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Population migration brings about many problems in villages. The Ji (几)-shape bend of the Yellow River is an important ecological sensitivity study area, and some progress exists in the study of villages, still has many problems. This article addresses the inadequacy of the existing research and mainly solves the problems in three areas. It primarily used the research method of Arc GIS10.8, the big data research methods such as imbalance index, Gini coefficient, geographic concentration index, Geodetector, and other methods were used, laying the groundwork for additional analysis of various factors. Hence, the subsequent study findings were attained. 1) The distribution pattern in the village system around the Ji-shape bend of the Yellow River seems to be a positive spatial correlation, with the characteristics of random distribution, uneven spatial distribution, and low concentration, with Hohhot-Baotou serving as a center. 2) Natural factors are the most important factors in the distribution of villages. 3) Among the natural factors, elevation (0.244619), the value of slope (0.319805), and the aspect of slope (0.074089) appear to be the strongest explanatory power. Among the social factors, the rate of urbanization (0.019082), highway density (0.019082), and percentage of tertiary industry (0.018422) show the strongest explanatory power on socioeconomic factors. The natural and social characteristics of villages are important for the siting of villages. This paper put forward some suggestions for the protection and development of villages in ecologically sensitive areas. [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]

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]

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]

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]

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 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]

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]

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]

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]

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]

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]

Roadway mine pressure monitoring is one of the important means to ensure the safe and efficient mining of coal mines. However, the traditional monitoring methods have the disadvantages including lack of systematim, low accuracy, poor reliability, and difficulty in networking. In this paper, by using the grating sensor as a monitoring method, a roadway mine pressure grating monitoring system including roof separation, bolt stress, surrounding rock stress and bolt load monitoring was systematically designed and develop, to solve the shortcomings of current monitoring methods. Firstly, taking the 81303 return airway of a coal mine in Inner Mongolia as the research object, the stress distribution law of the two coal pillars was clarified by numerical simulation, and the optimal measuring point layout scheme of the roadway was determined. Secondly, the overall framwork of the roadway mine pressure grating monitoring system was built, and the design and research of the system hardware configuration and monitoring software were carried out to realize the real-time online monitoring and data processing of the roadway mine pressure. In addition, the industrial application test shows that the mine pressure law obtained by the system is generally consistent with those from the traditional method, and the relative error of the monitoring parameters is up to 1.16%, which verifies the effectiveness and adaptability of the mine pressure grating monitoring system. [ABSTRACT FROM AUTHOR]

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]

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]

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]

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]

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]

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]

Tracing the historical development of soil salinization and monitoring its current status are crucial for understanding the driving forces behind it, proposing strategies to improve soil quality, and predicting future trends. To comprehensively understand the evolution of research on the remote sensing inversion of soil salinity, a scientific bibliometric analysis was conducted on research from the past two decades indexed in the core scientific databases. This article analyzes the field from various perspectives, including the number of publications, authors, research institutions and countries, research fields, study areas, and keywords, in order to reveal the current state-of-the-art and cutting-edge research in this domain. Special attention was given to topics such as machine learning, data assimilation methods, unmanned aerial vehicle (UAV) remote sensing technology, soil inversion under vegetation cover, salt ion inversion, and remote sensing model construction methods. The results indicate an overall increase in the volume of publications, with key authors such as Metternicht, Gi and Zhao, Gengxing, and major research institutions including the International Institute for Geoinformatics Science and Earth Observation and the Chinese Academy of Sciences making significant contributions. Notably, China and the USA have made substantial contributions to this field, with research areas extending from Inner Mongolia's Hetao irrigation district to the Mediterranean region. Research in the remote sensing domain focuses on various methods, including hyperspectral imaging for salinized soil inversion, with an increasing emphasis on machine learning. This study enriches researchers' knowledge of the current trends and future directions of remote sensing inversion of soil salinization. [ABSTRACT FROM AUTHOR]

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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]

This article is devoted to the study of electromagnetic scattering characteristics in arid areas, and proposes environmental monitoring and improvement methods. A four-component soil dielectric model was established to study the relationship of soil dielectric constant with soil moisture and frequency. As the Monte Carlo Method combined with Gaussian spectral function was used to simulate the actual dry ground, the Sparse Matrix/Canonical Grid (SMCG) algorithm model based on the surface current equation was established to calculate the electromagnetic scattering coefficient of arid areas. To verify the correctness of the proposed algorithm, the results obtained by SMCG was compared with those calculated by Method of Moments (MOM), which showed great consistency. Many results were obtained by using the algorithm in this paper, based on the measured soil data in the southeastern area of Ejin Banner, Inner Mongolia. It was found that soil moisture content, area roughness and incident electromagnetic wave segment had influence on the scattering echo and showed regular change. The results of this paper are of guiding significance for soil moisture monitoring, desertification control and agricultural planting in arid areas. [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]

The winter cold stress of dairy cows has become one of the important problems affecting the healthy development of animal husbandry. Cold stress will lead to the decrease of feed intake, milk yield and reproductive performance of dairy cows, and seriously harm the economic benefits of dairy farmers. Inner Mongolia is located in a cold region, where animals are in a cold environment for a long time, and the impact of cold stress is more common. In order to more specifically understand the effects of cold stress on the production performance of dairy cows, the paper reviews the effects of cold stress on the behavior, milk yield, neuroendocrine, biochemical indexes, immune, antioxidant function, intestinal flora and other aspects of dairy cows, and summarizes the effective prevention and control measures to prevent cold stress of dairy cows, to provide reference for further research on the prevention and relief of cold stress in dairy cows. [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]

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]

This paper archaeologically investigates three representative Eastern Zhou cemeteries in south-central Inner Mongolia. Through analysis, two types of tombs can be distinguished, according to the forms of tombs and assemblages of grave goods. Type A tombs belong to Zhao state agricultural immigrants from the south; Type B, pastoralists from the north. The coexistence of two groups of people with distinct subsistence economies in one cemetery reflects the integration process of agriculturalists and pastoralists. The emergence of agropastoralist integration in central-southern Inner Mongolia cross-confirms historical trajectory of the southward advance of pastoralists and the strategic management of northwestern areas by the Zhao state. [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]

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]

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]

Introduction: Power industry is one of the largest sources of CO2 emissions in China. The Yellow River Basin plays a supportive role in guaranteeing the effective supply of electricity nationwide, with numerous power generation bases. Understanding the drivers and peak of CO2 emissions of power industry in the Yellow River Basin is vital for China to fulfill its commitment to reach carbon emissions peak by 2030. Methods: The Logarithmic Mean Divisia Index (LMDI) model was employed to explore the drivers to the change of CO2 emissions in power industries of three study areas, including Inner Mongolia Autonomous Regions, Shanxi Province, and Shandong Province in the Yellow River Basin. And Back Propagation (BP) neural network was combined with scenario analysis to empirically predict the trend of the amount of CO2 emitted by power industry (CEPI) from provincial perspective. Results: CEPI in Inner Mongolia under the scenarios of a low degree of CO2 emissions promotion with a medium degree of CO2 emissions inhibition (LM) and a low degree of CO2 emissions promotion with a high degree of CO2 emissions inhibition (LH) scenario can reach a peak as early as 2030, with the peak value of 628.32 and 638.12 million tonnes, respectively. Moreover, in Shanxi, only CEPI under a low degree of CO2 emissions promotion scenarios (LL, LM, LH) can achieve the peak in 2025 ahead of schedule, with amounts of 319.32, 308.07, and 292.45 million tonnes. Regarding Shandong, CEPI under scenarios of a low degree of CO2 emissions promotion with a high degree of CO2 emissions inhibition (LH) and a medium degree of CO2 emissions promotion with a high degree of CO2 emissions inhibition (MH) could achieve the earliest peak time in 2025, with a peak of 434.6 and 439.36 million tonnes, respectively. Discussion: The earliest peak time of CEPI in Shandong Province and Shanxi Province is 2025, but the peak of CEPI in Shanxi is smaller than that of Shandong. The peak time of CEPI in Inner Mongolia is relatively late, in 2030, and the peak is larger than that of the other two provinces. The per capita GDP is the most positive driving factor that contributes to the CEPI. Shandong has a strong economy, and its per capita GDP is much higher than Shanxi's. Therefore, even under the same peak time, the CEPI in Shandong is much higher than that of Shanxi. Inner Mongolia is extensive and sparsely populated, which makes its per capita GDP rank among the top in China. In addition, Inner Mongolia's coal-based power generation structure and high power generation also contribute to its late CO2 peak time and large CO2 peak. [ABSTRACT FROM AUTHOR]

In order to explore the influencing factors of spatial and temporal evolution of production-living-ecological space in Beijing Tianjin sandstorm source area, the remote sensing images, natural environment and socio-economic data of Duolun County in Inner Mongolia from 2000 to 2020 were selected, and the spatial auto-correlation model and principal component analysis model were used to analyze the spatial pattern evolution and influencing factors of production-living-ecological space. The results show that: (1) the function of production space decreases slightly, and the degree of spatial agglomeration decreases; (2) The function of living space rose slightly, and its spatial agglomeration degree showed an upward trend; (3) The ecological spatial function showed a slow upward trend, and its spatial agglomeration degree increased; (4) The spatial pattern of production-living-ecological space is characterized by "high in the southwest and low in the northeast"; (5) Precipitation has the greatest impact on the spatial evolution of the production-living-ecological space. The distance from the main residential areas, per capita GDP, the distance from the main roads and the distance from the main waters have strong explanatory power on the spatial evolution of the production-living-ecological space. [ABSTRACT FROM AUTHOR]

Fusarium crown and root rot (FCRR), caused by Fusarium oxysporum f. sp. radicis-lycopersici (FORL), is an economically important disease that affects tomatoes worldwide and has become more prevalent in China in recent years. In 2021 and 2022, tomato plants in greenhouses in Hohhot, Inner Mongolia, were observed showing symptoms of stunting, premature loss of lower leaves, and root rot. Fungal pathogens were isolated from 20 infected tomato plants and identified based on morphological observation and DNA sequencing. Twelve isolates were consistently identified as Fusarium oxysporum f. sp. radicis-lycopersici (FORL) via an analysis of the ITS, TEF-1α, and pgx4 genes. This is the first report of FORL in Inner Mongolia, China. The isolates were examined for their pathogenicity by inoculating them on tomatoes, eggplants, peppers, and chickpeas. The fungicide sensitivity of the isolates was determined. Effective concentrations for 50% growth inhibition (EC50) were measured using seven fungicides. The EC50 values of tebuconazole and prochloraz were <1.0 μg·mL−1, exhibiting the most effective inhibition among the fungicides tested. Additionally, FORL resistance screening of tomato germplasms was performed. One tomato variety was resistant to FORL, and the remaining 43 germplasm lines showed various levels of resistance. The rates of highly susceptible, moderately susceptible, susceptible, and moderately resistant germplasms accounted for 29.55%, 22.73%, 40.91%, and 4.55% of the 44 germplasms tested, respectively. [ABSTRACT FROM AUTHOR]

In a nine-year field experiment in a wheat-maize-sunflower cropping system in Hetao Irrigation Area, Inner Mongolia, China, organic amendments applied as straw, manure, green manure, and the combination of green manure and straw increased wheat and maize yield, soil aggregate stability, and soil microbial activity in comparison with chemical fertilizer, without changing greenhouse gas emission intensity. [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]

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]

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]

Copyright of Journal of Agricultural Resources & Environment / Nongye Ziyuan yu Huanjing Xuebao is the property of Journal of Agricultural Resources & Environment Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)