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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]

Northeast China played an irreplaceable role in population migrations and cultural exchanges in East Asia during the Paleolithic. This paper collected 182 archaeological sites to analyse the characteristics of spatial-temporal variations of Paleolithic human activities in Northeast China, and explored the driving mechanisms behind these variations in combination with the paleoenvironmental and archaeological studies. During the Lower Paleolithic, constrained by the relatively cold-dry climate and blocked by the Songnen paleo-lake basin, the population was sparse and distributed only near 40° N at the southern end of Northeast China. Upon entering the Middle Paleolithic, as humans developed greater tolerance to cold climates and adopted more sophisticated survival strategies with the application of small lithic tools, their numbers increased and geographical distribution expanded northward to 45° N at the central region of Northeast China. The Upper Paleolithic saw a considerable increase in population and expansion across almost all of Northeast China except for the eastern Inner Mongolia Plateau. We speculated that 50 ka and 30 ka BP were two key points, both of which may be associated with a significant increase in the frequency of migrations and communications among humans, and the widespread popularity of highly mobile microblade technology, respectively. In addition, the environmental analysis of archaeological sites revealed a continuous spread of Paleolithic humans to areas with higher elevations, steeper slopes, and lower temperatures. Meanwhile, they were becoming less reliant on water resources and were more widely conducting activities in open-air areas, showing that the environmental adaptability had been continuously improving over time. This study can provide a reference for the reconstruction of the migration history of early humans in East Asia, and is also of great significance for a comprehensive understanding of the evolutionary process of early human-environment interactions. [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]

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]

Considering China's goal of achieving peak carbon emissions in 2030 and carbon neutrality in 2060, this paper analyzes carbon emissions, carbon emission intensity, the decoupling of carbon emissions and economic development, and associated influencing factors using data from Ordos City from 2009 to 2020. The methods employed are the IPCC carbon emission calculation method, Tapio decoupling model, and logarithmic average Dickens index decomposition. The results show the following: (1) During the study period, Ordos City carbon emissions showed an increasing trend, and the total carbon emissions increased from 5.634 billion tons in 2009 to 204.734 million tons in 2020, with an average annual growth rate of 13.77%. (2) The decoupling elasticity of Ordos City from 2009 to 2016 was 1.26, which is the expansion negative decoupling state. From 2016 to 2020, the decoupling elasticity was -3.2657, showing a strong negative decoupling state. (3) The increase in population and per capita GDP in Ordos are the main factors contributing to the increase of carbon emissions, and the main negative growth driver is the increase in energy intensity. [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]

With the proposal of“dual carbon”goals, China′ s construction of an ecological civilization has entered a new stage with the focus on reducing carbon. The eastern grassland area of the eastern Inner Mongolia Autonomous Region plays an important role in ensuring national energy security, ecological security, and achieving the goal of“carbon neutrality”as scheduled. However, the ecological environment in this area is characterized by extreme cold, semi-arid conditions, and a scarcity of topsoil. Furthermore, the ecological environment problems caused by mineral resources exploitation seriously restrict the sustainable development of regional energy and ecological security. Therefore, it is necessary to perform research on ecological restoration of mines in the grassland area in eastern Inner Mongolia. This paper reviews the research process of mine ecological restoration at home and abroad, summarizes the existing research on mine ecological restoration and the advanced technologies of mine ecological restoration in the grassland area of eastern Inner Mongolia, and analyzes the path and mode of mine ecological restoration in the grassland area under the background of carbon neutrality. This paper preliminarily clarifies the existing problems and deficiencies in the research of mine ecological restoration in the eastern grassland area of Inner Mongolia and considers the prospects of future research trends, with the goal of providing reference for future generations to study the ecological restoration of mines in these grasslands and similar areas both at home and abroad. [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]

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 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]

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]

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]

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]

In order to expand the application of remote sensing prospecting technology in gold prospecting, this paper takes the Zhuanshanzi area in Inner Mongolia as an example, and selects Landsat 8 OLI remote sensing data. On the basis of image data preprocessing, the regional tectonic information is enhanced by the fusion of B7B5B3 band. The principal component analysis is used to extract the alteration anomaly information through threshold segmentation. Based on the geological characteristics and remote sensing interpretation information of the region and Zhuanshanzi Gold Deposit, the prospecting indicator of gold deposits in Zhuanshanzi area is established, and 3 prospect areas for prospecting prediction are delineated. The field verification shows that there is gold mineralization in the prospect area. It is believed that the linear and ring structure and remote sensing anomaly information extraction based on OLI remote sensing images can be used as auxiliary means for gold prospecting prediction. [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]

Inner Mongolia Pacific Mining Co., Ltd. uses a heap leaching process for gold extraction. The large area of ore heap leaching and high sodium cyanide consumption result in high production costs. To further reduce costs and increase efficiency, the company has optimized the process and implemented the effective area dripping method. This paper introduces in detail the application conditions of the effective area dripping method in heap leaching process and the control of various indexes. The successful application of the method effectively reduces the dosage of reagents, saving 55.14 million yuan in reagent costs with significant results. [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]

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]

Lithium is one of the important strategic energy metals, which is in short supply in China. There are three major types of lithium deposits: brine and salt lake type, highly differentiated granite or pegmatite type, and carbonate-clay type. In recent years, some new types of lithium deposits have also begun to receive great attention and subject recent research. There are many crypto-explosive breccia pipe type deposits in the world, including copper, gold, lead, zinc, tungsten and tin deposits, but little is known about this type of lithium deposit. This paper introduces the latest research results of the Weilasituo Sn−Li−Rb polymetallic deposit in Inner Mongolia (NE China), which occurs in the middle-southern section of the Great Xing'an Range metallogenic belt. A remarkable feature of this deposit is the coexistence of various mineralization types, including granite type Rb and Sn−Zn, hydrothermal crypto-explosive breccia pipe type Li−Rb, quartz vein type Sn−Zn and sulfide vein type Pb−Zn−Ag mineralization. Among them, hydrothermal crypto-explosive breccia pipe type Li-Rb deposit is currently very rare at home and abroad, which is likely a new type of rare metal deposit that worthy of our attention. This paper systematically summarizes the geology, alteration and mineralization, geochemistry, isotopes and geochronology of the Weilasituo deposit, and establishes a new petrogenic and metallogenic model. [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]

The randomicity and fluctuation of the wind speed will influence the precision of the forecast. This paper presents a new method of combined wind speed forecast based on the two-level decomposition and weighted average, which can improve the accuracy of wind speed forecasting. First, the improved complementary ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) decomposition method is used to get different sub-sequences, and then the fuzzy entropy is used to judge the degree of confusion of the sub-sequences. In this paper, the autoregressive integrated moving average (ARIMA) model is used to predict the minimum fuzzy entropy. And the other subsequences are decomposed by backpropagation neural network (BPNN), variational mode decomposition (VMD) and predicted by nonlinear auto-regressive (NAR) and BP neural network with suitable weighting ratio for weighted average and particle swarm optimization- long short-term memory (PSO-LSTM) neural network respectively, and ultimately all the predicted values are superimposed to get the final prediction. Experiments are conducted using three datasets and eight comparison models to verify the validity of this model. The prediction analysis was carried out using the actual measured data of a wind farm in Inner Mongolia, and the results indicated that (1) using fuzzy entropy can effectively improve the prediction precision; (2) the prediction accuracy of the combined prediction method of neural network based on two-level decomposition was greatly improved and the prediction results were more reliable; (3) Decompose one of the subsequences with VMD, predict it with NAR and BP neural network, and choose appropriate weight ratio for weighted average prediction will achieve better prediction results; (4) the root mean square error (RMSE) of the hybrid model on the three wind speed datasets were 0.28777, 0.22786 and 0.17128, which are lower than the comparison values of other models. So, it is workable to use this hybrid model in wind speed prediction. [ABSTRACT FROM AUTHOR]

The properties and service life of asphalt pavement are to a large extent dependent on pavement structure. Most pavement structural designs at home and abroad commonly follow the typical structural design method; however, considering that the geographical span from east to west in Inner Mongolia is large, a single pavement structure cannot be optimal for all environments, and low-temperature fracturing may easily occur during the road service life. Ten kinds of pavement structures are analyzed in this paper. The pavement structure mechanical indices are analyzed using different soil base modulus values, different axle loads, and different internal contact conditions. A low-temperature return period was introduced to establish a Gumbel extreme temperature model. The low-temperature protection index and calculation method based on the return period for asphalt pavement is proposed, which takes Arxan City as a benchmark for calculating low-temperature protection values in Eastern Inner Mongolia. The low-temperature fracturing formula is improved to calculate low-temperature indexes for different pavement structures. Using a life cycle cost model, the economy of different pavement structures is evaluated from the aspects of initial cost, maintenance cost, and pavement residual value. By establishing a combined weight-fuzzy pavement evaluation model and combining the mechanical response, low-temperature fractures during the return period, and economy of the life cycle, a comprehensive property ranking for different pavement structures was obtained. Finally, the typical structural combination for the asphalt pavement in the Eastern Inner Mongolia is recommended to be three layers of asphalt surface + semi-rigid base or three layers of asphalt surface + asphalt treated base (ATB) + semi-rigid base. [ABSTRACT FROM AUTHOR]

Simple Summary: In this paper, two new genera with two new species of Dermaptera are described from the Middle Jurassic Jiulongshan Formation of Daohugou, Inner Mongolia, China. The discovery of these two new species enriches the comparatively meagre fossil record of Dermaptera, particularly from the Middle Jurassic. The description of Applanatiforceps angustus is another brick laid in the foundation of protodiplatyid diversity, and the new genus Ekpagloderma gracilentum highlights the diversity of cercal forms among Aglyptodermatinae and the remarkable homogeneity of the general morphology of groups within this clade. Two new genera and species of Dermaptera are described from the Middle Jurassic Jiulongshan Formation of Daohugou, Inner Mongolia, China: Applanatiforceps angustus gen. et sp. nov. in the archidermapteran family Protodiplatyidae, and Ekpagloderma gracilentum gen et sp. nov. in the eodermapteran family Semenoviolidae. Applanatiforceps shares the typical characters of the extinct suborder Archidermaptera (e.g., pentamerous meta tarsi, filiform and multimerous cerci) and externalized ovipositor. The family identity of the Protodiplatyidae can be further distinguished by comparing this new genus with other genera of the Protodiplatyidae. As a result of its large compound eyes, tegmina without venation, body sparsely setose, legs rather short and slender, and shape of the veinless tegmina, Ekpagloderma is classified in the subfamily Aglyptodermatinae. Ekpagloderma not only has the typical features of the Aglyptodermatinae, but also exhibits a more primitive slender segmented cerci, which is different from all other genera of Eodermaptera. In fact, the diversity of Eodermaptera as known today indicates some of the challenges in understanding the suborder and whether or not it is monophyletic as historically construed, or if the separation of Turanodermaptera is justified. [ABSTRACT FROM AUTHOR]

(1) Background--In 2021, the forest chief system was fully implemented nationwide. Under this background, how to embed the forest-chief system into the forest resources management system in the state-owned forest areas and fully realize the comprehensive efficiency of forest supervision and protection policies has become an important issue in the forest areas at present. (2) Methods--Based on the field investigation of some typical forestry enterprises in the key state-owned forest areas, this paper systematically analyzed the forest resources management practice after the reform in the key state-owned forest areas at the present stage, summarized the new challenges faced by the forest resources management mechanism after the implementation of the forest chief system, and on this basis, put forward policy suggestions to help the forest chief system to be embedded in the forest resources management system in the key state-owned forest areas. (3) Results--First, the forest chief system was carried out in the key state-owned forest areas, and the state-owned forest industry enterprises were incorporated into the local forest chief system through the organization of personnel. Second, the managers in different state-owned forest industry enterprises served as forest chiefs in different forms. Among them, the enterprise managers of China Longjiang Forest Industry Group Co., Ltd., Yichun Forest Industry Group and Daxing' anling Forestry Group participated in the forest chief system by serving as deputy forest chief of their respective counties (cities or districts). The managers of Jilin Forest Industry Group Co., Ltd.and Changbai Mountain Forest Industry Group served as the general forest chief of their respective forestry bureaus in accordance with the county-level forest chief system. As one of the six major areas of responsibility under the forest chief system in Inner Mongolia Autonomous Region, Inner Mongolia Forest Industry Group appointed deputy forest chief to manage forest resources. (4) Conclusions and Discussions--The implementation of forest chief system in the key state-owned forest areas faces a series of challenges. First, in the process of realizing the policy goal of forest chief system in the key state-owned forest areas, the forest resources management in the forest areas needs to be systematically integrated in the goal setting. Second, under the background of the overall implementation of forest chief system, the forest resources management in the key state-owned forest areas has a pattern of "dual-track and parallel". Third, the coordination mechanism of forest resources management under the forest chief system in the key state-owned forest areas is not perfect, including the government-enterprises coordination mechanism and the social participation mechanism. Based on the above analysis, the following policy suggestions are put forward. First, promote the integration of forest resources management objectives based on the reality of the key state-owned forest areas. Second, develop a list of forest chief powers to clarify the boundaries of responsibilities and powers of forest resources management under the forest chief system. Third, accelerate the establishment of the working mechanism of forest resources management under the forest chief system. In short, when promoting the forest resources management under the forest chief system in the key state-owned forest areas, the appeals of the central government, local governments, forest industry enterprises, forest residents and other parties must be comprehensively considered, the work objectives of the forest chief system must be clearly defined, the work content of the forest chief system must be enriched, and the objectives of integrating ecological benefits, social benefits and economic benefits must be formulated. [ABSTRACT FROM AUTHOR]

The early stages of forest fires are usually accompanied by large amounts of smoke, so smoke identification and concentration inversion can effectively warn and locate the fire point. To achieve smoke identification and concentration inversion, this paper first analysed the spectral differences between smoke and underlying background features based on the samples selected from Landsat 8/OLI fire data of Qiqian forest in Inner Mongolia, China, andNew South Wales, Australia. Then, the sensitive band of smoke identification was screened and the relative smoke concentration indices were established. Finally, a mathematical model between the indices and smoke concentration level was constructed and the best inversion model was established by accuracy test based on samples in each background. The results show that (1) the reflectance increases with increasing smoke concentration in B1-B4 bands under different backgrounds (vegetation, water, bare ground), and the reflectance was significantly different between different concentrations of smoke; (2) the smoke concentration inversion model form is y = kx + b with R2 > 0.8 (x denotes the smoke concentration level, y denotes the relative smoke concentration index), and the visible brightness index (VBI = B1 + B2 + B3 + B4) was the best relative smoke concentration index under different background; (3) the model's accuracy was tested using each background smoke sample with a known level of smoke concentration, and the inversion accuracy was above 90%. The results show that the VBI can effectively reflect the spectral variation between different smoke concentrations and background features; the variation is closely related to smoke concentration which determines that the mathematical correlation model between VBI and relative smoke concentration can be established; the model is accuracy and can be used for the relative smoke concentration inversion of forest fire cases in different study areas. [ABSTRACT FROM AUTHOR]

Simple Summary: Osmylopsychopidae, an extinct family of Neuroptera, is closely related to the extant Psychopsidae. The sporadic records of this family and limited preservation of fossil specimens have hindered the understanding of the evolution of Osmylopsychopidae. In this paper, one new genus with four new species of Osmylopsychopidae are described from the Middle Jurassic Jiulongshan Formation of northeastern China. These newly discovered osmylopsychopids with a forewing length of ca. 10 mm (implying small body size), clearly distinguished from the traditional sense of Osmylopsychopidae, suggest that Osmylopsychopidae possibly underwent a significant diversification during the Mesozoic. One new genus with four new species sharing the similar character of a forewing length of ca. 10 mm, namely, Minipsychops spasulus gen. et sp. nov., Minipsychops polychotomus sp. nov., Minipsychops densus sp. nov., and Minipsychops unicus sp. nov., are described from the Middle Jurassic Jiulongshan Formation of Daohugou, Inner Mongolia in China. These new insects can be attributed to Osmylopsychopidae for their distinctive configuration of costal space and the venations of RP1 and Cu. Compared with the typically medium to large body sizes of known osmylopsychopids, these new Middle Jurassic taxa of a particularly miniaturized lineage not only enrich the species diversity of Osmylopsychopidae, but also enhance our understanding of the historical evolution of these poorly known lacewings. [ABSTRACT FROM AUTHOR]

The Zhaojinggou Nb–Ta deposit is one of large rare metal deposits newly discovered in the northern margin of the North China Craton in recent years. This paper reports petrography, petrochemistry, columbite‐group minerals U–Pb chronology study of the amazonite granitic pegmatite (AGP) exposed in this deposit, and composition of columbite‐group minerals and biotite are obtained by electron probe microanalyzer and LA‐ICP‐MS. Eighteen analyses of columbite‐group minerals yielded weighted mean 206Pb/238U age of 116.9 ± 1.4 Ma. The crystallization temperature of biotite is 630–650°C, and the oxygen fugacity is 10−17–10−18 bars. The biotite has low MgO contents and high Rb, Rb/Sr, and FeOT/(FeOT + MgO) ratios. The AGP has extremely low MgO, Cr, Co and Ni contents, with Nb/Ta ratios range from 1.63 to 9.05 and Rb/Sr ratios range from 303.30 to 648.90, and obvious 'M' type tetrad effect of rare earth element indicating that the formation of the AGP is related to crust‐derived magma. The contents of Nb2O5 and FeO decrease, while the Ta2O5 and WO3 contents, Mn# and Ta# values increase gradually from the core to the rim of columbite‐group minerals. Some columbite‐group minerals have unobvious oscillatory zoning, and some have a clear bright zoing with high Ta contents on the rim, indicating that the genesis of Zhaojinggou Nb–Ta deposit is mainly magmatic crystallization differentiation, accompanied by hydrothermal autometasomatism in the late stage. [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]

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]

Climate change means that China needs to reduce carbon dioxide emissions from its transport sector. The study reported in the paper analysed the spatial–temporal characteristics of carbon doxide emissions produced by transporting coal by rail in the country between 2000 and 2014. The kriging interpolation method was used to analyse the emission distributions. The results showed that total emissions produced from rail transport of coal increased from 1·18 Mt in 2000 to 11·71 Mt in 2014, although they appear to have peaked. Inner Mongolia, Shanxi and Shaanxi were the provinces with the largest emission increases. The emissions were positively correlated and showed spatial heterogeneity, with Shanxi and Shaanxi provinces being high-emission provinces surrounded by other high-emission provinces. The paper concludes with a discussion of energy conservation and emissions-reduction measures that could be implemented by the Chinese transport industry. [ABSTRACT FROM AUTHOR]

In this paper, recent research on terrestrial ecosystem predictability using the conditional nonlinear optimal parameter perturbation (CNOP-P) method is summarized. The main findings include the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, the identification of key physical parameters that lead to large uncertainties in terrestrial ecosystem modeling and prediction, and the evaluation of the simulation ability and prediction skill of terrestrial ecosystems by reducing key physical parameter errors. The study areas included the Inner Mongolia region, north–south transect of eastern China, and Qinghai–Tibet Plateau region. The periods of the studies were from 1961 to 1970 for the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, and from 1951 to 2000 for the identification of the most sensitive combinations of physical parameters. Climatic Research Unit (CRU) data were employed. The numerical results indicate the important role of nonlinear changes in climate variability due to the occurrences of extreme events characterized by CNOP-P in the abrupt grassland ecosystem equilibrium state and formation of carbon sinks in China. Second, the most sensitive combinations of physical parameters to the uncertainties in simulations and predictions of terrestrial ecosystems identified by the CNOP-P method were more sensitive than those obtained by traditional methods (e.g., one-at-a-time (OAT) and stochastic methods). Furthermore, the improvement extent of the simulation ability and prediction skill of terrestrial ecosystems by reducing the errors of the sensitive physical parameter combinations identified by the CNOP-P method was higher than that by the traditional methods. [ABSTRACT FROM AUTHOR]

Unregulated livestock breeding and grazing can degrade grasslands and damage the ecological environment. The combination of remote sensing and artificial intelligence techniques is a more convenient and powerful means to acquire livestock information in a large area than traditional manual ground investigation. As a mainstream remote sensing platform, unmanned aerial vehicles (UAVs) can obtain high-resolution optical images to detect grazing livestock in grassland. However, grazing livestock objects in UAV images usually occupy very few pixels and tend to gather together, which makes them difficult to detect and count automatically. This paper proposes the GLDM (grazing livestock detection model), a lightweight and high-accuracy deep-learning model, for detecting grazing livestock in UAV images. The enhanced CSPDarknet (ECSP) and weighted aggregate feature re-extraction pyramid modules (WAFR) are constructed to improve the performance based on the YOLOX-nano network scheme. The dataset of different grazing livestock (12,901 instances) for deep learning was made from UAV images in the Hadatu Pasture of Hulunbuir, Inner Mongolia, China. The results show that the proposed method achieves a higher comprehensive detection precision than mainstream object detection models and has an advantage in model size. The m A P of the proposed method is 86.47%, with the model parameter 5.7 M. The average recall and average precision can be above 85% at the same time. The counting accuracy of grazing livestock in the testing dataset, when converted to a unified sheep unit, reached 99%. The scale applicability of the model is also discussed, and the GLDM could perform well with the image resolution varying from 2.5 to 10 cm. The proposed method, the GLDM, was better for detecting grassland grazing livestock in UAV images, combining remote sensing, AI, and grassland ecological applications with broad application prospects. [ABSTRACT FROM AUTHOR]

With the centralization of wind power development, power-prediction technology based on wind power clusters has become an important means to reduce the volatility of wind power, so a large-scale power-prediction method of wind power clusters is proposed considering the prediction stability. Firstly, the fluctuating features of wind farms are constructed by acquiring statistical features to further build a divided model of wind power clusters using fuzzy clustering algorithm. Then the spatiotemporal features of the data of wind power are obtained using a spatiotemporal attention network to train the prediction model of wind power clusters in a large scale. Finally, the stability of predictive performance of wind power is analyzed using the comprehensive index evaluation system. The results show that the RMSE of wind power prediction is lower than 0.079 at large-scale wind farms based on the prediction method of wind power proposed in this paper using experience based on the data of 159 wind farms in the Nei Monggol Autonomous Region in China and the extreme error is better than 25% for the total capacity of wind farms, which indicates high stability and accuracy. [ABSTRACT FROM AUTHOR]

China started the pilot project of subsidy on desertification land protection in 2013. It had been established that 71 national desertification regions were closed and protected, and followed up to monitor for several years in five northwest provinces, Inner Mongolia and Tibet since 2016, while the valuable research conclusion had not been stilly taken. In this paper, the related research and practice at domestic and abroad were reviewed. The four suggestions were put forward for the problem to be solved in time by discussing the closed target and theoretical carrying capacity, based on the key factors on affecting grassland vegetation, the more important issues and the effect of grazing prohibition and monitor as follow. 1) The achievement of investigation and monitor of closed sand land and grazing prohibition during the past years should be concluded in time for providing the basis for government management and improving the closed sand land and grazing prohibition scheme and the next decision-making. 2) The theoretical carrying capacity of desertification region should be determined, such as the actual safe carrying capacity by the basis of the theoretical carrying capacity. 3) In order to improve the practical value of monitoring data, the monitored plot should be compressed, and further revised the monitoring index system. 4) The monitoring research on the benefit of closed sand land and grazing prohibition should be shifted from monitoring the response of vegetation by grazing intensity in the past to monitoring the response of land desertification. [ABSTRACT FROM AUTHOR]

Sensitivity analysis of model parameters and inputs is an important research method to improve model accuracy and calibration efficiency. The purpose of this paper is to explore the sensitivity of model parameters and model inputs in arid areas, and then to study the linear or nonlinear relationship of model sensitivity taking Erjiama small watershed in Jungar banner, Ordos, Inner Mongolia, China as the research object. Based on the calibration of CASC2D-SED model, four model parameters, including hydraulic conductivity, Manning coefficient, Suction head and vegetation interception, and one model input-river network were perturbed at a variation rate of 25%. The hydrological process is simulated by using the combination of 20 model parameters and model inputs after perturbation, and then the sensitivity analysis of model parameters and inputs is studied. The results show that: 1) The sensitivity of Manning coefficient to peak discharge and peak arrival time is non-linear, while the sensitivity of hydraulic conductivity, Suction head and vegetation interception to peak discharge, peak arrival time, simulated total discharge and infiltration amount is linear; 2) With the increase of hydraulic conductivity, Suction head and vegetation interception, the peak discharge and simulated total discharge decrease gradually, while the peak arrival time and infiltration amount increase gradually; 3) With the increase of Manning coefficient, the simulated total flow decreases gradually, while the infiltration rate increases gradually; 4) With the increase of the number of tributaries, the peak discharge, the simulated total discharge and the total amount of infiltration gradually decrease, while the flood peak arrival time presents a U-shaped change; 5) With the increase of Manning coefficient, hydraulic conductivity, Interception and Suction head, the simulated sediment flow decreases. Manning coefficient is more sensitive to the simulated amount of clay than the other three model parameters. Sensitivity analysis of parameters and inputs of CASC2D-SED model plays a guiding role in model calibration and accurate modeling. This method can be applied to the calibration, structural uncertainty and model application of hydrological models, and has a wide range of application. [ABSTRACT FROM AUTHOR]

The resulting maps of land use classification obtained by pixel-based methods often have salt-and-pepper noise, which usually shows a certain degree of cluttered distribution of classification image elements within the region. This paper carries out a study on crop classification and identification based on time series Sentinel images and object-oriented methods and takes the crop recognition and classification of the National Modern Agricultural Industrial Park in Jalaid Banner, Inner Mongolia, as the research object. It uses the Google Earth Engine (GEE) cloud platform to extract time series Sentinel satellite radar and optical remote sensing images combined with simple noniterative clustering (SNIC) multiscale segmentation with random forest (RF) and support vector machine (SVM) classification algorithms to classify and identify major regional crops based on radar and spectral features. Compared with the pixel-based method, the combination of SNIC multiscale segmentation and random forest classification based on time series radar and optical remote sensing images can effectively reduce the salt-and-pepper phenomenon in classification and improve crop classification accuracy with the highest accuracy of 98.66 and a kappa coefficient of 0.9823. This study provides a reference for large-scale crop identification and classification work. [ABSTRACT FROM AUTHOR]

Grasshoppers can greatly interfere with agriculture and husbandry, and they will breed and grow rapidly in suitable habitats. Therefore, it is necessary to extract the distribution of the grasshopper potential habitat (GPH), analyze the spatial-temporal characteristics of the GPH, and detect the different effects of key environmental factors in the meadow and typical steppe. To achieve the goal, this study took the two steppe types of Xilingol (the Inner Mongolia Autonomous Region of China) as the research object and coupled them with the MaxEnt and multisource remote sensing data to establish a model. First, the environmental factors, including meteorological, vegetation, topographic, and soil factors, that affect the developmental stages of grasshoppers were obtained. Secondly, the GPH associated with meadow and typical steppes from 2018 to 2022 were extracted based on the MaxEnt model. Then, the spatial-temporal characteristics of the GPHs were analyzed. Finally, the effects of the habitat factors in two steppe types were explored. The results demonstrated that the most suitable and moderately suitable areas were distributed mainly in the southern part of the meadow steppe and the eastern and southern parts of the typical steppe. Additionally, most areas in the town of Gaorihan, Honggeergaole, Jirengaole, as well as the border of Wulanhalage and Haoretugaole became more suitable for grasshoppers from 2018 to 2022. This paper also found that the soil temperature in the egg stage, the vegetation type, the soil type, and the precipitation amount in the nymph stage were significant factors both in the meadow and typical steppes. The slope and precipitation in the egg stage played more important roles in the typical steppe, whereas the aspect had a greater contribution to the meadow steppe. These findings can provide a methodical guide for grasshopper control and management and for further ensuring the security of agriculture and husbandry. [ABSTRACT FROM AUTHOR]

With the rapid development of urban agglomerations in northwest arid and semiarid regions of China, the scope of the urban heat island (UHI) effect has gradually expanded and gradually connected, and has formed a regional heat island (RHI) with a larger range of impact to the regional environment. However, there are few studies on the heat island effect of urban agglomerations in arid and semiarid regions, so this paper selects the urban agglomeration of Hohhot, Baotou and Ordos (HBO) of Inner Mongolia, China as the study area. Based on the 8-day composite Moderate-resolution Imaging Spectroradiometer (MODIS) surface temperature data (156 scenes in all) and land use maps for 2005, 2010, and 2015, we analyze the spatiotemporal distributions of regional heat (cool) islands (RH(C)I) and the responses of surface temperatures to land-use changes in the diurnal and interannual surface cities. The results showed that: 1) from 2005 to 2015, urban areas showed the cold island effect during the day, with the area of the cold island showing a shrinking feature; at night, they showed the heat island effect, with the area of the heat island showing a first decrease and then an increase. 2) From 2005 to 2015, the land development (unutilized land to building land) brings the greatest temperature increase (ΔT = 1.36°C) during the day, while the greatest temperature change at night corresponds to the conversion of cultivated land to building land (ΔT = 0.78°C) exhibited the largest changes at night. From 2010 to 2015, the land development (grassland to building land) bring the greatest temperature increase (ΔT = 0.85°C) during the day, while the great temperature change at night corresponds to the conversion of water areas to building land (ΔT = 1.38°C) exhibited the largest changes at night. Exploring the spatial and temporal evolution of surface urban heat (cool) islands in urban agglomerations in arid and semiarid regions will help to understand the urbanization characteristics of urban agglomerations and provide a reference for the formulation of policies for the coordinated and healthy development of the region and co-governance of regional environmental problems. [ABSTRACT FROM AUTHOR]

Soil wind erosion is a global problem that leads to increasingly serious regional land degradation, where the need for windbreak and sand fixation services (WSFS) is substantial. Inner Mongolia plays an important role in global semiarid and arid areas and the severe land degradation resulting from soil wind erosion warrants an urgent solution. However, the mechanism of influence of various driving factors on windbreak and sand fixation services is still not fully studied. In this paper, the revised wind erosion equation (RWEQ) model was used to synthesize the monthly spatiotemporal dynamics of soil wind erosion modulus (SWEM) and WSFS in Inner Mongolia from January 2000 to February 2020 from a semi-monthly scale. The influencing factors of WSFS were examined from both natural and anthropogenic aspects. Results show that over the past 20 years, the average SWEM in Inner Mongolia was 118.06 t ha−1 yr−1, the areas with severe wind erosion were mainly concentrated in the desert areas in the southwest of Inner Mongolia, and the forests in the northeast suffered less soil wind erosion. Meanwhile, the average WSFS was 181.11 × 108 t yr−1, with the high-value areas mainly located in major deserts, sandy land, and the area bordering Mongolia in the north and the low-value areas mainly located in the densely forested northeast and the Gobi Desert in the northwest. Both SWEM and WSFS showed a clear downward trend and a certain periodicity over the past 20 years. WSFS showed two peaks a year (April and October). Among the natural factors, precipitation and NDVI showed a significant correlation with WSFS and were identified as the main driving factors of WSFS, whereas temperature had no significant correlation. Among the anthropogenic factors, farming and animal husbandry intensity and GDP showed a positive correlation with WSFS, whereas population showed a negative correlation. These four types of factors were identified as socio-economic factors that drive WSFS. Meanwhile, WSFS did not show any significant correlation with the administrative area. Land use change contributed to a large proportion of WSFS change, thereby suggesting that the intensity of human activities is another central driver of WSFS. [ABSTRACT FROM AUTHOR]

Groundwater is a primary freshwater resource for human consumption and an essential source for industry and agriculture. Therefore, understanding its spatial and temporal trends and drivers is crucial for governments to take appropriate measures to manage water resources. This paper uses Gravity Recovery and Climate Experiment (GRACE) satellite data and the Global Land Data Assimilation System (GLDAS) to derive groundwater storage anomalies (GWSAs) and to analyze the spatial and temporal trends of GWSA in different regions of China (Xinjiang, Tibet, Inner Mongolia, North China Plain, South China, and Northeast China). It used groundwater-level observation data to verify the accuracy of GWSA estimates and analyzed the drivers of regional GWSA changes. The results showed that: (1) GWSA in South China increased at a rate of 4.79 mm/a from 2003 to 2016, and GWSA in other regions in China showed a decreasing trend. Among them, the decline rates of GWSA in Xinjiang, Tibet, Inner Mongolia, North China Plain, and Northeast China were −6.24 mm/a, −3.33 mm/a, −3.17 mm/a, −7.35 mm/a, and −0.75 mm/a, respectively. (2) The accuracy of the annual-scale GWSA estimates was improved after deducting gravity losses due to raw coal quality, and the correlation coefficient between GWSA and groundwater levels monitored by observation wells increased. (3) In Xinjiang, the annual water consumed by raw coal mining, industrial, and agricultural activities had a greater impact on GWSA than rainfall and temperature, so these human activities might be the main drivers of the continued GWSA decline in Xinjiang. Water consumption by raw coal mining and industry might be the main drivers of the continued decline in GWSA in Inner Mongolia and the North China Plain. The increase in groundwater storage in South China was mainly due to the recharge of rainfall. [ABSTRACT FROM AUTHOR]

• This paper analyzes whether the financial support for grassland ecological protection and restoration has improved the vegetation coverage of grassland. • There is a nonlinear relationship between financial support for ecological restoration and grassland vegetation coverage. • Different fiscal expenditure structure has a heterogeneous response. • The degree of fiscal decentralization has a significant positive regulatory effect on the ecological benefits. Grassland ecological restoration is an important cornerstone to maintain the sustainable development of grassland ecosystem. One of the goals of financial support for grassland ecological protection and restoration is whether the ecological benefits of grassland are fully realized, and grassland vegetation coverage is the main index to measure the ecological benefits. This paper aims to analyze whether the financial support for grassland ecological protection and restoration has improved the vegetation coverage of grassland. and then verify whether there is room for improvement in the fiscal effect of grassland ecological protection and restoration? Based on the panel data of 54 animal husbandry and semi-agricultural and semi-animal husbandry counties in Inner Mongolia Autonomous Region of China, this paper adopts a bidirectional fixed effect model and cross-fixed effect model to introduce natural factors affecting grassland vegetation coverage into the model and systematically examines the financial effects of ecological benefits of financial support for grassland ecological protection and restoration. The main findings are as follows: (1) there is a nonlinear relationship between financial support for grassland ecological protection and restoration and grassland vegetation coverage when natural factors are taken into account in the model. (2) different fiscal expenditure structure has a heterogeneous response to the impact of grassland ecological protection and restoration on ecological benefits. (3) the degree of fiscal decentralization and the relative performance of the government have a significant positive moderating effect on the ecological benefits of fiscal support for grassland ecological protection and restoration. [ABSTRACT FROM AUTHOR]

In order to accurately identify targets such as insulators, shock hammers, bird nests, and spacers on high-voltage transmission lines, this paper proposes a multitarget detection model for transmission lines based on DANet and YOLOv4. First, the DANet and YOLOv4 are fused to solve the difficulty in understanding the scene and the discrimination of pixels caused by the complex and diverse scenes of UAV' (unmanned aerial vehicle) aerial images (lighting, viewing angle, scale, occlusion, and so on) so as to improve the significance of the detection target. Gaussian function and KL (Kullback–Leibler) divergence are used to improve the nonmaximum suppression in YOLOv4 so as to improve the recognition rate of occluded targets; the focal loss function and the balanced cross entropy function are used to improve the loss function of YOLOv4 in order to reduce the impact of not only the imbalance between the background and the detection target but also the imbalance among the samples, which is aimed at improving the accuracy of the detection. Then, a data set is made for the experiment by using the UAV inspection image provided by a power grid company in Eastern Inner Mongolia. Finally, the algorithm proposed in this paper is compared with other target detection algorithms. Experimental results show that the average detection accuracy of the proposed algorithm can reach 94.7%, and the detection time of each image is 0.05 seconds. The method has good accuracy, real-time, and robustness. [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]

As the essential content of intelligent animal husbandry, identifying each livestock is the only way to achieve modern and refined scientific husbandry. This paper proposes a sheep face recognition method based on European spatial metrics and realizes noncontact sheep identity recognition by training the network using sheep face image samples in the natural environment. The SheepBase data set was first proposed in this process, which contains 6559 images of Inner Mongolia fine-wool sheep and Sunite sheep. To enhance the diversity of the data, the sheep face images were data-enhanced. Secondly, to solve the problems of more redundant information in the sheep face image and the poor posture and angle of the sheep face, we propose the sheep face detection and correction (SheepFaceRepair) method. This method aims to detect the sheep face area in the image to be recognized and align the sheep face area. On this basis, we offer an open sheep facial recognition network (SheepFaceNet) based on the European spatial metric. This method incorporates the biological identity information features of the sheep face to achieve sheep identity. We also tested the effectiveness of this method in the SheepBase data set. The experimental results show that the method proposed in this paper is much higher than the other methods, and the precision of recognition reaches 89.12%. In addition, we found that integrating the biometrics of the sheep face can effectively improve the network's recognition capacity. [ABSTRACT FROM AUTHOR]

The aim of this paper is to assess the loss of grain production caused by agrometeorological disasters in the Inner Mongolia Autonomous Region (IMAR), which is an important grain production base of China. The disaster-yield assessment model was formed and verified using grain production, yield, planting area and agrometeorological disaster conditions data of the IMAR from 1981 to 2020, and the loss of grain yield caused by meteorological disasters was assessed by this model. The results showed that grain production, yield and planting area observed an escalating trend from 1981 to 2020, and the rate of increase was 78.85×104t·y-1, 100.97kg·ha-1·y-1 and 74.48×10³ha-1·y-1. The covered and affected area of agrometeorological disasters for the IMAR and National both increased and then decreased during the 1981-2020 period. Drought was the most important agrometeorological disaster in the IMAR, and the covered and affected area was 64.10% and 62.45%, respectively, accounting the total covered and affected area of all kinds of disasters in 1981-2020. The grey correlation analysis showed that drought had the highest correlation with grain yield at the level of disaster covered and affected rate, and hail had the highest correlation with grain yield at the level of disaster destory rate. The disaster-yield assessment model constructed by this study was of high simulation accuracy, and the linear regression coefficients (R²) and the slop between the simulated and measured grain yield was 0.99 and 0.98, respectively (P < 0.01). The average relative simulation yield was 0.20% and relative simulation error of the following year grain yield was 2.49%. Grain yield loss rate due to disaster in the IMAR decreased (R²=0.77，P<0.01) from 1981 to 2020 with a rate of 0.48 percentage points·y-1, and average grain yield loss rate was 14.79% and there were 68.42% of years which grain yield loss rate above 10%. The disaster-yield assessment model of the IMAR formulated in this study can simulate and predict grain yield, and assess the loss of grain yield due to disasters, which can meet the needs of agrometeorological services. [ABSTRACT FROM AUTHOR]