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The crop-livestock integration model is the main path for the sustainable development of agriculture and animal husbandry in China, and farmers' participation behavior is critical to the formation of this model. So this paper based on a field survey data of 615 farmers in 10 pilot counties of Crop-Livestock Integration (CLI) in the dairy industry in the east, middle, and west of Inner Mongolia, the relationship among transaction costs, farmers' decision-making of participating in the CLI model, and income effects was analyzed using the Endogenous Switching Regression (ESR) model in this paper. The results show that under the current market environment, the proportion of farmers participating in the CLI model is 37.56% of the farmer surveyed. The high costs of information searching, negotiation, and execution are the critical factors to inhibit farmers from participating in the CLI model. The results of the counterfactual test of the ESR model show that the effect of the CLI model on the income of participated farmers is not noticeable, while the effect is more significant on the income of non-participating farmers. Moreover, there is no obvious heterogeneity in the effects of the farmer level and "farmers-to-farm" level CLI models on farmers' income. Based on these conclusions, this paper proposes that the government should actively promote the establishment of the information-sharing platform and training mechanism about the CLI model, reduce farmers' costs in information searching and negotiation, optimize the incentive policy of the CLI model, incorporate the farmers planting forage into the subsidy scope of the CLI model, improve the economic benefits of farmers participating in the CLI model, and stimulate the enthusiasm of farmers participating in the CLI model, so as to effectively promote the realization of the CLI model in the animal husbandry industry. [ABSTRACT FROM AUTHOR]

An accurate estimation of canopy cover can provide an important basis for forest ecological management by understanding the forest status and change patterns. The aim of this paper is to investigate the four methods of the random forest (RF), support vector regression (SVR), k-nearest neighbor (KNN), and k-nearest neighbor with fast iterative features selection (KNN-FIFS) for modeling forest canopy cover, and to evaluate three mainstream optical data sources—Landsat8 OLI, Sentinel-2A, Gaofen-1 (GF-1)—and three types of data combined comparatively by selecting the optimal modeling method. The paper uses the Daxinganling Ecological Station of Genhe City, Inner Mongolia, as the research area, and is based on three types of multispectral remote sensing data, extracting spectral characteristics, textural characteristics, terrain characteristics; the Kauth–Thomas transform (K-T transform); and color transformation characteristics (HIS). The optimal combination of features was selected using three feature screening methods, namely stepwise regression, RF, and KNN-FIFS, and the four methods: RF, SVR KNN, and KNN-FIFS, were combined to carry out the evaluation analysis regarding the accuracy of forest canopy cover modeling: (1) In this study, a variety of remote sensing features were introduced, and the feature variables were selected by different parameter preference methods and then employed in modeling. Based on the four modeling inversion methods, the KNN-FIFS model achieves the best accuracy: the Landsat8 OLI with R2 = 0.60, RMSE = 0.11, and RMSEr = 14.64% in the KNN-FIFS model; the Sentinel-2A with R2 = 0.80, RMSE = 0.08, and RMSEr = 11.63% in the KNN-FIFS model; the GF-1 with R2 = 0.55, RMSE = 0.12, and RMSEr = 15.04% in the KNN-FIFS model; and the federated data with R2 = 0.82, RMSE = 0.08, and RMSEr = 10.40% in the KNN-FIFS model; (2) the three multispectral datasets have the ability to estimate forest canopy cover, and the modeling accuracy superior under the combination of multi-source data features; (3) under different optical data, KNN- FIFS achieves the best accuracy in the established nonparametric model, and its feature optimization method is better than that of the random forest optimization method. For the same model, the estimation result of the joint data is better than the single optical data; thus, the KNN-FIFS model, with specific parameters, can significantly improve the inversion accuracy and efficiency of forest canopy cover evaluation from different data sources. [ABSTRACT FROM AUTHOR]

This paper aims to theoretically and empirically test whether the Weather Index Insurance for Mutton Sheep (WIMS) which protects the herders from increased feeding costs resulting from drought and snow disasters promotes the income of herders in China's Inner Mongolia or not. We have applied the OLS, PSM, and quantile regression models using field survey data from 261 herders in Xilin Gol, Inner Mongolia Autonomous Region for our objective. The findings demonstrate that the WIMS significantly increases the overall and high-income herders' income, but has no significant effect on herders' income at other income levels. According to the results, we recommend that as the subsidized agricultural insurance product, the government should expand the pilot region of WIMS to furtherly test its income effect and consider reducing or exempting insurance premiums for low-income herders to reduce their financial pressure. [ABSTRACT FROM AUTHOR]

Obtaining accurate and timely crop area information is crucial for crop yield estimates and food security. Because most existing crop mapping models based on remote sensing data have poor generalizability, they cannot be rapidly deployed for crop identification tasks in different regions. Based on a priori knowledge of phenology, we designed an off-center Bayesian deep learning remote sensing crop classification method that can highlight phenological features, combined with an attention mechanism and residual connectivity. In this paper, we first optimize the input image and input features based on a phenology analysis. Then, a convolutional neural network (CNN), recurrent neural network (RNN), and random forest classifier (RFC) were built based on farm data in northeastern Inner Mongolia and applied to perform comparisons with the method proposed here. Then, classification tests were performed on soybean, maize, and rice from four measurement areas in northeastern China to verify the accuracy of the above methods. To further explore the reliability of the method proposed in this paper, an uncertainty analysis was conducted by Bayesian deep learning to analyze the model's learning process and model structure for interpretability. Finally, statistical data collected in Suibin County, Heilongjiang Province, over many years, and Shandong Province in 2020 were used as reference data to verify the applicability of the methods. The experimental results show that the classification accuracy of the three crops reached 90.73% overall and the average F1 and IOU were 89.57% and 81.48%, respectively. Furthermore, the proposed method can be directly applied to crop area estimations in different years in other regions based on its good correlation with official statistics. [ABSTRACT FROM AUTHOR]

Satellite laser altimetry technology, a novel space remote sensing technique, actively acquires high-precision elevation information about the Earth's surface. However, the accuracy of laser altimetry can be compromised by alterations in the satellite-ground environment, thermal dynamics, and cosmic radiation. These factors may induce subtle variations in the installation and internal structure of the spaceborne laser altimeter on the satellite platform, diminishing measurement precision. In-orbit calibration is thus essential to enhancing the precision of laser altimetry. Through collaborative calculations between satellite and ground stations, we can derive correction parameters for laser pointing and ranging, substantially improving the accuracy of satellite laser altimetry. This paper introduces a sophisticated calibration method for laser altimeter pointing and ranging that utilizes dense control points. The approach interpolates discrete ground control point data into continuous simulated terrain using empirical Bayesian kriging, subsequently categorizing the data for either pointing or ranging calibration according to their respective functions. Following this, a series of calibration experiments are conducted, prioritizing "pointing" followed by "ranging" and continuing until the variation in the ranging calibration results falls below a predefined threshold. We employed experimental data from ground control points (GCPs) in Xinjiang and Inner Mongolia, China, to calibrate the GaoFen-7 (GF-7) satellite Beam 2 laser altimeter as per the outlined method. The calibration outcomes were then benchmarked against those gleaned from infrared laser detector calibration, revealing disparities of 1.12 s in the pointing angle and 2 cm in the ranging correction value. Post validation with ground control points, the measurement accuracy was refined to 0.15 m. The experiments confirm that the proposed calibration method offers accuracy comparable to that of infrared laser detector calibration and can facilitate the updating of 1:10,000 topographic maps utilizing stereo optical imagery. Furthermore, this method is more cost-effective and demands fewer personnel for ground control point collection, enhancing resource efficiency compared to traditional infrared laser detector calibration. The proposed approach surpasses terrain-matching limitations when calibrating laser ranging parameters and presents a viable solution for achieving frequent and high-precision in-orbit calibration of laser altimetry satellites. [ABSTRACT FROM AUTHOR]

As urban economies flourish and populations become increasingly concentrated, urban surface deformation has emerged as a critical factor in city planning that cannot be overlooked. Surface deformation in urban areas can lead to deformations in structural supports of infrastructure such as road bases and bridges, thereby posing a serious threat to public safety and creating significant safety hazards. Consequently, research focusing on the monitoring of urban surface deformation holds paramount importance. Interferometric synthetic aperture radar (InSAR), as an important means of earth observation, has all-day, wide-range, high-precision, etc., characteristics and is widely used in the field of surface deformation monitoring. However, traditional solitary InSAR techniques are limited in their application scenarios and computational characteristics. Additionally, the manual selection of ground control points (GCPs) is fraught with errors and uncertainties. Permanent scatterers (PS) can maintain high interferometric coherence in man-made building areas, and distributed scatterers (DS) usually show moderate coherence in areas with short vegetation; the combination of DS and PS solves the problem of manually selecting GCPs during track re-flattening and regrading, which affects the monitoring results. In this paper, 45 Sentinel-1B data from 16 February 2019 to 14 December 2021 are used as the data source in the urban area of Horqin District, Tongliao City, Inner Mongolia Autonomous Region, for example. A four-threshold (coherence coefficient threshold, FaSHPS adaptive threshold, amplitude divergence index threshold, and deformation velocity interval) GCPs point screening method for PS-DS, as well as a Small Baseline Subset-Permanent Scatterers-Distributed Scatterers-Interferometric Synthetic Aperture Radar (SBAS-PS-DS-InSAR) method for selecting PS and DS points as ground control points for orbit refinement and re-flattening, are proposed. The surface deformation results obtained using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) and the SBAS-PS-DS-InSAR proposed in this paper were comparatively analysed and verified. The maximum cumulative line-of-sight settlements were −90.78 mm and −83.68 mm, and the maximum cumulative uplifts are 74.94 mm and 97.56 mm, respectively; the maximum annual average line-of-sight settlements are −35.38 mm/y and −30.38 mm/y, and the maximum annual average uplifts are 25.27 mm/y and 27.92 mm/y. The results were evaluated and analysed in terms of correlation, mean absolute error (MAE), and root mean square error (RMSE). The deformation results of the two InSAR methods were evaluated and analysed in terms of correlation, MAE, and RMSE. The errors show that the Pearson correlation coefficients between the vertical settlement results obtained using the SBAS-PS-DS-InSAR method and the GPS monitoring results were closer to 1. The maximum MAE and RMSE were 13.7625 mm and 14.8004 mm, respectively, which are within the acceptable range; this confirms that the monitoring results of the SBAS-PS-DS-InSAR method were better than those of the original SBAS-InSAR method. SBAS-InSAR method, which is valid and reliable. The results show that the surface deformation results obtained using the SBAS-InSAR, SBAS-PS-DS-InSAR, and GPS methods have basically the same settlement locations, extents, distributions, and temporal and spatial settlement patterns. The deformation results obtained using these two InSAR methods correlate well with the GPS monitoring results, and the MAE and RMSE are within acceptable limits. By comparing the deformation information obtained using multiple methods, the surface deformation in urban areas can be better monitored and analysed, and it can also provide scientific references for urban municipal planning and disaster warning. [ABSTRACT FROM AUTHOR]

Agricultural drought events have become more frequent in the Inner Mongolia inland river basin in recent years, and the spatio-temporal evolution characteristics and development rules can be accurately and comprehensively understood using the three-dimensional identification method. In this paper, standardized soil moisture index (SSMI) was used to characterize agricultural drought, and modified Mann–Kendall trend test (MMK) and 3D recognition of drought events were used to analyze the spatio-temporal evolution characteristics of agricultural drought events in this basin and reveal the drought development law. The relationships between drought and temperature (T), precipitation (P), evapotranspiration (E), and humidity (H) were analyzed using a cross-wavelet method. The results are as follows: (1) When the time scale of agricultural drought was short (monthly scale), the alternations of dry and wet were frequent, but the SSMI index of all scales showed a downward trend; (2) The spatial distribution characteristics of drought change trend in four seasons were similar, but the area with a significant downward trend of drought in spring was the largest, and the area of high frequency region was also the largest, and the drought trend was the most obvious; (3) The most serious agricultural drought event occurred from October 2000 to May 2002, and reached its maximum value in September 2001 (drought area and drought severity of 2.26 × 105 km2 and 3.61 × 105 months·km2, respectively), which mainly experienced five processes—drought onset–intensification–decay–re-intensification–termination—and the migration path of the drought center showed the characteristics of southwest–northeast transmission; (4) All the four meteorological factors were correlated with SSMI, and P had a greater impact on SSMI. This article aims to reveal the spatio-temporal evolution of agricultural drought events in the Inner Mongolia inland river basin, and provide a new way to accurately evaluate the spatio-temporal evolution of drought. [ABSTRACT FROM AUTHOR]

In pastoral society, the reproduction of livestock is directly related to the survival and prosperity of herders. The key to domestic animal reproduction lies in the cognitive bond between mother livestock and their young. Herdsmen use various tools and techniques to help develop this cognitive bond. These human mediation tools have various characteristics such as 'restorative' or 'destructive'. The lamb bag, a widely used tool in pastoral society, has both 'restorative' and 'destructive' natures. Based on ethnographic data collected in Inner Mongolia, China, this paper first introduces the production method of lamb bags, then describes their structure, function and the multi-dimensional relationships generated during the application process, and finally discusses the cultural implications of 'restorative' and 'destructive' human mediation in pastoral culture. [ABSTRACT FROM AUTHOR]

Agricultural insurance is a risk management tool developed to guarantee regional production and national food security. Based on survey data from 629 households in the Inner Mongolia autonomous region, China, this paper examines the impact of agricultural insurance on farmers' planting structure. The results show that: (1) Farmers' participation in agricultural insurance significantly affects their planting structure, especially lowering the level of specialization in production; insured households are about 3–6% lower than the non-insured, and there is a complementary effect between insurance participation and diversified planting. (2) For different types of farmers, participating in insurance has different effects on their agricultural production structure. Farmers purchasing insurance with low or medium levels in proportion to agricultural income significantly reduce the degree of production specialization. The effect of participation in insurance on large-scale farmers' adjustment of planting structure is more obvious. For pure grain farmers, participation in insurance will reduce planting specialization by about 3–4%. (3) Participation in agricultural insurance will encourage farmers to plant grain crops, but the effect is small. Therefore, we need to expand the coverage areas, increase insurance types, and improve coverage levels; the products should be more targeted and differentiated, strengthening farmers' participation in complete cost insurance and income insurance. [ABSTRACT FROM AUTHOR]

In order to study the correlation between the vegetation coverage of typical grassland and the thickness of chestnut calcium soil layer, three typical geomorphic types of Wuzhumuqin typical grassland in Inner Mongolia were selected as experimental plots. It uses 3S technology and the methods of landscape ecology and geostatistics to test the image data and field quadrat in the past three years. It closely combines vegetation ecology with soil environment, the relationship between soil characteristics and vegetation landscape, and makes a correlation analysis on the synergistic evolution of chestnut soil thickness. The relationship between chestnut soil thickness, soil water content, and vegetation coverage under three different geomorphic conditions was obtained. Based on the quantitative analysis of the temporal and spatial differences between the vegetation coverage of typical grassland and the thickness of chestnut soil, the spatial distribution patterns of different soil types are revealed. Based on Landsat 8 TM image data, this paper makes statistics of vegetation index (NDVI) at three test sites. The spatial overlap method and the actual observation data are abandoned for spatial interpolation, and the similarity conclusion is obtained. The study shows that among the three sample plots in 2021, except for the original wavy high flat sample plot whose natural environment has been greatly damaged, the correlation coefficient between chestnut calcium soil layer thickness and vegetation coverage in the other two sample plots is also significant in the significance of 0.01 or 0.05 (two-sided test). It shows that there is a very significant positive correlation between the thickness of chestnut calcium soil layer and the thickness of chestnut calcium soil layer. The purpose of this paper is to use hyperspectral images to classify different kinds of plants, so as to realize the monitoring of chestnut soil. It will provide rapid and dynamic technical support for desertification control in the future. [ABSTRACT FROM AUTHOR]

The problem of dust pollution in the open-pit coal mine significantly impacts the health of staff, the regular operation of mining work, and the surrounding environment. At the same time, the open-pit road is the largest dust source. Therefore, it analyzes the influencing factors of road dust concentration in the open-pit coal mine. It is of practical significance to establish a prediction model for scientific and effective prediction of road dust concentration in the open pit coal mine. The prediction model helps reduce dust hazards. This paper uses the hourly air quality and meteorological data of an open-pit coal mine in Tongliao City, Inner Mongolia Autonomous Region, from January 1, 2020, to December 31, 2021. Create a CNN-BiLSTM-Attention multivariate hybrid model consisting of a Convolutional Neural Network (CNN), a bidirectional long short-term memory neural network (BiLSTM), and an attention mechanism, Prediction of PM2.5 concentration in the next 24h. Establish prediction models of parallel and serial structures, and carry out many experiments according to the change period of the data to determine the optimal configuration and the input and output size. Then, a comparison of the proposed model and Lasso regression, SVR, XGBoost, LSTM, BiLSTM, CNN-LSTM, and CNN-BiLSTM models for short-term prediction (24h) and long-term prediction (48h, 72h, 96h, and 120h). The results show that the CNN-BiLSTM-Attention multivariate mixed model proposed in this paper has the best prediction performance. The mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) of the short-term forecast (24h) are 6.957, 8.985, and 0.914, respectively. Evaluation indicators of long-term forecasts (48h, 72h, 96h, and 120h) are also superior to contrast models. Finally, we used field-measured data to verify, and the obtained evaluation indexes MAE, RMSE, and R2 are 3.127, 3.989, and 0.951, respectively. The model-fitting effect was good. [ABSTRACT FROM AUTHOR]

Lifespan of fine roots plays important roles in regulating carbon (C) cycling in terrestrial ecosystems. Determination of root lifespan and elucidation of its regulatory mechanism in different plant communities are essential for accurate prediction of C cycling from ecosystem to regional scales. Temperate steppes in Inner Mongolia grasslands have three major types, i.e., Stipa krylovii, Stipa grandis and Stipa breviflora grasslands. There have been no studies to compare the root dynamics among the three types of grasslands. In the present study, we determined root lifespan of the three grasslands using the rhizotron. We found that root lifespan differed substantially among the three types of grasslands within the temperate steppes of Inner Mongolia, such that root lifespan of Stipa breviflora > Stipa grandis > Stipa krylovii grasslands. Root lifespan across the three types of grasslands in the Inner Mongolian temperate steppes displayed a similar temporal pattern, i.e. lifespan of the roots produced in spring and autumn was shortest and longest, respectively, whereas lifespan of summer-produced roots was between that of roots produced in spring and autumn. The spatial and temporal differences in root lifespan across the three types of grasslands were mainly determined by contents of soluble sugars in roots of the dominant species. The differences in root lifespan across the major types of grasslands and different seasons highlight the necessity to take into account these differences in the prediction of C cycling within grassland ecosystem by the simulating model. [ABSTRACT FROM AUTHOR]

Enhanced deposition of atmospheric nitrogen (N) resulting from anthropogenic activities has negative impacts on plant diversity in grassland ecosystems globally. Several mechanisms have been proposed to explain the species loss. Ion toxicity due to N deposition-induced soil acidification has been suggested to be responsible for species loss in acidic grasslands, while few studies have evaluated the role of soilmediated homeostasis of ions in species loss under elevated N deposition in alkaline grasslands. To determine whether soil-mediated processes are involved in changes in species composition by N deposition, the effects of 9 yrN addition on soil properties, aboveground biomass (AGB) and species composition were investigated in an Inner Mongolia steppe. Low to moderate N addition rate (2, 4, 8 g N m-2 yr-1) significantly enhanced AGB of grasses, while high N addition rate (> 16 g N m-2 yr-1) reduced AGB of forbs, leading to an overall increase in AGB of the community under low to moderate N addition rates. Forb richness was significantly reduced by N addition at rates greater than 8 gNm-2 yr-1, while no effect of N addition on grass richness was observed, resulting in decline in total species richness. N addition depleted base cations (Ca2+, Mg2+ and K+) in soils, reduced soil pH and mobilized Mn2+, Fe3+ and Cu2+ ions in soils. Soil inorganic-N concentration was negatively correlated with forb richness, explaining 27.2% variation of forb richness. The concentrations of base cations (Ca2+ and Mg2+) and metal ions (Mn2+ and Cu2+) showed positively and negatively linear correlation with forb richness, accounting for 25.9 and 41.4% variation of forb richness, respectively. These results reveal that disruption of metal ion homeostasis in soils by N addition, particularly enhanced release of soil Mn2+ and Cu2+ may be associated with reduction in forb richness in temperate steppe of Inner Mongolia. [ABSTRACT FROM AUTHOR]

China's coal industry has long faced challenges due to imbalance between supply and demand divisions and the discrepancies between supply and demand prices. Research on optimizing coal transfer amid fluctuating coal prices is crucial for enhancing coal resource allocation, ensuring a balanced and stable supply of coal resources, and promoting the sustainable development of the coal industry. This paper focuses on optimizing coal transfer schemes within a comprehensive transportation system, considering fixed transportation routes and opening times of railroad transportation and waterway transportation, with road transportation serving as a supplementary network. A three-dimensional spatio-temporal network model is established to represent the spatial and temporal paths and transportation modes of coal logistics. The study uses the coal transportation network from Inner Mongolia and Shaanxi to East China as a case study, analyzing factors such as coal price fluctuation, transportation rates, and the ratio of self-produced to purchased coal at the production end via sensitivity analysis. The findings indicate that the proposed model can effectively guide transportation practices under the integrated production, transportation, and sales framework in the energy industry. Additionally, it shows that enterprises can achieve higher profits and maintain revenue and supply stability despite coal price fluctuations, aligning with the coal industry's transformation and development in the current context. [ABSTRACT FROM AUTHOR]

To investigate the spatial and temporal changes in fractional vegetation coverage (FVC) and their driving forces in different regions of the Inner Mongolia section of the Yellow River Basin, this paper observed the spatial trends and stability of FVC in these regions based on the MOD13Q1 information regarding the 2000–2020 period as a data source. It used the dimidiate pixel model to invert FVC, and based on the centre of gravity migration model, the coefficient of variation and the Mann–Kendall and Sen's slope estimator test, it studied the spatial variation trend and stability of FVC in the four relevant areas of the Inner Mongolia section; an attribution analysis using a geodetector was also conducted. The following results were found: (1) in terms of temporal FVC change in the relevant areas, from 2000 to 2020, the overall FVC showed an increasing trend, indicating an obvious hierarchy of change as per different seasonal scales (summer > growing season > fall > spring). There is a mutation point in FVC in different areas, and the FVC sequence is random. (2) Regarding spatial change, the overall FVC showed a trend of being high in the eastern regions and low in the western regions and low–high–low from the north to the south; the stability of the Hetao Irrigation District–Wuliangsuhai Area changed more significantly with the successive seasons, and the degraded areas of FVC were mainly distributed in the city centre of the Kundulun River–Daheihe River Area and in the Hetao Irrigation District in the summer. (3) In terms of driving factors, soil type had a relatively higher explanatory power regarding the Hetao Irrigation District–Wuliangsuhai Area, rainfall had a relatively higher explanatory power regarding the Morin River–Wuding River Area and the Kundulun River–Daheihe River Area, and land use had a relatively higher explanatory power regarding the Ten Kongtui–Heidaigou Area. [ABSTRACT FROM AUTHOR]

Objective The increase in atmospheric CO2 and the associated global warming is expected to affect plant growth and development. This paper investigates the spatiotemporal variation in vegetation phenological traits and peak NDVI of plants in Hetao Irrigation District in Inner Mongolia. [Method] The analysis was based on MOD13Q1 data from 2001 to 2021. The impact of climatic factors on spatiotemporal variation in the start of season SOS, the end of season (EOS), the length of season (LOS), the peak of season (POS), and the normalized difference vegetation index (NDVI) of the vegetations in the region was analyzed using the two-logistic and four-parameter model. [Result] The SOS started from the end of May to the middle of June, and ended from the middle of September to the beginning of October. The annual peak LOS and POS ranged from 95 to 116 days, and from 200 to 220 days, respectively. The annual peak NDVI ranged from 0.5-0.7. Climate change delayed the onset of SOS, reduced LOS, and elevated peak NDVI. Additionally, the delayed SOS contributed to the decrease in LOS. The changes in EOS and POS with climate were consistent. SOS, EOS and POS were negatively correlated to temperature and positively correlated to precipitation. The peak NDVI was positively correlated to temperature and precipitation. [Conclusion] The vegetation phenology and peak NDVI in the Hetao Irrigation District were spatially heterogeneous, and the impact of climatic factors on them also varied. [ABSTRACT FROM AUTHOR]

[Objective] A pre-planting border irrigation in spring coupled with a drip irrigation in summer during crops growth season is an irrigation technique to reduce soil salinity and safeguard crops growth in the salt-affected soils in the Hetao Irrigation District in Inner Mongolia. This paper investigates the impact of different combinations of irrigation amounts in the dual irrigations on changes in soil water and salt, as well as the growth of sunflower. [Method] The field experiment compared two spring (S) irrigation amounts: 95 mm and 135 mm, and three summer (W) irrigation amounts: 68, 100 mm and 135 mm. In each treatment, we measured the spatiotemporal changes in soil water and salt, as well as crop growth characteristics. [Result] ① The soil water content in the S135W135 treatment was the highest among all treatments during the experimental period, with the average soil water content and saturation being 17.10% and 75.53%, respectively. The coefficient of variation of soil water content in the S95W135 treatment was 22.40%, the lowest among all treatments. ② Depending on the summer irrigation amount, the desalination rate of the 0-80 cm soil layer under S135 and S95 varied from 32.64% to 50.50% and 21.8% to 38.87%, respectively. Although the spring irrigation amounts did not significantly affect immediate post-irrigation salt content, the S135W100 and S95W135 combinations showed deeper leaching depths and higher desalination rates (40.77% and 33.37%, respectively) than other treatments. ③ Aboveground dry matter production was significantly higher in the S95W135 and S135W100 combinations than in other combinations, surpassing the S135W135 combination by 10.55% and 9.94%, respectively. The S135W100 combination achieved the highest water use efficiency at 21.59%, an increase of 13.03% compared to S135W135. [Conclusion] Reducing spring irrigation by 30% to 95 mm combined with a summer drip irrigation of 135 mm is the most efficient irrigation scheme for sunflower cultivation in the salt-affected soils in the Hetao Irrigation District. [ABSTRACT FROM AUTHOR]

The coordinated development of agriculture and tourism is very important. On the basis of the index system of the predecessors, the development effect index after the integration of the subsystems is added, so as to construct the evaluation index system of the integrated development of agriculture and tourism in Inner Mongolia. The entropy weight method is used to set the weight value for each index, and the panel data from 2001 to 2019 collected from the Inner Mongolia Statistical Yearbook and the China Yearbook are analyzed with the coupled coordination degree model. The research results show that the development of agriculture and tourism in Inner Mongolia has been highly coupled since 2004; it has been reluctantly coordinated from 2007 until 2019 to achieve high-quality coordination; from 2001 to 2011, the development of tourism lagged behind the development of agriculture, while after 2012, the development of agriculture has been lagging behind the tourism industry. Wang (Asia Pac J Tour Res 24(6):550–562, 2019), Li and Du (Sustainability 13(10), 2021) had got similar conclusions. The article puts forward suggestions from two aspects. On the one hand, using the tourism as the trigger for the development of agriculture tourism by developing more agricultural-related tourism products so as to fully tap the tourism attributes of agriculture. The marketing of tourism products should be consciously inclined to agriculture; on the other hand, the promoting the development of tourism can be realized by adopting modern agriculture, which includes cultivating new types of large agricultural households, supporting the development of large and medium-sized farms, promoting the development of green agriculture and industrialized and three-dimensional agriculture. The modern agriculture can be deeply integrated with the tourism industry, thereby promoting the development of tourism. The research results and suggestions put forward in this paper have certain reference significance for the coordinated development of agriculture and tourism in Inner Mongolia and Southeast Asia. [ABSTRACT FROM AUTHOR]

Taking the Jiefangzha irrigation area of the Inner Mongolia Autonomous Region as the research area, the response relationships between the backscattering coefficient and radar frequency, radar incidence angle, root-mean-square height, correlation length, and soil water content under different conditions were simulated using advanced integral equations. The backscattering characteristics of exposed surfaces in cold and dry irrigation areas were discussed, and the reasons for the different effects were analyzed. Based on this, surface roughness models and statistical regression moisture inversion models were constructed through co-polarized backscatter coefficients and combined surface roughness. The correlation between the inverted surface roughness values and the measured values was R2 = 0.7569. The correlation between the soil moisture simulation values and the measured values was R2 = 0.8501, with an RMSE of 0.04. The findings showed a strong correlation between the values from the regression simulation and the measured data, indicating that the model can be applied to soil moisture inversion and has a good inversion accuracy. Compared with previous studies in the same area, the inversion model proposed in this paper has a higher accuracy and is more suitable for the inversion of soil moisture in the Jiefangzha irrigation area. These findings can support research on the water cycle and water environment assessment in the region. [ABSTRACT FROM AUTHOR]

The general requirements of China's rural revitalization strategy are industrial prosperity, ecological livability and rich life. However, the traditional livestock breeding model has struggled to balance the dual requirements of production development and ecological protection, and it is urgent to inject new impetus and explore new development paths. At present, e-commerce has become a bridge between pastoral areas and cities, herdsmen and consumers. E-commerce participation is not only an important starting point for herdsmen to increase the added value and profit space of livestock products, but also an effective way to change the original breeding behavior based on the premise of destroying grassland. Therefore, this paper presents an in-depth study on the issue of e-commerce enabling grassland ecological restoration, aiming to provide more scientific and effective guidance for e-commerce to be used to achieve a win–win situation in economy and ecology. Therefore, based on the data of 271 herdsmen in pastoral areas of Inner Mongolia, we used the OLS model and the two-stage least squares (2SLS) method to identify the direct impact of herdsmen's e-commerce participation on grassland utilization pressure. The empirical results show that e-commerce participation can significantly decrease the grassland utilization pressure. The conclusion was still valid after alleviating endogeneity and conducting a robustness test. The results of a mechanism analysis suggest that the reduction effect of e-commerce participation on grassland utilization pressure is mainly due to price incentive, reputation incentive and place identity. Subjective norms can strengthen the inhibitory effect of e-commerce participation on grassland utilization pressure. Furthermore, a heterogeneity analysis demonstrates that e-commerce participation has a better, decreased impact on the grassland utilization pressure on the banners of China's rural e-commerce demonstration county program. Under a counterfactual assumption, if herdsmen who can participate in e-commerce choose not to do this, their grassland utilization pressure will increase. [ABSTRACT FROM AUTHOR]

The Shuangjianzishan silver polymetallic deposit is located in the copper–tin–lead–zinc–silver polymetallic metallogenic belt in the Southern Great Xing'an Range, with silver resources of more than 18,000 t, which is the largest silver polymetallic deposit in Asia. Early studies concluded that the Shuangjianzishan deposit is typically an epithermal Ag-Pb-Zn deposit that lacks a high-temperature mineralization stage. In recent years, with the deepening of research, a large amount of Cu-Sn mineralization has been found in the deep part of the Shuangjianzishan deposit, but it is less studied. The laser-ablation inductively coupled mass spectroscopy (LA-ICP-MS) technique is used to investigate the distribution and substitution of trace elements in chalcopyrite and cassiterite. In this paper, the trace element study of chalcopyrite and cassiterite from the Shuangjianzishan deposit reveals that Sn, In, As, Se, Sb, and Tl mainly exist in chalcopyrite in isomorphic form, while Pb, Bi, and Ni mainly exist in chalcopyrite in the form of mineral inclusions. The enrichment of the high-temperature elements Sn and Se in chalcopyrite, and the deficit of the middle- and low-temperature elements Ga, Sb, etc., reflect that the chalcopyrite in the Shuangjianzishan deposit was formed in a middle- and high-temperature environment, and it also indicates that the early ore-forming hydrothermal solution may be rich in Sn. Fe, In, Co, and Ni mainly exist in cassiterite in isomorphic form, and the content of W in cassiterite is high. There are two main forms, one is isomorphic and the other is wolframite inclusion. Cassiterite has Fe-rich and W-U-poor characteristics, indicating that cassiterite from the Shuangjianzishan deposit was formed under relatively oxidized conditions, and the relative enrichment of elements such as Fe, W, Zr, and Hf indicates that the temperature of cassiterite formation was high. The elemental content and inter-ionic coupling relationships suggest that the cassiterite from the Shuangjianzishan deposit may have an elemental replacement mechanism of W6+ + Fe2+ ↔ 2Sn4+ or Fe3+ + OH− ↔ Sn4+ + O2−. The trace elements in cassiterite of the Shuangjianzishan deposit are rich in Fe and Mn and depleted in Nb and Ta, according to the Fe-W diagram, and the tin mineralization of the Shuangjianzishan deposit belongs to cassiterite–sulfide-type tin mineralization. Chalcopyrite Co/Ni ratios >1 are consistent with the characteristics of chalcopyrite genesis in hydrothermal deposits. [ABSTRACT FROM AUTHOR]

For the Jiawula lead–zinc deposit, as easily accessible resources become depleted, mines are becoming deeper to replenish ore reserves. Identifying large, continuous, and high-grade ore bodies in deep areas has become a daunting problem. Moreover, separating lead–zinc-bearing complex ore bodies from waste material and extracting them from associated minerals are also difficult. Thus, pioneering exploratory strategies and technological methodologies are required to make breakthroughs in mineral discovery. Based on extensive-scale structural lithofacies mapping, this paper uses short-wave infrared (SWIR) spectroscopy technology to investigate hydrothermal alteration minerals in the mining area. It has identified a total of 16 hydroxyl-bearing alteration minerals, including chlorite, muscovite, illite, calcite, ankerite, kaolinite, and smectite. These minerals establish zoning characteristics around the ore bodies and on their flanks. They comprise a segmented assemblage that follows the pattern of comb-textured quartz–illite–chlorite–carbonate → muscovite–illite–chlorite–ankerite → illite–smectite–chlorite → chlorite–kaolinite–calcite. Deep-zone illitization with a lower Al–OH absorbance peak wavelength (<2206 nm) and higher crystallinity indices (>1.1) and chloritization with higher Fe–OH absorbance peak wavelengths (>2254) and higher crystallinity indices (>3.0) are indicators of potential hydrothermal centers in the deeper regions. By finding hydrothermal centers and connecting their spatial distribution with existing ore bodies, a pertinent relationship between diabase + andesite, Fe-chlorite + illite, and high-grade mineralization has been established. They correspond well with the lithology-alteration mineralization. This research provides a basis for predicting the positioning of concealed ore bodies deep inside a mine or at the periphery. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanisation, urban areas are subject to the combined effects of the accumulation of various natural factors, such as changes in temperature leading to the thermal expansion or contraction of surface materials (rock, soil, etc.) and changes in precipitation and humidity leading to an increase in the self-weight of soil due to the infiltration of water along the cracks or pores in the ground. Therefore, the subsidence of urban areas has now become a serious geological disaster phenomenon. However, the use of traditional neural network prediction models has limitations when examining the causal relationships between time series surface deformation data and multiple influencing factors and when applying multiple influencing factors for predictive analyses. To this end, Sentinel-1A data from March 2017 to February 2023 were used as the data source in this paper, based on time series deformation data acquired using the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique. A sparrow search algorithm–convolutional neural network–long short-term memory (SSA-CNN-LSTM) neural network prediction model was built. The six factors of temperature, humidity, precipitation, and ground temperature at three different depths below the surface (5 cm, 10 cm, and 15 cm) were taken as the input of the model, and the surface deformation data were taken as the output of the neural network model. The correlation between the spatial and temporal evolution characteristics of the ground subsidence in urban areas and various influencing factors was analysed using grey correlation analysis, which proved that these six factors contribute to some extent to the deformation of the urban surface. The main urban area of Hohhot City, Inner Mongolia Autonomous Region, was used as the study area. In order to verify the efficacy of this neural network prediction model, the prediction effects of the multilayer perceptron (MLP), backpropagation (BP), and SSA-CNN-LSTM models were compared and analysed, with the values of the correlation coefficients of the feature points of A1, B1, and C1 being in the range of 0.92, 0.83, and 0.93, respectively. The results show that compared with the traditional MLP and BP neural network models, the SSA-CNN-LSTM model achieves a higher performance in predicting time series surface deformation data in urban areas, which provides new ideas and methods for this area of research. [ABSTRACT FROM AUTHOR]

Forest fires are a type of disaster with both human and natural factors; they differ from other forest disasters, in that they can cause significant damage not only to the ecological environments but also to the economy and society in many irreversible ways. While the risk factor of forest fires has been large, systematic studies on economic losses caused by forest fires have been lacking in recent years, and there is also a lack of analysis on forest fire economic losses in both spatial and temporal dimensions. Therefore, based on the forest fire data from 2006 to 2018, this paper establishes a forest fire economic loss evaluation system to calculate the economic losses in China and analyzes the spatial distribution characteristics and change trends of the forest fire economic losses in each province through thermal mapping. The results show the following. (1) The economic loss from forest fires in China is generally characterized by a fluctuating decline, but anomalous values due to human factors may occur. (2) The spatial heterogeneity of economic loss in China's provinces is limited by many factors, such as the differences in resource endowments, showing the characteristics of "low in the eastern and western regions and high in the central region". (3) Forest fires in China cause the most serious losses to forest ecological benefits. (4) Forest resources and fires are not independent of each other between regions, and areas with similar economic losses related to forest fires are often found in blocks. (5) Although the overall economic losses caused by forest fires in China are fluctuating and decreasing, some provinces are showing signs of increasing economic losses, most notably in Inner Mongolia. Therefore, this paper suggests targeted recommendations based on forest fires in different regions and with reference to the changing trends of economic loss caused by forest fires. For low-loss areas, we can further reduce the economic loss per unit area while ensuring that the losses do not increase any further. For high-loss areas, the main focus should be to find the weak points in the adaptation to forest fires. The right way to permanently reduce the damage caused by forest fires is to improve the adaptive and symbiotic capacity of the ecosystems and residential communities in relation to fires in a targeted manner and to improve the capacity for quick economic recovery after a fire. [ABSTRACT FROM AUTHOR]

As a raw material for clean energy supply for the new generation, the soybean is conducive to the realization of global energy transition and sustainable development in the context of "carbon neutrality". However, global warming has been affecting soybean yields in recent years. How to clarify the correlation between meteorological factors and soybean yields, so as to ensure the security of soybean growth and development and the stability of renewable energy development, is a key concern of the government and academia. Based on the data of temperature, precipitation, sunshine duration and active accumulated temperature during the soybean growing season in Hulunbuir, Inner Mongolia Autonomous Region from 1951 to 2019, and soybean yield data of the city from 1985 to 2019, this paper adopted statistical methods such as the Trend Analysis Method, the Rescaled Range Analysis Method and so on to analyze the trends of yield changes, characteristics of abrupt changes and periodic patterns of climate factors and soybean yields in Hulunbuir. A Pearson Correlation Analysis and a Grey Relation Analysis were used to explore the correlation between climatic factors and soybean yields, followed by a comprehensive impact model of the combined effect of temperature and precipitation on soybean yields established by the Method of Integral Regression. The results showed that temperature and active accumulated temperature are the dominant factors affecting soybean yields in Hulunbuir, while the decrease in precipitation is unfavorable to the improvement of soybean yields. Meanwhile, temperature and precipitation have different effects on the growth and development of the soybean at different stages. The conclusion of this paper is of great practical significance for Hulunbuir to promote the sustainable development of clean energy. [ABSTRACT FROM AUTHOR]

Improving the operating income of farmers and herdsmen is an important starting point for achieving common prosperity. As a common form of learning and an important source of skills training, informal learning has a certain impact on the economy and income level of farmers and herdsmen. This paper takes 439 herdsmen in three cities of the Inner Mongolia Autonomous Region as the research object and tries to explore the comprehensive influence, subdivision difference, and mechanism of informal learning on the operating income of herdsmen on the theoretical and empirical levels. The results show that the impact of informal learning on the operating income of herdsmen is "inverted U-shaped", and there is an informal learning balance point of 2.9776 h, which maximizes the effect of informal learning on the increased operating income of herdsmen. After using the instrumental variable method to deal with endogeneity and conducting robustness tests through winsorizing, quantile regression, and substitution variables, the research conclusions were still valid. Heterogeneity analysis found that informal learning has a significant impact on the increase in operating income of herdsmen in the low human capital group, reflecting the role of "sending charcoal in the snow". However, it has no significant effect on the increase in operating income of herdsmen in the high human capital group, and the effect of "icing on the cake" is not obvious. In view of this result, government departments should speed up the planning of Internet infrastructure construction in pastoral areas, and accurately push the knowledge and skills needs of herdsmen to help increase the operating income of herdsmen. [ABSTRACT FROM AUTHOR]

With the wide application of remote sensing technology, target detection based on deep learning has become a research hotspot in the field of remote sensing. In this paper, aimed at the problems of the existing deep-learning-based desert land intelligent extraction methods, such as the spectral similarity of features and unclear texture features, we propose a multispectral remote sensing image desert land intelligent extraction method that takes into account band information. Firstly, we built a desert land intelligent interpretation dataset based on band weighting to enhance the desert land foreground features of the images. On this basis, we introduced the deformable convolution adaptive feature extraction capability to U-Net and developed the Y-Net model to extract desert land from Landsat remote sensing images covering the Inner Mongolia Autonomous Region. Finally, in order to analyze the spatial and temporal trends of the desert land in the study area, we used a structural equation model (SEM) to evaluate the direct and indirect effects of natural conditions and human activities, i.e., population density (PD), livestock volume (LS), evaporation (Evp), temperature (T), days of sandy wind conditions (LD), humidity (RH), precipitation (P), anthropogenic disturbance index (Adi), and cultivated land (CL). The results show that the F1-score of the Y-Net model proposed in this paper is 95.6%, which is 11.5% more than that of U-Net. Based on the Landsat satellite images, the area of desert land in the study area for six periods from 1990 to 2020 was extracted. The results show that the area of desert land in the study area first increased and then decreased. The main influencing factors have been precipitation, humidity, and anthropogenic disturbance, for which the path coefficients are 0.646, 0.615, and 0.367, respectively. This study will be of great significance in obtaining large-scale and long-term time series of desert land cover and revealing the inner mechanism of desert land area change. [ABSTRACT FROM AUTHOR]

Among the methods used to describe soil-available water in terms of yield, field water capacity and permanent wilting coefficient were considered as the upper and lower boundaries, respectively, for normal plant growth. This study investigated the soil properties and groundwater resources of the Hailiutu pasture in Inner Mongolia, China. Soil water characteristics and hydraulic conductivity function curves of the pasture soil were measured based on filter paper method. Experimental results showed that air-entry and residual value were determined to be 34.6% and 13.1%, corresponding to the field water capacity and permanent wilting coefficient, respectively, and the available water capacity was 218.0 mm. The downward velocity of the soil wetting front in the silt is 3.0 mm/h. Site investigation revealed that the pasture was a natural capillary barrier, and its critical suction could optimize the upper boundary of irrigation. Considering the limited underground water resources, shallow water level, and the transpiration of Caragana Korshinskii in the pasture, an available drip irrigation method was designed. The spacing between drip irrigation pipes is 60 cm, the spacing between drip holes is 60 cm, the drip irrigation volume per hole is 475.2~838.8 mL/d, the drip irrigation time is 110~200 min at each night. Each hectare pasture exhausts 13.5~22.5 m3 water each day. Field tests showed that the proposed method is feasible and can be used for irrigation in dryland pastures. [ABSTRACT FROM AUTHOR]

Polarimetric target decomposition algorithms have played an important role in extracting the scattering characteristics of buildings, crops, and other fields. However, there is limited research on the scattering characteristics of grasslands and a lack of volume scattering models established for grasslands. To improve the accuracy of the polarimetric target decomposition algorithm applicable to grassland environments, this paper proposes an adaptive polarimetric target decomposition algorithm (APD) based on the anisotropy degree (A). The adaptive volume scattering model is used in APD to model volume scattering in forest and grassland regions separately by adjusting the value of A. When A > 1, the particle shape becomes a disk, and the grassland canopy is approximated as a cloud layer composed of randomly oriented disk particles; when A < 1, the particle shape is a needle, simulating the scattering mechanism of forests. APD is applied to an L-band AirSAR dataset from San Francisco, a C-band AirSAR dataset from Hunshandak grassland in Inner Mongolia Autonomous Region, and an X-band COSMO-SkyMed dataset from Xiwuqi grassland in Inner Mongolia Autonomous Region to verify the effectiveness of this method. Comparison studies are carried out to test the performance of APD over several target decomposition algorithms. The experimental results show that APD outperforms the algorithms tested in terms of this study in decomposition accuracy for grasslands and forests on different bands of data. [ABSTRACT FROM AUTHOR]

Platypalpus Macquart is reported in Inner Mongolia, China for the first time. Four new species are found: P. flavipilosus sp. nov., P. longus sp. nov., P. shengi sp. nov. and P. shuimogouanus sp. nov. This paper provides a description of the four species and a key to the genus in Inner Mongolia. [ABSTRACT FROM AUTHOR]

As important green energy, wind power and photovoltaic power have great development prospects. The suitability evaluation of wind and solar power plants is a popular research field, which is related to the sustainable and healthy development of wind and solar power generation. In this paper, based on multiple dimensions such as land types, climatic conditions, topographic features and policy environment, we selected 10 indicators and combined (analytical hierarchy process) AHP method to build a suitability assessment model for evaluating the suitability of solar and wind power in Inner Mongolia, China. The findings revealed that, Inner Mongolia has a great potential to generate wind and solar electricity, for wind power, the category of 'excellent' regions covers 83855 km2 and represents 7.10% of the total surface area; for solar power, 7.66% (nearly 90420 km2) are classified as 'excellent'. The suitability of both solar and wind energy in the western region is considered to have the most suitable development region, parts of Alxa League and Bayannur City have great potential for combined wind and solar power generation. The research results could provide important technical and data support for capacity evaluation and power station location decision. [ABSTRACT FROM AUTHOR]

The durability of concrete is critical for the service life of concrete structures, and it is influenced by various factors. This paper investigates the impact of the relative humidity (RH) of the curing environment on the durability of five different concrete types. The aim is to determine a suitable approach for designing concrete that is well-suited for use in the salt lake region of Inner Mongolia. The concrete types comprise ordinary Portland cement (OPC), high-strength expansive concrete (HSEC), high-strength expansive concrete incorporating silica fume, fly ash, and blast furnace slag (HSEC-SFB), steel fiber-reinforced high-strength expansive concrete (SFRHSEC), and high elastic modulus polyethylene fiber-reinforced high-strength expansive concrete (HFRHSEC). All these concrete types underwent a 180-day curing process at three distinct relative humidities (RH = 30%, 50%, and 95%) before being subjected to freeze–thaw cycles in the Inner Mongolia salt lake brine. The curing environment with a 95% RH is referred to as the standard condition. The experimental results reveal that the durability of OPC and HSEC decreases significantly with increasing relative humidity. In comparison with the control sample cured in 95% RH, the maximum freeze–thaw cycles for concrete cured in lower RHs are only 31% to 76% for OPC and 66% to 77% for HSEC. However, the sensitivity of the durability of HSEC-SFB, SFRHSEC, and HFRHSEC to variations in RH in the curing environment diminishes. In comparison with the corresponding reference value, the maximum freeze–thaw cycles for samples cured in dry conditions increase by 14% to 17% for HSEC-SFB and 21% for SFRHSEC. Specifically, the service life of HFRHSEC cured in a low RH is 25% to 46% higher than the reference value. The durability of HSEC-SFB, SFRHSEC, and HFRHSEC has been proven to be appropriate for structures located in the salt lake region of Inner Mongolia. [ABSTRACT FROM AUTHOR]

Prospecting for and exploiting buried mineral deposits is currently challenging. Given their high precision and resolution, reflection seismic methods might be useful in such applications involving deep mineral deposits. However, there are few open seismic datasets available from mineral deposit exploration, especially in hardrock environments. The world‐class Caosiyao porphyry Molybdenum deposit (1.76 Mt) in the Jining area of Inner Mongolia, China, is largely covered by loess layers, which poses challenges to its exploration. Seismic reflection surveys were conducted to help delineate the deep granite porphyry intrusions and associated orebodies. This paper presents the raw seismic reflection dataset from three profiles on the Caosiyao deposit area, which can be used as a standard dataset for reflection seismic processing in shallow coverage and hardrock areas. Situated at the juxtaposition of the Khondalite Belt and the Trans‐North China Orogen in the northern North China Craton, the Jining region hosts considerable known porphyry Mo deposits. As such, this open dataset can assist in research on deep geological structures and hence increase prospecting efficiency in geologically similar areas. [ABSTRACT FROM AUTHOR]

Studying surface geochemical anomalies is important for detecting the presence of mineral deposits. However, distinguishing inconspicuous geochemical anomalies is a challenge for geochemists. This paper studies geochemical quantitative prediction for Pb–Zn metallic mineral deposits by identifying inconspicuous surface geochemical anomalies mainly associated with the Permian and Jurassic strata in the middle-southern Da Hinggan Mountains metallogenic belt. Some new methods are employed to highlight weak surface geochemical anomalies. The weak surface geochemical anomalies of Pb and Zn are effectively highlighted by the average contrast values of Pb–Zn–Ag–Cd. The similarity coefficient with the large typical discovered deposits is used to identify new Pb–Zn mineralized anomalies and delineate new prospecting target areas. The denudation degree of mineral deposit is determined by the ratio of (W × Sn)/(As × Sb). The analogy method and areal productivity method are employed for resource prediction. Thirty-six prediction areas with Pb–Zn resources of 307.73 million tons are delineated. Five prediction areas are verified, and some new mineral deposits are proven by drilling. The verification results show that the predicted resources are very reasonable and credible. This paper is a successful case of quantitative prediction assessment of mineral resource potential, which can be used as a reference for future prospecting activities. [ABSTRACT FROM AUTHOR]

The net primary productivity (NPP) of vegetation is an important indicator reflecting the vegetation dynamics and carbon sequestration capacity in a region. In recent years, China has implemented policies to carry out ecological protection. To understand the changes in the distribution of vegetation NPP in China and the influence of climate factors, the Carnegie–Ames–Stanford approach (CASA) model was used to estimate the NPP from 2001 to 2020. In this paper, several sets of measurement datasets and products were collected to evaluate the effectiveness of the model and suggestions were provided for the modification of the CASA model based on the evaluation results. In addition to the correlation analysis, this paper presents a statistical method for analyzing the quantitative effects in individual climatic factors on NPP changes in large regions. The comparison found that the model has a better estimation effect on grassland and needleleaf forest. The estimation error for the evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF) decreases with the warming of the climatic zone, while the evergreen broadleaf forest (EBF) and deciduous needleleaf forest (DNF) do the opposite. The changes in total CASA NPP were consistent with the trends of other products, showing a dynamic increasing trend. In terms of the degree of correlation between the NPP changes and climatic factors, the NPP changes were significantly correlated with temperature in about 10.39% of the vegetation cover area and with precipitation in about 26.92% of the vegetation cover area. It was found that the NPP variation had a negative response to the temperature variation in Inner Mongolia grasslands, while it had a positive but small effect (±10 g C) in the Qinghai–Tibet Plateau grasslands. Precipitation had a facilitative effect on the grassland NPP variation, while an increase in the annual precipitation of more than 200 mm had an inhibitory effect in arid and semi-arid regions. This study can provide data and methodological reference for the ecological assessment of large-scale regional and climate anomalous environments. [ABSTRACT FROM AUTHOR]

There are a large number of tunnels built in permafrost regions every year in China. When investigating the road tunnels that have been in operation in cold regions, it was found that most of these tunnels have various freezing damages. Therefore, in the design, construction, operation, and maintenance of tunnels in cold regions, there are still many technical problems that need to be solved urgently. Among them, the problems of heat preservation, anti-freezing, and anti-drainage are the key technical problems to determine whether the tunnels in cold regions are affected by freezing damage. The project was based on the completed highway tunnels in Inner Mongolia. Given a series of special problems faced by the construction and management of tunnels in cold regions, a large number of reference documents were consulted. This paper designed thermal insulation, antifreeze, and anti-drainage technology for tunnels in the cold area of Jinpen Bay. The research in this paper can effectively reduce the probability of the occurrence of tunnel freezing damage, ensure the safety of the long-term operation of the tunnel lining structure, and greatly reduce maintenance costs, which have good economic and social benefits. [ABSTRACT FROM AUTHOR]

The theoretical and practical research of industrial integration provides new directions for the development of many industries and new ideas for the reform of many technologies. In particular, it provides new impetus for the development of agricultural modernisation. This paper takes the rural development of Inner Mongolia as the research object, discusses the integration of the primary, secondary and tertiary industries in agriculture, and then provides guidance for the further development of agriculture. Moreover, this paper combines big data technology to construct an input–output analysis model for the integration of primary, secondary and tertiary industries in rural areas of Inner Mongolia, and on this basis, conducts research and analysis on the model. In addition, this paper uses a simulation model to analyse the industrial integration and uses the statistical yearbook data of Inner Mongolia as the input to calculate the data mining effect and data analysis effect of this model. Through experimental research and analysis, it can be seen that the model constructed in this paper can play a certain effect in the analysis of the integration of primary, secondary and tertiary industries in the rural areas of Inner Mongolia. [ABSTRACT FROM AUTHOR]

This paper presents a study of the late Cenozoic Chifeng basalts (CBs) of NE China, including their olivine He isotopic compositions, whole‐rock major‐ and trace‐element contents, and whole‐rock Sr–Nd–Hf–Pb–Mo isotopic compositions, with the aim of constraining their mantle source. Results show that the basalts have high MgO, low CaO contents, and high FeOT/MnO values, which indicate that their mantle lithology was most likely pyroxenite. The CBs also exhibit ocean‐island‐basalt‐like trace‐element patterns (e.g., enrichment in light rare earth elements and high‐field‐strength elements) and have depleted Sr–Nd–Hf and relatively radiogenic Pb isotopic compositions, requiring both depleted and enriched components in their mantle. The low olivine He (3He/4He = 0.8–5.5 Ra) and whole‐rock Mo (δ98/95Mo = −0.71‰ to −0.18‰) isotopic values of the CBs, together with geophysical evidence, indicate that the rocks were derived from a depleted MORB mantle (DMM) enriched by recycled oceanic crust that was sourced from the mantle transition zone (MTZ). During the late Cenozoic, ascending wet mantle plumes triggered by dehydration of a stagnant Pacific oceanic slab are inferred to have transported preexisting recycled Pacific oceanic crust from the MTZ into the overlying asthenosphere mantle. The upwelling Pacific oceanic crust reacted with asthenospheric mantle peridotite (i.e., DMM) to produce mantle pyroxenite, whose partial melting at shallow depths generated the CBs. Considering the low δ98/95Mo values of both the CBs and coeval potassic basalts from NE China, we speculate that there may be a low δ98/95Mo reservoir in the MTZ beneath NE China. Key Points: The Chifeng basalts (CBs) exhibit relatively low 3He/4He ratios ranging from 0.8 to 5.5 RaThe mantle source end‐members of CBs were the depleted mid‐ocean‐ridge basalt mantle and recycled oceanic crustA low δ98/95Mo reservoir is inferred in the mantle transition zone beneath NE China [ABSTRACT FROM AUTHOR]

Based on the greening and low interference disposal requirements of coal gangue in high-yield and high-efficiency mines in Inner Mongolia and Shaanxi, and by integrating the existing theories and technologies such as underground filling technology of coal gangue, mine yellow mud grouting technology, and the evolution law of mining overburden fractures, a technology of filling goaf with coal gangue slurry for green disposal of coal gangue is proposed. The principle and technical framework of the technology of filling goaf with coal gangue slurry are clarified. This paper expounds on the technological process of technology of filling goaf with coal gangue slurry, establishes three types of slurry filling systems, such as centralized ground layout, ground and underground coordinated layout, and centralized underground layout, and constructs three slurry filling methods, including low-level grouting, adjacent level grouting, and high-level grouting, forming seven kinds of technology models of filling goaf with coal gangue slurry, including ground centralized pulping + high-level grouting, ground centralized pulping + adjacent grouting, ground centralized pulping + low level grouting, ground and underground coordinated pulping + adjacent grouting, ground and underground coordinated pulping + low level grouting, underground centralized pulping + adjacent grouting, and underground centralized pulping + low level grouting, and gives the selection process of technology models of filling goaf with coal gangue slurry. Based on the different conditions and requirements of Haidaze Coal Mine and Huangling No. 2 Coal Mine, engineering tests were carried out on two different technology modes, namely, ground and underground coordinated pulping + low level grouting and ground and underground coordinated pulping + adjacent grouting, based on simulation tests of low level grouting and adjacent grouting. The tests prove the feasibility of filling goaf with coal gangue slurry and explore the way for the theoretical research of the technology of filling goaf with coal gangue slurry and greening and low interference disposal of coal gangue. [ABSTRACT FROM AUTHOR]

This paper takes 207 traditional villages in Inner Mongolia as the research object and uses the ArcGIS10.7 software platform, using the nearest neighbor index, coefficient of variation analysis, spatial autocorrelation analysis, imbalance index, kernel density estimation method, geographical detector, and other methods to explore the spatial distribution characteristics and influencing factors of traditional villages in Inner Mongolia. The research shows that: (1) the spatial distribution of traditional villages in Inner Mongolia is condensed; the distribution of cities is uneven; and the overall distribution pattern of 'two main and two vice' is presented. (2) The traditional villages are mainly distributed in the altitude area of 500–1500 m, and their spatial distribution characteristics are positively correlated with the annual average temperature, annual precipitation, total population, the proportion of the primary industry, and the number of intangible cultural heritage, and negatively correlated with the slope, river distance, highway density, per capita GDP, urbanization, and the proportion of the secondary industry. (3) The results of GeoDetector2018 software show that socio-economic factors are the primary factors affecting the spatial distribution of traditional villages in Inner Mongolia, followed by natural geographical factors. The interaction and synergy between the influencing factors have increased significantly, which jointly affects the spatial pattern of the distribution of traditional villages in Inner Mongolia. The purpose of the study is to provide reference for the protection and development of traditional villages in Inner Mongolia and the implementation of the national rural revitalization strategy. [ABSTRACT FROM AUTHOR]

Metal migration and precipitation in hydrothermal fluids are important topics in economic geology. The Hongling polymetallic deposit comprises one of the most important parts of the Huanggangliang–Ganzhuermiao polymetallic metallogenic belt, which is in eastern Inner Mongolia. Except for lead–zinc skarn, minor cassiterite in the skarn and disseminated W–Sn mineralization in granitic rocks have also been found. The dominant Sn–W mineralization is in the northern part of the deposit, occurring as disseminated wolframite and cassiterite in aplite hosted in Mesozoic granite porphyry. The aplite together with pegmatite K-feldspar–quartz comprises vein dikes hosted in the granite porphyry, providing evidence for the transition from melt to fluid. The veins, dikes, and Sn–W mineralization in the aplite provide an opportunity to investigate fluid exsolution and the mechanics of metal precipitation. Based on field observations, the micrographic and scanning electron microscopy/energy dispersive spectroscopy (SEM/EDS) results of the vein dikes, chronology, and the whole-rock geochemistry of the host rock, together with the fluid inclusion results, this paper discusses the characteristics of the causative magma, the mechanics of fluid exsolution and W–Sn precipitation. Our results show that the causative magma is of highly fractionated A-type granite affinity and has an intrusive age of late Mesozoic (133.3 ± 0.86 Ma). The magmatic evolution during shallow emplacement led to immiscibility between highly volatile, high-silica, and W- and Sn-enriched melts from the parent magma, followed by fluid exsolution from the water-rich melt. The alkaline-rich fluid exsolution led to a change in the redox state of the magma and the chilling of the melt. Fluid boiling occurred soon after the fluid exsolution and was accompanied by the degassing of CO2. The boiling and escape of CO2 from the fluid led to changes in fluid redox and W and Sn precipitation; thus, the W and Sn mineralization are mostly hosted in causative intrusions or peripheral wall rocks, which can be used as indicators for Sn–W exploration in the area. [ABSTRACT FROM AUTHOR]

Highwall mining is a method that involves using a continuous highwall miner system (CHM) to extract coal from the remaining coal seams, which has proven to be an effective and safe method for extracting coal after open-pit mining. However, application cases globally have shown that the feasibility of highwall mining in open-pit coal mines is subject to geological conditions, mining techniques, and other factors. If application conditions are not suitable, equipment may be trapped under collapsed coal–rock masses and unable to be retrieved, resulting in severe safety issues for slope stability. To meet the real-world demand for extracting the remaining coal in open-pit coal mines in China, it is urgent to conduct a feasibility evaluation of highwall mining in these areas. This paper establishes a mathematical evaluation framework for assessing the feasibility of highwall mining by summarizing a large number of engineering application cases globally and analyzing various technical characteristics such as geological deposit conditions, mining techniques, and technical equipment. The analytic hierarchy process (AHP), fuzzy comprehensive evaluation (FCE) and variable weight theory (VWT) are utilized in conjunction to form this framework, which includes four secondary indicators: geological deposit factors, mining technique factors, safety impact factors, and economic evaluation factors, and 20 tertiary sub-indicators, along with their corresponding characteristic values. The feasibility sub-set is divided into four categories: infeasible, basically feasible, relatively feasible, and highly feasible, and the values of the sub-indicators strictly follow and represent these four levels of feasibility. Weight vectors for the sub-indicators are obtained through a judgment matrix established within the mathematical evaluation framework. The fuzzy relationship matrix of the sub-indicators is constructed using fuzzy mathematical membership functions, and the final feasibility evaluation is determined through two-level comprehensive evaluation. The accuracy of the model is verified using the characteristic parameters of open-pit coal mines under two different conditions (JZT coal mine in Inner Mongolia, China, and GC coal mine in Australia). The results demonstrate that the maximum evaluation membership degree for the JZT mine is 0.7113, belonging to the "highly feasible" level, while the GC mine is 0.3304, belonging to the "basically feasible" level, which aligns well with real-world usage, proving that the evaluation model can effectively reveal the performance and membership degree of each indicator in different application cases. By quantitatively characterizing the feasibility level of highwall mining technology under different application conditions, this evaluation model can provide scientific guidance for coal mining enterprises to introduce CHM for highwall mining operation in open-pit coal mines. [ABSTRACT FROM AUTHOR]

Mudstone, as a typical soft rock with wide distribution, has been endangering the slopes containing mudstone by its water-sensitivity of swelling and weakening strength when encountering water. To comprehensively understand the water-sensitivity of mudstone and reveal its influence on slope stability, we took the working slope containing water-sensitive mudstone of Shengli No.1 open-pit coal mine in Xilinhot, Inner Mongolia, China, as an example. Mudstone samples taken from the working slope were remodeled and saturated, and then triaxial tested to obtain the effective cohesion and effective internal friction angle. The filter paper method was used to obtain the soil–water characteristic curve of unsaturated mudstone. The pore structure of mudstone samples with different water contents were analyzed using the mercury intrusion porosimetry tests combined with the fractal dimension. The total pore content of the mudstone sample with lower water content is greater than that of the mudstone sample with higher water content. The mesopores are more in the mudstone sample with lower water content, while the small pores are more in the mudstone sample with higher water content. The variation of water content will change the complexity of mudstone pore structure. The higher the water content, the simpler the mudstone pore structure and the smoother the pore surface. Numerical calculations were conducted on the stability of the working slope under different rainfall conditions. The effective saturation on the mudstone layer surface changed and the plastic strain all occurred on the mudstone steps under different rainfall conditions. The key to preventing landslide of the slope containing water-sensitive mudstone in Shengli No.1 open-pit coal mine is to control the deformation and sliding of the mudstone layer. [ABSTRACT FROM AUTHOR]

Simple Summary: In recent years, the shortage of cow stocks and the reduction of cow breeders in China have caused a shortage of cattle resources and a high price of calves, which has become a bottleneck restricting the further development of China's beef cattle industry. At present, there are few studies on the decision-making behavior of cow breeding in China. In order to explore the factors that affect the decision-making behavior on cow breeding by beef cattle farmers, this paper uses field survey data to make an empirical analysis through the Logit ISM model. The results show that the age of the breeder, the breeding year, the planting area of forage, market expectations, the loan amount, the breeding method policy publicity and policy subsidies are significant factors affecting the decision-making behavior of beef cattle farmers on cow breeding. The beef cattle industry is an important part of herbivorous animal husbandry and an important industry to enrich the dietary structure of residents and promote the income of farmers and herdsmen. The cow is an important foundation to support the healthy development of the beef cattle industry, which is related to the stability of cattle sources and the sustainable development of the industry. However, in recent years, the shortage of cows in our country has led to the shortage of cattle resources and the high price of calves, which has restricted the further development of our beef cattle industry. In order to explore the factors that affect the decision-making behavior behind cow breeding and to find the right policy to mobilize the enthusiasm for cow breeding, based on the field survey of five provinces (cities and regions), including Inner Mongolia Autonomous Region and Ningxia Hui Autonomous Region, this paper conducts an empirical analysis through the Logit ISM model. The results show that market expectation is the surface factor that directly affects the decision-making behavior of cow breeding. The influencing factors of the middle layer are policy propaganda, policy subsidies, breeding years, and feeding methods. The deep root factors are the age of the breeder, the amount of loan, and whether to plant feed crops. Based on this, this paper proposes that we should actively promote the importance of cow breeding, strengthen policy support for cow breeding, formulate scientific and reasonable subsidy policies for cows, innovate financial support methods to solve the problem of fund shortage of farmers, and develop forage resources and reduce the breeding cost of cows. [ABSTRACT FROM AUTHOR]

In order to deal with the threat of forest fire to the original forest resources, improve the efficiency of firefighting, and better protect the forest ecological resources in the original forest area. In this paper, the ant colony algorithm is used as the search algorithm for the firefighting path, and the Qiqian Forestry Bureau in the northern primitive forest region of the Great Xing'an Range in Inner Mongolia is taken as the research object to select road entry points with different linear distances from the fire poin. By adjusting the pheromone volatility coefficient, the improved ant colony algorithm can better deal with the off-road firefighting path planning in forest environment. The simulation results show that using the road entry point with linear distance of 24.5 km as the starting point for the path planning of off-road firefighting in the northern the Great Xing'an Range can effectively shorten the path and minimize the loss caused by forest fire. At the same time, it verifies the effectiveness and rationality of the path planning of the improved ant colony algorithm under such environmental conditions. The optimization scheme meets the needs of forest fire fighting in the original forest area, and can play a guiding role in design of the forest fire path planning in the original forest area in the northern Great Xing'an Range of Inner Mongolia and a reference for fire path planning in other forest areas in China. [ABSTRACT FROM AUTHOR]

In the Uxin Banner area of the Inner Mongolia Autonomous Region, mines that have experienced rock bursts have all been affected by the presence of confined water in the roof strata. Strong mine pressure appears in the working face with about 30 m wide coal pillar in this area, and the research and practice of prevention and control of rock burst by small coal pillar are carried out. Mining-related events linked to the preservation of small coal pillars in the 2-2 coal seam of this region, and studies of the phenomenon, have shown that head-on rock bursts occur during gob-side roadway driving at the edge of the drained area, making it necessary to identify the sources of pressure triggering the events, to determine the related threshold criteria, and to identify methods to reduce the occurrence and magnitude of the rock burst events. This study used the gob-side entry driving in the drained area of the 2202 auxiliary haulage roadway of a mine as a case study. The paper built a structural and computational model for overburdens (including the drained stratum) before mining disturbance, based on the theory for a continuously distributed Winkler elastic foundation. The models used and developed in our study were used to identify, quantify, and describe the changes to stress and the transfer of stress during the drainage process. On the basis of the effects of drainage stress induced by the gob-side entry driving, we outlined a method for ranking the level of rock burst hazard associated with the areas in and adjacent to the drained area. The level of rock burst hazard associated with the entry driving could be arranged in descending order as follows: parallel boundary > vertical boundary > undrained area > drained area. Stress threshold criteria for head-on ejection were also proposed in the paper, namely, (1) the occurrence (or not) of coal ejection during loading and (2) the critical stress for the occurrence of ejection. Field monitoring indicated that microseismic events and energy are mainly concentrated in the driving region parallel to the boundary of the drained area. We concluded that head-on large-diameter borehole destressing would effectively reduce the likelihood of a rock burst occurrence. [ABSTRACT FROM AUTHOR]

To address the severity of the wind and light abandonment problem and the economics of hydrogen energy production and operation, this paper explores the problem of multi-cycle resource allocation optimization of hydrogen storage systems for coal–wind–solar power generation. In view of the seriousness of the problem of abandoning wind and photovoltaic power and the economy of hydrogen production and operation, the node selection and scale setting issues for hydrogen production and storage, as well as decision-making problems such as the capacity of new transmission lines and new pipelines and route planning, are studied. This research takes the satisfaction of energy supply as the basic constraint and constructs a multi-cycle resource allocation optimization model for an integrated energy system, aiming to achieve the maximum benefit of the whole system. Using data from Inner Mongolia, where wind abandonment and power limitation are severe, and Beijing and Shanxi provinces, where hydrogen demand is high, this paper analyzes the benefits of the hydrogen storage system for coal–wind–solar power generation, and explores the impact of national subsidy policies and technological advances on system economics. [ABSTRACT FROM AUTHOR]

As a typical desert in the Inner Mongolia Autonomous Region, the Ulan Buh Desert has a dry climate and scarce precipitation all year round. Groundwater has become the main factor limiting the growth of vegetation in this region. It is of great significance to study the influence of groundwater depth on the spatial distribution pattern of vegetation in this region. Based on the PIE-Engine platform and using long-term time-series Landsat data, this paper analyzed the spatial–temporal distribution characteristics and trends in vegetation coverage in the Ulan Buh Desert in the last 20 years using a pixel dichotomy model and the image difference method. The Kriging interpolation method was used to interpolate the groundwater depth data from 106 monitoring wells in the Ulan Buh Desert over the past 20 years, and the spatial distribution characteristics of groundwater depth in the Ulan Buh Desert were analyzed. Finally, the correlation coefficient between changes in vegetation coverage and changes in groundwater depth was calculated. The results showed the following: (1) The vegetation coverage in the Ulan Buh Desert was higher in the periphery and lower in the center of the desert. The overall vegetation level showed an increasing trend year by year; the growth rate was 4.73%/10 years, and the overall vegetation cover showed an improving trend. (2) The overall groundwater depth in the Ulan Buh Desert was deep in the southwest and shallow in the northeast. In the past 20 years, the groundwater depth in the Ulan Buh area has become shallower, and the ecological condition has gradually improved. (3) On the whole, the vegetation coverage varied with the groundwater depth, and the shallower the groundwater depth, the greater the vegetation coverage. When the groundwater depth increased to more than 4 m, the change in the groundwater depth had a significant effect on the vegetation coverage. However, when the groundwater depth was greater than 6 m, the change in the groundwater depth had no significant effect on the change in vegetation coverage. [ABSTRACT FROM AUTHOR]

Following the launch of the ZY1-02E satellite, the thermal infrared sensor aboard the satellite experienced alterations in the space environment, leading to varying degrees of attenuation in some components. The laboratory calibration accuracy could not satisfy the demands of quantitative production, and a certain degree of deviation was observed in on-orbit calibration. To accurately characterize the on-orbit radiation properties of thermal infrared remote sensing payloads, an absolute radiometric calibration campaign was carried out at the Ulansuhai Nur and Baotou calibration sites in Inner Mongolia in July 2022. This paper outlines the processes of onboard calibration and vicarious calibration for the ZY1-02E satellite, comparing the outcomes of onboard calibration with those of vicarious calibration. The onboard calibration method involved internal calibration, while the vicarious calibration method utilized an on-orbit absolute radiometric calibration technique based on various natural features that were not constrained by satellite–Earth spectrum matching requirements. Calibration coefficients were acquired, and the absolute radiometric calibration results of on-orbit vicarious and onboard calibration were compared, analyzed, and verified using the radiance computed from measured data and the reference sensor data. The accuracy of on-orbit absolute vicarious calibration was determined, and the causes for the decline in the radiation calibration accuracy on the orbiting satellite were examined. The findings revealed that the vicarious calibration results exhibited a lower percentage of radiance deviation compared with the onboard calibration results, meeting the quantitative requirements of remote sensing data. These results were significantly better than those obtained from onboard blackbody calibration, offering a data foundation for devising satellite calibration plans and enhancing calibration algorithms. In the future, the developmental trend of on-orbit radiometric calibration technology will encompass high-precision and slow-attenuation onboard calibration techniques, as well as high-frequency and simplified-step vicarious calibration methods. [ABSTRACT FROM AUTHOR]

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