 2.8, and 255.8 ± 3.4 Ma) of mafic blocks in the Jinshajiang Suture. These mafic blocks have a chemical oceanic island basalt (OIB) affinity. These facts, together with previously published data (236 Ma OIBs), may be interpreted as a series of seamounts/oceanic plateaux varying from Late Silurian to Late Triassic, which were accreted early in the subduction–accretion process. An andesite from the Jinshajiang Suture with continental arc characteristics yielded a zircon U–Pb weighted average age of 385.2 ± 6.6 Ma, implying that the subduction initiation may have occurred at least in the Middle Devonian. Our work suggests a long‐lived continuous accretion, which also puts an earlier initial opening time than previously thought. Taking into account the above data and integrated with relevant published information, we favour a long‐lived accretionary process accompanied with seamounts/oceanic plateaux, which provides robust new evidence for subduction‐related continental growth in the central Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Geochemical anomalies are commonly separated into different geochemical anomaly levels based on one or more thresholds. However, this practice may cause some important geochemical anomaly information to be lost and subsequently draw wrong decisions for mineral exploration. In addition, previous studies indicate that sparse geochemical sampling always entails uncertainty resulting from conventional geochemical interpolation methods because of smoothing effect. Uncertainty can propagate through the various steps of geochemical data analysis that may lead to significant impact on the final results (e.g., anomaly interpretation and mineral exploration). For geochemical anomaly identification, quantifying the probability of unsampled locations and characterizing the spatial uncertainty of geochemical anomaly based on (not) exceeding a key threshold is very important for practical demands such as exploration risk assessment. Considering the limitations of deterministic modeling method and geochemical anomaly assessment, this study proposes a new method of geochemical anomaly uncertainty assessment by combining geostatistical simulation and singularity analysis. A case study for Au anomaly uncertainty assessment is presented in the west Tianshan region (China) so as to verify the feasibility and effectiveness of the proposed method. The sequential Gaussian simulation was adopted to generate a set of equiprobable realizations that were subsequently employed to produce a series of corresponding singularity index realizations by means of singularity analysis. Critical thresholds of E-type singularity index (α) were determined by the method of singularity-quantile plot analysis, which were used to simulate the spatial uncertainty of Au anomaly in the study area. The results show that the risk probability of Au anomaly characterized by (not) exceedance of a critical threshold can be considered as an important reference for exploration decision-making and risk management. [ABSTRACT FROM AUTHOR]

Multifractal features of element concentrations in the Earth's crust have demonstrated to be closely associated with multiple probability distributions such as normal, lognormal and power law. However, traditional understanding of geochemical distribution satisfying normal, lognormal or power-law models still faces a serious problem in adjusting theoretical statistics with the empirical distribution. Given that the differences among different geochemical distribution populations may have considerable effects on the target estimation, a new perspective from the singularity of fractal density is adopted to investigate mixed geochemical distribution patterns within frequency and space domains. In the framework of fractal geometry, ordinary density such as volume density (e.g., g/cm3 and kg/m3) described in Euclidean space can be considered as a special case of the fractal density (e.g., g/cmα and kg/mα). According to the nature of fractal density, geochemical information obtained from Euclidean geometry may not sufficiently reflect inherent geochemical features, because some information might be hidden within fractal geometry that can be only revealed by means of a set of fractional dimensions. In the present study, stream sediment geochemical data collected from west Tianshan region, Xinjiang (China), were used to explore element distribution patterns in the Earth's crust based on a fractal density model. Four elements Cu, Zn, K and Na were selected to study the differences between minor and major elements in terms of their geochemical distribution patterns. The results strongly suggest that element distribution patterns can be well revealed and interpreted by means of a fractal density model and related statistical and multifractal parameters. [ABSTRACT FROM AUTHOR]

Machine Learning technologies have the potential to deliver new nonlinear mineral prospectivity mapping (MPM) models. In this study, Back Propagation (BP) neural network Support Vector Machine (SVM) methods were applied to MPM in the Hatu region of Xinjiang, northwestern China. First, a conceptual model of mineral prospectivity for Au deposits was constructed by analysis of geological background. Evidential layers were selected and transformed into a binary data format. Then, the processes of selecting samples and parameters were described. For the BP model, the parameters of the network were 9-10 − 1; for the SVM model, a radial basis function was selected as the kernel function with best C = 1 and γ = 0.25. MPM models using these parameters were constructed, and threshold values of prediction results were determined by the concentration-area (C-A) method. Finally, prediction results from the BP neural network and SVM model were compared with that of a conventional method that is the weight- of- evidence (W- of- E). The prospectivity efficacy was evaluated by traditional statistical analysis, prediction-area (P-A) plots, and the receiver operating characteristic (ROC) technique. Given the higher intersection position (74% of the known deposits were within 26% of the total area) and the larger AUC values (0.825), the result shows that the model built by the BP neural network algorithm has a relatively better prediction capability for MPM. The BP neural network algorithm applied in MPM can elucidate the next investigative steps in the study area. [ABSTRACT FROM AUTHOR]

Cluster analysis is a well-known technique that is used to analyze various types of data. In this study, cluster analysis is applied to geochemical data that describe 1444 stream sediment samples collected in northwestern Xinjiang with a sample spacing of approximately 2 km. Three algorithms (the hierarchical, k-means, and fuzzy c-means algorithms) and six data transformation methods (the z-score standardization, ZST; the logarithmic transformation, LT; the additive log-ratio transformation, ALT; the centered log-ratio transformation, CLT; the isometric log-ratio transformation, ILT; and no transformation, NT) are compared in terms of their effects on the cluster analysis of the geochemical compositional data. The study shows that, on the one hand, the ZST does not affect the results of column- or variable-based (R-type) cluster analysis, whereas the other methods, including the LT, the ALT, and the CLT, have substantial effects on the results. On the other hand, the results of the row- or observation-based (Q-type) cluster analysis obtained from the geochemical data after applying NT and the ZST are relatively poor. However, we derive some improved results from the geochemical data after applying the CLT, the ILT, the LT, and the ALT. Moreover, the k-means and fuzzy c-means clustering algorithms are more reliable than the hierarchical algorithm when they are used to cluster the geochemical data. We apply cluster analysis to the geochemical data to explore for Au deposits within the study area, and we obtain a good correlation between the results retrieved by combining the CLT or the ILT with the k-means or fuzzy c-means algorithms and the potential zones of Au mineralization. Therefore, we suggest that the combination of the CLT or the ILT with the k-means or fuzzy c-means algorithms is an effective tool to identify potential zones of mineralization from geochemical data. [ABSTRACT FROM AUTHOR]

Mineral prospectivity mapping is an important preliminary step for mineral resource exploration. It has been widely applied to distinguish areas of high potential to host mineral deposits and to minimize the financial risks associated with decision making in mineral industry. In the present study, a maximum entropy (MaxEnt) model was applied to investigate its potential for mineral prospectivity analysis. A case study from the Nanling tungsten polymetallic metallogenic belt, South China, was used to evaluate its performance. In order to deal with model over-fitting, varying levels of βj-regularization were set to determine suitable β value based on response curves and receiver operating characteristic (ROC) curves, as well as via visual inspections of prospectivity maps. The area under the ROC curve (AUC = 0.863) suggests good performance of the MaxEnt model under the condition of balancing model complexity and generality. The relative importance of ore-controlling factors and their relationships with known deposits were examined by jackknife analysis and response curves. Prediction-area (P-A) curves were used to determine threshold values for demarcating high probability of tungsten polymetallic deposit occurrence within small exploration area. The final predictive map showed that high favorability zones occupy 14.5% of the study area and contain 85.5% of the known tungsten polymetallic deposits. Our study suggests that the MaxEnt model can be efficiently used to integrate multisource geo-spatial information for mineral prospectivity analysis. [ABSTRACT FROM AUTHOR]

Although alteration minerals related to metallogenesis is very important in mineral exploration, information of alteration mineral is weakly expressed in remote sensing imagery, which is often subject to interfering noise and sometimes limited in spectral and spatial resolutions. Because of easy access, moderate images are the main sources of alteration mineral information. Therefore, it is very important to develop alteration mineral information extraction methods from remote sensing images. In this paper, a combined method based on Mask, principal component analysis (PCA) and support vector machine method (SVM) was used to extract alteration mineral information from Enhanced thematic mapper plus remote sensing data with limited spectral and spatial resolutions. First, a mask image of the remote sensing imagery was created to remove interference information such as vegetation, shadow and water. Then, PCA was employed to collect sample data relating to iron, argillic, and carbonatization alteration. Finally, SVM was used to deal with alteration anomaly and build a feature extraction model of high accuracy. The Mask-PCA-SVM model is used to extract alteration mineral information from remote sensing images of Hatu area, Xinjiang Uygur Autonomous Regions, China. The results show that the new methods proposed in this paper can coincide well with known deposits occurrences, rate reached 86.51%. While, the consistent rate with known deposits of the ratio model, PCA model and Spectral angle mapper model were only 3.37, 65.08 and 69.05% respectively. This suggests that the proposed model can find the actual distribution of mineral deposits more effectively by reducing interference to a greater degree. [ABSTRACT FROM AUTHOR]

The exhumation and tectonic emplacement of eclogites and blueschists takes place in forearc accretionary complexes by either forearc- or backarc-directed extrusion, but few examples have been well analysed in detail. Here we present an example of oblique wedge extrusion of UHP/HP rocks in the Atbashi accretionary complex of the Kyrgyz South Tianshan. Our field mapping and structural analysis demonstrate that the Atbashi Eclogite–Blueschist Complex is situated in a complicated duplex formed by a northerly dextral transpression system and a southerly sinistral transtension system. The two major shear systems suggest that the Atbashi Complex was extruded obliquely southwestwards during eastward penetration of the southern tip of the Yili–Central Tianshan Arc of the Kazakhstan Orocline during the Late Triassic. Also, we report new zircon U–Pb metamorphic ages of four eclogites and one garnet-bearing quartz-schist from the Atbashi complex of 217–221 Ma and 223.9 Ma, respectively, suggesting that the main extrusion was later than previously proposed and that the final orogenesis was not completed until the Late Triassic. The HP/UHP rocks have an oblique plunge to the NE and extrusion took place southwestwards during escape tectonics along the South Tianshan accretionary wedge in the Late Triassic. Our work shows that the movement of HP/UHP rocks had a 3D style with an arc-parallel structure, and sheds light on earlier 2D models with either forearc- or backarc-directed extrusions, which indicates that more systematic structural and geochronological work is needed to characterize the accretionary tectonics of many orogens around the world. Our data on the timing of extrusion and emplacement of the Atbashi Eclogite–Blueschist Complex also help to resolve the long-standing controversy about the time of terminal orogeny of the Central Asian Orogenic Belt. [ABSTRACT FROM AUTHOR]

The Tarbagatay Complex, located in northwest Junggar, is situated tectonically between the Zharma–Saur arc to the north and the Tacheng terrane and the Boshchekol–Chingiz arc to the south. This Complex belt is variably composed of ophiolitic mélange, sedimentary mélange, and coherent units of turbidites and shallow water sediments. These rocks crop out in fault-bound slices with fault-parallel asymmetric folds. Both the lithologies and deformation features of the Tarbagatay Complex suggest an accretionary origin generally with a top-to-the-south tectonic vergence, suggesting N-dipping subduction beneath the Zharma–Saur arc. The presence of a former ocean is indicated by the Ordovician ophiolite mélanges and related marine fossils. The time duration of the Tarbagatay Complex can be bracketed by detrital zircon ages of turbidites and shallow water sediments with a lower limit of major peak ages of 350–370 Ma, and an upper limit of middle Permian indicated by detrital zircon ages of 262.3 Ma. Based on these data, we suggest that the subduction of the Tarbagatay Ocean likely started in the Late Devonian and lasted until the middle Permian. Taking into account the formation of the northern part of the Kazakhstan orocline, which has a similar temporal-spatial framework, we propose a tectonic model for the western CAOB that involves accretion and amalgamation from the Ordovician to the middle Permian. [ABSTRACT FROM PUBLISHER]

Leaf chlorophyll is an important indicator of nutritional stress, photosynthetic capacity, and growth status of plants. Therefore, it is important to accurately estimate leaf chlorophyll content over a range of spatial and temporal scales. However, traditional methods for chlorophyll measurement mainly rely on chemical analysis, which is not universally applicable to dynamic monitoring of plants in large areas because it is time consuming and requires destructive measurements. Hyperspectral remote sensing has enormous potential for accurate retrieval of plant biochemical parameters. Therefore, it has become the most popular means to retrieve chlorophyll content, by establishing empirical relationships between different vegetation indices and chlorophyll content. In recent years, many vegetation indices have been developed for the inversion of chlorophyll content. Only the vegetation indices that are less affected by the external environment are used, in order to establish a strong and robust model. Therefore, it is very important to assess the anti-disturbance ability of different vegetation indices. In this paper, a new method is proposed to quantitatively assess the anti-disturbance ability of vegetation indices. The anti-disturbance ability of several vegetation indices that are commonly used for chlorophyll estimation was evaluated using this method. We concluded that the anti-disturbance ability of VogD, TCARI/OSAVI, and Datt99 is stronger than the other vegetation indices tested. However, if a vegetation index is not sensitive to chlorophyll content, predicting chlorophyll content holds no value even though it has a strong anti-disturbance ability. Therefore, we used the slope of the best fitting function between the vegetation index and chlorophyll content (defined as d(VI)/d(Chlorophyll content)) to measure the sensitivities of different indices to chlorophyll content. Finally, we found that TCARI/OSAVI was one of the best vegetation indices to estimate chlorophyll content at the leaf level. However, we have only considered three factors to evaluate the anti-disturbance ability of different vegetation indices, which is still far from enough because the canopy reflectance is affected by many factors. Therefore, we should account for more factors in the future. [ABSTRACT FROM AUTHOR]

The Palaeozoic orogenic process in the North Tianshan of the southern Central Asian Orogenic Belt is controversial. Systematic field study indicates that the ophiolitic fragments of the North Tianshan are mainly thrust slices and blocks of a late Palaeozoic accretionary complex, which was intruded by granitoids. U-Pb zircon dating of plagiogranites from the North Tianshan ophiolite yielded a mean age of 343.1 ± 2.7 Ma. These are typical oceanic plagiogranites but with a supra-subduction zone (SSZ) signature. Ophiolitic basalts display N-MORB, E-MORB, and OIB compositions. One gabbro with an age of 301.9 ± 2.2 Ma shows E-MORB geochemistry mixed with N-MORB and OIB. Some andesites show clear island arc characters indicated by enrichment of LILEs relative to HFSEs. Mean ages of 344.9 ± 4.2 and 298.7 ± 2.4 Ma were obtained for a granite porphyry and a mylonitic granite, respectively. The two granitoids display an island arc geochemical signature evidenced by enrichment of LILEs and depletion of HFSEs. Combined with an eastward migration of Late Devonian to Carboniferous arc magmatism and related Cu-Au-Mo deposits, we propose that trench retreat and slab roll-back took place during subduction of the Junggar Ocean spreading ridge beneath the North Tianshan arc, and that the accretion may have lasted into early Permian time, an important late stage of the long-lived accretionary orogenesis in the southern Central Asian Orogenic Belt. [ABSTRACT FROM AUTHOR]

On the basis of analysing the deficiency of the relative absorption band-depth (RBD) approach, we present an improved similarity measure called weighted RBD (WRBD) applied to the extraction of iron-stained alteration information from Huan Jing-1A (HJ-1A) Hyperspectral Imaging Radiometer (HSI) data. By introducing the continuum removed reflectance (CRR) and the full width at half maximum (FWHM), the WRBD approach fully considered the non-symmetry of the reflection peaks and the effective bandwidth of each band spectrum. The results of Hatu gold ore district HSI data experiments show that using the improved WRBD images to extract alteration information improves user’s accuracy by 45%, although it is 14% lower in producer’s accuracy, compared with the RBD approach. The improved approach can more accurately reflect the alteration state and reduce exploration costs. [ABSTRACT FROM AUTHOR]

In the Gurbantünggüt Desert, snowmelt-induced high soil water contents briefly create favorable conditions for the germination and growth of plants every spring. Monitoring the rapidly changing conditions in this time period demands fast and efficient methods for measuring soil water contents at the field scale. For this study, a series of ground-penetrating radar (GPR) measurements were carried out on sites characterized by semi-vegetated dunes both in April 2010 and 2011. We compare water contents calculated from the GPR direct ground wave signal to both point scale validation measurements by time-domain reflectometry (TDR) and gravimetric sampling. Our results show that GPR is an effective method to rapidly obtain a detailed image of the field scale soil water content distribution in the Gurbantünggüt Desert with an accuracy similar to TDR. Observed large scale soil water content variations are dominated by dune topography: During snow melting, melt water was found to trickle slowly from the dune ridges to interdune valleys, increasing the soil water content there while the dune ridges quickly started to dry down. In dune valleys, smaller scale near-surface soil water content changes were dominated by variations in the vegetation coverage, leading to snowmelt funnels at distinct locations: The snowmelt initially occurred around the stems and branches of plants, forming funnel-shaped melt water induced holes through the snow cover and leading to an increasing amount of melt water collected around these plant roots. Our comparison of data from 2010 to 2011 furthermore suggests a temporally stable distribution of near-surface soil water content. This has important ecological significance for controlling desertification and for restoring and reconstructing vegetation in the Gurbantünggüt Desert. [ABSTRACT FROM AUTHOR]

The basement rocks in the Kuluketage area are composed predominately of tonalite-trondhjemite-granodiorite rocks, and occured mainly in Xinger and Korla. U-Pb dating of TTG gneiss near Korla yielded a late Neoarchean weighted mean Pb/Pb age of 2.65 Ga, which is the oldest published age for the TTG rocks in the Kuluketage area and thus suggests that Archean terrane in the area was formed in the late Neoarchean. The Korla gneiss is much younger than the TTG rocks in the northern Altyn Tagh, eastern Tarim Craton, indicating that the oldest terrane of the Tarim Craton was exposed probably in the northern Altyn Tagh. Until late Neoarchean, the Tarim continent extends to the Kuluketage area and finally had generated a relatively large uniform Archean basement within the craton. Zircon Hf isotopic analyses of the TTG gneiss give low ɛ( t) values (−5 to 1) with Paleoarchean to Mesoarchean two-stage model ages ( T) between 3.0 and 3.3 Ga, suggesting that the basement rocks in the northern Tarim Craton were derived dominately from partial melting of Paleoarchean to Mesoarchean juvenile crustal material. The Hf model ages, therefore, indicate that no continent crust older than 3.3 Ga existed in the Kuluketage area. [ABSTRACT FROM AUTHOR]

Machine learning (ML) as a powerful data-driven method is widely used for mineral prospectivity mapping. This study employs a hybrid of the genetic algorithm (GA) and support vector machine (SVM) model to map prospective areas for Au deposits in Karamay, northwest China. In the proposed method, GA is used as an adaptive optimization search method to optimize the SVM parameters that result in the best fitness. After obtaining evidence layers from geological and geochemical data, GA–SVM models trained using different training datasets were applied to discriminate between prospective and non-prospective areas for Au deposits, and to produce prospectivity maps for mineral exploration. The F1 score and spatial efficiency of classification were calculated to objectively evaluate the performance of each prospectivity model. The best model predicted 95.83% of the known Au deposits within prospective areas, occupying 35.68% of the study area. The results demonstrate the effectiveness of the GA–SVM model as a tool for mapping mineral prospectivity. [ABSTRACT FROM AUTHOR]

In this paper, we analysed the monitored data from nine groundwater-monitoring transects in the lower reaches of Tarim River during the five times of stream water deliveries to the river transect where the stream flow ceased. The results showed that the groundwater depth in the lower reaches of Tarim River rose from −9.30 m before the conveyances to −8.17 and −6.50 m after the first and second conveyances, −5.81 and −6.00 m after the third and fourth the conveyance, and −4.73 m after the fifth. The horizontal extent of groundwater recharge was gradually enlarged along both sides of the channel of conveyance, i.e., from 250 m in width after the first conveyance to 1,050 m away from the channel after the fourth delivery. With the rising groundwater level, the concentrations of major anions Cl−, SO and cations Ca2+, Mg2+, Na+, as well as total dissolved solids (TDS) in groundwater underwent a significant change. The spatial variations in groundwater chemistry indicated that the groundwater chemistry at the transect near Daxihaizi Reservoir changed earlier than that farther from it. In the same transect, the chemical variations were earlier in the monitoring well close to watercourse than that farther away from the stream. In general, the concentration of the major ions and TDS at each monitoring well increased remarkably when the water delivery started, and decreased with the continued water delivery, and then increased once again at the end of the study period. Hence, the whole study period may be divided into three stages: the initial stage, the intermediate stage and the later stage. According to the three stages of groundwater chemistry reaction to water delivery and the relationships between groundwater chemical properties and groundwater depths, we educe that under the situation of water delivery, the optimum groundwater depth in the lower reaches of the Tarim River should be −5 m. [ABSTRACT FROM AUTHOR]

According to the features of the basins in arid areas, in this paper a quantified study framework of sustainable management of water resources is developed, and the contents include mainly the quantification rules, index system, basic models and quantification method. A quantified study method (M-D method) about sustainable management of water resources is put forward based on the simulation and integrative development degree. In the method, the fuzzy subordinatness description and the multi-rule integration are used to calculate the integrative development degree so as to quantitatively describe the sustainable development degree of economic society; the mathematical simulation is used to quantitatively describe the interactions between water resources, economic society and ecosystems so as to lay a foundation for quantitatively giving expression to the development situation of economic society related to the management of water resources; based on the organic combination of these two, quantification rules and other constraint conditions, a quantified model of water resources management is developed. The M-D method is applied to developing a scientific scheme of water resources management in the Bosten Lake Basin, Xinjiang, China. [ABSTRACT FROM AUTHOR]

RS-monitoring index systems of ecological environment changes at a large scale, based on empirical data and trends in environmental change in Central Asia, are developed using NOAA and MODIS data. Moreover, with the help of mathematical statistics and GIS spatial analysis, the degrees, hazards and distribution extent of various possible ecological problems are discussed, environmental changes in Central Asia in 1990 and 2005 are separately evaluated, and dynamic changes in the environment in Central Asia over a 15-year period are analyzed. The results reveal that during the 15-year period from 1990 to 2005, areas of degenerated vegetation in Kazakhstan, Uzbekistan, Turkmenistan, Kirghizstan and Tadzhikistan were enlarged by 0.069×105 km2, 0.081×105 km2, 0.296×105 km2, 0.022×105 km2 and 0.112×105 km2, respectively. The ecological environment in Central Asia was in the state of significant degeneration and even deterioration. This study proves that NOAA and MODIS data can be used to successfully monitor the environment and provide useful results. [ABSTRACT FROM AUTHOR]