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Leaf area index (LAI) assessment methods relying on physical and empirical models are considered to be the most commonly used method at present, but their estimation efficiency and accuracy are deficient. Although the hybrid model of these two methods can address these issues, a poor coupling mechanism can easily occur. Given that, a PROSAIL model coupling particle swarm optimization (PSO) neural network (NN) algorithm (PSO-NN-PROSAIL model) was introduced to invert the winter wheat LAI (WWLAI) at five distinct growth stages. The Xiangfu District in the east of Kaifeng City, Henan Province was served as the study region. Based on the measured WWLAI data at varying stages and GF-1 WFV satellite images, the initial analysis focused on assessing the PROSAIL model's sensitivity in simulating vegetation canopy reflectance. It then calculated six vegetation index models according to the wavelength reflectance of GF-1 WFV and analysed their correlation with LAI to select the input parameters that could be used in the model. Normalized differential vegetation Index (NDVI) and ratio vegetation Index (RVI) as well as vegetation canopy reflectance were employed as input parameters to invert the WWLAI by adopting the PSO-NN-PROSAIL model. The experimental results showed the following: (1) In the vegetation index model, the determination coefficient (R2) of NDVI and RVI was greater than 0.68, implying that NDVI and RVI might serve as input factors for the proposed model in this paper; (2) LAI and chlorophyll a + b content (Cab) were most sensitive to the PROSAIL model in near-infrared and visible light bands; and (3) the PSO-NN-PROSAIL model possessed better LAI inversion accuracy. In summary, the model proposed in this paper provided a technical reference for rapid and accurate remote sensing monitoring of WWLAI. The optimization technology of particle swarm optimization algorithm is integrated into the neural network, and the weight of the neural network is adjusted by its fitness function transformation and inertia weight. By integrating prior knowledge into the inversion of crop leaf area index constructed by machine learning and radiative transfer model, the ill-posed problem of physical model inversion has been improved. [ABSTRACT FROM AUTHOR]

In order to overcome the limitations of traditional clean energy utilization methods, this paper proposed an innovative technical solution for a combined heating system that cleverly integrated solar, wind, and geothermal energy to achieve complementarity and synergized among them, thereby ensuring stable and efficient energy utilization. First, a comprehensive mathematical model was developed for the entire heating system, encompassing solar thermal subsystem, geothermal subsystem, wind power generation subsystem, and a second-stage reheating subsystem. Subsequently, Ebsilon simulation software was utilized to cleverly couple these subsystems together, with corresponding boundary conditions set to ensure the overall efficiency and stability of the system. Based on meteorological data and geothermal resource parameters from a typical heating season in Zhengzhou, Henan Province, China, this paper thoroughly analyzed the variations in key performance indicators such as the photothermal conversion efficiency of solar thermal subsystem and the heating capacity of geothermal subsystem. This provided valuable insight for optimizing the design of heating system. The results indicated that during the daylight hours of the heating season, both the photothermal conversion efficiency and the heat supply from the solar thermal subsystem exhibited an increasing trend as solar radiation increased. Among them, the photothermal conversion efficiency peaked at 76.013%, while the maximum heat supply output reached 40.311 kW. When solar direct radiation was relatively weak, the system primarily relied on the heat release process of the thermal storage tank to maintain heating, with a minimum heat supply of 27.268 kW. During nighttime hours of the heating season, the geothermal subsystem dominated the heating process, with a maximum heat supply of 125.556 kW. Additionally, for every 5 °C increased in geothermal water temperature, the heat supply from the geothermal subsystem increased by an average of 6.553 kW, demonstrating excellent heating response performance. Therefore, the integrated clean heating system that combines solar, geothermal, and wind energy not only significantly improves the utilization efficiency of clean energy but also enhances the heating stability of the integrated clean energy coupling system to a certain extent. The clean heating technical solution proposed in the paper had a theoretical total heating capacity of 19 680 kW during the heating season. When converted, this equates to a substitution of 6.9 tons of standard coal, resulting in a reduction of carbon dioxide emissions by 17.94 tons. This demonstrates the considerable cleanliness and environmental benefits of the proposed heating system. This study provides a valuable reference for the engineering application of renewable energy in the field of clean heating. [ABSTRACT FROM AUTHOR]

New energy vehicles (NEVs) are the main direction for the development of the global automobile industry. Evaluating and analyzing the competitiveness of new energy vehicle enterprises (NEVEs) is of great significance for promoting their development. In order to explore the current situation of NEVEs in Henan Province, this paper firstly constructs a competitiveness evaluation index system for NEVEs, comprising both quantitative and qualitative indexes. Then, a new definition of consistency, the consistency measure level, and corresponding improvement methods for interval multiplicative preference relations (IMPRs) are proposed. On this basis, fuzzy group decision-making models with IMPRs are constructed to deal with the ambiguity and uncertainty of the decision information, where consistency and consensus are both considered. In our case study, decision results are derived using Lingo 11.0 software. The results of this paper show that the degree of specialization has the greatest impact on the competitiveness of NEVEs, and some NEVEs are deficient in this regard. Related suggestions based on expert evaluation results are also provided. In addition, a comparison with other consistency improvement methods of IMPRs reveals that the methods proposed utilize the original information provided to decision-makers to the utmost degree. [ABSTRACT FROM AUTHOR]

The paper used the location entropy index, spatial gini coefficient and barycenter model to analyze the temporal and spatial changes of Chinese animal husbandry industry agglomeration from 2002 to 2021. On this basis, the fixedeffects model was constructed to explore the influencing factors of the animal husbandry industry agglomeration. The results showed that from 2002 to 2021, the agglomeration degree of Chinese animal husbandry industry exhibited a continuous upward trend. The focus of the animal husbandry industry agglomeration had been concentrated in Henan and Sichuan for a long time. The animal husbandry industry gradually gathered from the eastern to the central region. The technology input, industry correlation, economic development level and policy environment all had a positive impact on the animal husbandry industry agglomeration, while the number of labor force had no significant impact on the animal husbandry industry agglomeration. Therefore, the paper puts forward some suggestions to accelerate the clustered development of animal husbandry industry, stimulate the shift of high-qualitanimal husbandry industry elements to the centralregion, and strengthen the policy support for the animal husbandry industry agglomeration, so as to provide a reference for promoting the high-quality development of animal husbandry industry. [ABSTRACT FROM AUTHOR]

Geological hazards in Xinxian County, Xinyang City, Henan Province, are characterized by their small scale, wide distribution, and significant influence from regional tectonics. This study focuses on collapses and landslide hazards within the area, selecting twelve evaluation factors: aspect, slope shape, normalized difference vegetation index (NDVI), topographic relief, distance from geological structure, slope, distance from roads, land use cover type, area of land change (2012–2022), average annual rainfall (2012–2022), and river network density. Utilizing data from historical disaster sites across the region, the information quantity method and hierarchical analysis method are employed to ascertain the information quantity and weight of each factor. Subsequently, a random forest model is applied to perform susceptibility zoning of geological hazards in Xinxian County and to examine the characteristics of these geological disasters. The results show that in the study area, the primary factors influencing the development of geohazards are the distance from roads, rock groups, and distance from geological structure areas. A comparison of the susceptibility results obtained through two methods, the analytic hierarchy process information quantity method and the random forests model, reveals that the former exhibits a higher accuracy. This model categorizes the geohazard susceptibility in the study area into four levels: low, medium, high, and very high. Notably, the areas of very high and high susceptibility together cover 559.17 km2, constituting 35.99% of the study area's total area, and encompass 57 disaster sites, which represent 72.15% of all disaster sites. Geological hazards in Xinxian County frequently manifest on steep canyon inclines, along the curved and concave banks of mountain rivers, within watershed regions, on gully inclines, atop steep cliffs, and on artificially created slopes, among other sites. Areas with very high and high vulnerability to these hazards are mainly concentrated near the county's geological formations. The gneiss formations are widely exposed in Xinxian County, and the gneisses' strength is significantly changed under weathering, which makes the properties of the different degrees of weathering of the rock and soil bodies play a decisive role in the stability of the slopes. This paper provides a basis for evaluating and preventing geologic hazards in the Dabie mountainous area of the South Henan Province, and the spatial planning of the national territory. [ABSTRACT FROM AUTHOR]

As China's economy progresses towards high-quality development, the construction of science and technology think tanks, with talent construction as the key, has become an important supporting force and occupies a unique position in the national innovation system. In recent years, with the rapid expansion of the number of think tank talents, how to evaluate and manage think tank talents has become a key factor in the development of think tank influence and competitiveness. Based on the experience of talent team construction at home and abroad, Taking the typical science and technology innovation think tanks of Henan Province as an example, this paper analyzes the current situation and status quo of science and technology innovation think tank talents, and finds problems in the talents, Summarize the factors that affect the talent construction and development of science and technology innovation think tanks, From the perspective of six dimensions of competency model, four first-level indicators of talent quantity, talent quality, talent ability and talent contribution of science and technology innovation think tank and 16 subordinate second-level indicators are constructed for talent evaluation of think tank. Ahp is adopted to set questionnaires and collect data with Likert5-level scale, and yaahp software is used to verify the weight verification evaluation effect. Invite experts in the field to score the evaluation indicators. The research results show that the talent evaluation index of science and technology innovation think tank based on competency model pays more attention to the standardization, integration and systematization of the talent evaluation of the think tank, and the system is scientific and reasonable. It can provide reference and reference for promoting the construction, evaluation and development management of scientific and technological innovation think tanks. [ABSTRACT FROM AUTHOR]

The information released by the public on various social media platforms can assist experts in decision-making, thus improving the reliability of the decision-making results and increasing their likelihood of gaining public support. However, the determination of how to fully integrate public opinions with expert opinions and in what aspects to realize the integration is a research topic worthy of attention. Based on this, this paper proposes a multi-subject weighted information fusion method that fully considers public opinion. First, the Bayesian subject model is used to obtain the attribute set of public opinion, and the sentiment analysis technique is used to calculate the reference attribute weights. Second, public opinion is utilized to improve the traditional best–worst method to determine the subjective attribute weights of experts at a faster rate. Third, expert weights are determined using "knowledge" and attribute weights are defined at the aggregate level. Fourth, the cluster weights are determined according to the proximity of the clustered opinions to the public opinions, and the clustered opinions are then summarized to get the overall decision-making information, thus scientifically realizing the synergistic decision-making between the public and experts. Finally, the case of a rainstorm emergency in Henan Province, China, is used to analyze and determine the best plan that matches with the actual situation, and the results are then compared with the findings of existing research to illustrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Extreme precipitation usually cause grievous losses&casualties, which varies greatly under different scenarios. This paper took Henan province as an example, it innovatively constructed three different extreme precipitation scenarios and built indicators system of social vulnerability from exposure, sensitivity and resilience based on MOVE framework. Social Vulnerability Indexs(SoVI) were then calculated by mathematical models under three different reoccurrence intervals. The results show that SoVI was low in the west and high in the north. High SoVI areas expanded to the middle and south as recurrence intervals increased. SoVI in each area of Henan province increased along with the recurrence intervals at different growth rates. The larger the recurrence interval was, the faster the SoVI increased. The results indicate SoVI is greatly affected by disaster levels, which need to be incorporated into social vulnerability. This study provides not only a new thought for social vulnerability assessment, but also a reference for the policymakers to formulate related risk management policies. [ABSTRACT FROM AUTHOR]

The South-to-North Water Diversion Project (SNWDP) is believed to drive the next phase of sustainable productivity growth, meeting growing water demand, so as to address increasing environmental sustainability challenges. The Middle Route of SNWDP is regarded as an extremely large long-distance inter-basin water diversion project, which has benefited Henan, Hebei, Tianjin and Beijing since 2014 with great sustainable changes to the cities, groundwater, ecological environment, industrial structure and social development of the beneficiary areas. Taking the number of industrial enterprises above designated size (IEDS) in the water-receiving areas as the research object, this paper takes the year of policy implementation 2014 as the basic time point, evaluating the change of the number of IEDS in the beneficiary areas of the Middle Route of SNWDP through difference-in-difference model. The results show that: (1) The Middle Route of SNWDP promotes the additional growth of the number of IEDS in the beneficiary areas. (2) When the Middle Route of SNWDP promotes the growth of the number of IEDS in beneficiary areas, there is no regional difference for regions with different development levels. (3) The reasons why the Middle Route of SNWDP contributes to the additional growth of the number of IEDS are composed of promoting mixed ownership reform of enterprises in beneficiary areas, increasing water supply and increasing population. However, the Middle Route of SNWDP has not had a significant impact on the traditional total factor productivity or the components of production factors, technology and capital. From the final outcome, the South-to-North Water Diversion Project has played a facilitating role in the sustainable development of large-scale enterprises in the water-receiving areas. [ABSTRACT FROM AUTHOR]

Comprehending the spatiotemporal dynamics and driving factors of small and micro wetlands (SMWs) holds paramount significance in their conservation and sustainable development. This paper investigated the spatiotemporal evolution and driving mechanisms of SMWs in the Yellow River Basin, utilizing buffer zones, overlay analysis, and the Geodetector model based on Landsat satellite images and an open-surface water body dataset from 1990 to 2020. The results revealed that (1) from 1990 to 2020, SMWs in the Yellow River Basin exhibited an overall pattern of fluctuation reduction. The total area decreased by approximately 1.12 × 105 hm2, with the predominant decline occurring in the 0–1 hm2 and 1–3 hm2 size categories. In terms of spatial distribution, SMWs in Qinghai and Gansu decreased significantly, while the SMWs in Inner Mongolia, Henan, and Shandong gradually increased. (2) From 1990 to 2020, SMWs were mostly converted into grassland and cropland, with some transformed into impervious water surface and barren, and only a small percentage converted into other land types in the Yellow River basin. (3) The alterations in SMWs were influenced by factors, with their interplay exhibiting nonlinear or bilinear enhancement. Among these factors, annual precipitation, elevation, and potential evapotranspiration were the primary natural factors influencing the changes in the distribution of SMWs. On the other hand, land use cover type, gross domestic product (GDP), and road distance were the main anthropogenic factors. [ABSTRACT FROM AUTHOR]

Currently, there is a wealth of data and expert knowledge available on monitoring agro-meteorological disasters. However, there is still a lack of technical means to organically integrate and analyze heterogeneous data sources in a collaborative manner. This paper proposes a method for monitoring agro-meteorological disasters based on a spatio-temporal knowledge graph. It employs a semantic ontology framework to achieve the organic fusion of multi-source heterogeneous data, including remote sensing data, meteorological data, farmland data, crop information, etc. And it formalizes expert knowledge and computational models into knowledge inference rules, thereby enabling monitoring, early warning, and disaster analysis of agricultural crops within the observed area. The experimental area for this research is the wheat planting region in three counties in Henan Province. The method is tested using simulation monitoring, early warning, and impact calculation of the past two occurrences of dry hot wind disasters. The experimental results demonstrate that the proposed method can provide more specific and accurate warning information and post-disaster analysis results compared to raw records. The statistical results of NDVI decline also validate the correlation between the severity of wheat damage caused by dry hot winds and the intensity and duration of their occurrences. Regarding remote sensing data, this paper proposes a method that directly incorporates remote sensing data into spatio-temporal knowledge inference calculations. By integrating remote sensing data into the regular monitoring process, the advantages of remote sensing data granted by continuous observation are utilized. This approach represents a beneficial attempt to organically integrate remote sensing and meteorological data for monitoring, early warning, and evaluation analysis of agro-meteorological disasters. [ABSTRACT FROM AUTHOR]

The Huayuankou flood event (1938–1947) refers to the prolonged flooding caused by the artificial bursting of the Yellow River embankment at Huayuankou during the Sino-Japanese War (1937–1945). It recreated the historical scenes of frequent floods in the lower Yellow River region of China since the Ming and Qing Dynasties (1368–1911), with the counties along the Jialu River in the eastern plains of Henan especially becoming the disaster-stricken areas. The flood lasted for nearly nine years until the completion of embankment restoration work in 1947, causing long-term and extensive environmental impacts. This paper discusses this catastrophic historical flood event caused by human factors, the warfare strategies and hydraulic technology that acted as drives, and the location factors and historical context leading to the start of flooding in flood-prone areas of Henan. Based on spatial perspectives and the historical GIS approach, the paper compiles and integrates historical documents and maps with archival material and topographic maps from the 1930s and 1940s to present the extent of the flood, the associated disasters, and the persistent effects of official relief strategies and political situation in the wider context, examining how the Huayuankou flood was used as a military tactic, but with unpredictable disastrous consequences. [ABSTRACT FROM AUTHOR]

This paper utilizes high-resolution ERA5 hourly data from 1980 to 2020 and long-term normalized difference vegetation index (NDVI) time series obtained from remote sensing and applies trend analysis, correlation analysis, lag analysis, and other methods to study the spatiotemporal characteristics of extreme rainfall at daily and hourly scales in the Huang-Huai-Hai Plain. The paper explores the NDVI's variability and its relationship with extreme hourly precipitation and analyzes the main factors affecting it. The study made the following observations: (1) The extreme daily precipitation in the Huang-Huai-Hai Plain shows a decreasing trend, with a 13.6 mm/yr reduction rate. In contrast, the proportion of extreme rainfall to total precipitation generally exceeds 20%, and the intensity of extreme rain has gradually increased. The spatial distribution pattern of extreme rainfall follows the distribution pattern of China's rain belts, with the terrain being an important influencing factor. The high-incidence areas for extreme rainfall are the Huaihe River region and the Shandong Peninsula. (2) The observed significant increase in hourly extreme precipitation events in the Shandong and Henan provinces of the Huang-Huai-Hai Plain has led to an increased risk of flooding, while the corresponding events in the northwest region of the Plain have exhibited a gradual weakening trend over time. (3) The extreme hourly precipitation in the Huang-Huai-Hai plain shows a frequent and scattered pattern, with decreasing intensity over time. Extreme precipitation mainly occurs in the first half of the night, especially between 19:00 and 21:00, with extreme hourly rainfall intensity fluctuating between 0.2 and 0.25 and the proportion of rainfall to total precipitation reaching as high as 10%. The spatial distribution of extreme hourly rainstorms during the peak period (19:00–21:00) exhibits a high rainfall volume, intensity, and frequency pattern in the eastern region, while the western part exhibits low rainfall volume, intensity, and frequency. (4) The incidence of extremely heavy rainfall in an hour has exhibited a more significant increase compared to extreme daily events in the Huang-Huai-Hai Plain, primarily in the form of backward-type precipitation. Hourly extreme precipitation events in the Huang-Huai-Hai Plain are affected by terrain and land use/cover change (LUCC), with the micro-topography of hilly areas leading to a concentrated distribution of precipitation and LUCC suppressing extreme precipitation events in arid climates. (5) At the ten-day scale, the spatial distribution of the NDVI shows a gradually increasing trend from northwest to southeast, with the highest NDVI value reaching up to 0.6 in the southern part of the study area. For extreme hourly precipitation, there is no significant change observed at the multi-year ten-day scale; while the NDVI in the northern and central parts of the Huang-Huai-Hai Plain shows a significant decreasing trend, in contrast, it presents a significant increasing trend in the southern region. (6) Finally, the correlation between NDVI at the ten-day scale and extreme hourly precipitation exhibits a decreasing pattern from north to south, with a correlation coefficient decreasing from 0.48 to 0.08. The lagged correlation analysis of extreme hourly rainfall and NDVI for one, two, and three ten-day periods shows that the lagged effect of extreme hourly precipitation on NDVI is negligible. Analyzing the correlation between extreme hourly rainfall and NDVI for different months, the impact of extreme hourly precipitation on NDVI is predominantly negative, except for June, which shows a positive correlation (0.35), passing the significance test. This study offers a scientific foundation for enhancing disaster warning accuracy and timeliness and strengthening the research on disaster reduction techniques. [ABSTRACT FROM AUTHOR]

Volunteered geographic information (VGI) plays an increasingly crucial role in flash floods. However, topic classification and spatiotemporal analysis are complicated by the various expressions and lengths of social media textual data. This paper conducted applicability analysis on bidirectional encoder representation from transformers (BERT) and four traditional methods, TextRank, term frequency–inverse document frequency (TF-IDF), maximal marginal relevance (MMR), and linear discriminant analysis (LDA), and the results show that for user type, BERT performs best on the Government Affairs Microblog, whereas LDA-BERT performs best on the We Media Microblog. As for text length, TF-IDF-BERT works better for texts with a length of <70 and length >140 words, and LDA-BERT performs best with a text length of 70–140 words. For the spatiotemporal evolution pattern, the study suggests that in a Henan rainstorm, the textual topics follow the general pattern of "situation-tips-rescue". Moreover, this paper detected the hotspot of "Metro Line 5" related to a Henan rainstorm and discovered that the topical focus of the Henan rainstorm spatially shifts from Zhengzhou, first to Xinxiang, and then to Hebi, showing a remarkable tendency from south to north, which was the same as the report issued by the authorities. We integrated multi-methods to improve the overall topic classification accuracy of Sina microblogs, facilitating the spatiotemporal analysis of flooding. [ABSTRACT FROM AUTHOR]

Henan Province is the birthplace of Chinese civilization and one of the earliest human settlements, which means that the area has an important national cultural heritage. Traditional villages are an important facet of this cultural heritage, and studying their spatiotemporal characteristics in different periods has important theoretical and practical significance for the sustainable development and protection of cultural heritage in the region. This paper takes the traditional villages of the Yellow River basin in Henan Province that were formed before 1919 as the research object. Information on the ancient river was obtained through a literature search as well as via field research, and the important tributaries of the Yellow River in different periods were mapped using ArcGIS 10.0 software. The nearest neighbor index, kernel density estimation, standard deviation ellipse and other methods were adopted to analyze the spatiotemporal characteristics of the traditional villages. The factors that influenced the evolution of traditional villages were explored in depth by combining changes in the course of the river and water conservancy projects. The results show that the formation of traditional villages along the Yellow River in Henan Province has experienced a historical track of growth, contraction, growth and prosperity and stability. The traditional villages along the Yellow River in Henan Province generally show a clustered pattern, forming a dense concentration of traditional villages in the middle reaches of the Yellow River. The center of gravity shows a migration trend from southeast to northwest. In terms of influencing factors, the spatiotemporal evolution of the relationship between villages and their distance to water is closely related to climatic fluctuations, changes in channel, water conservancy projects and social and cultural factors. This paper deepens our understanding of the relationship between traditional village evolution and watersheds by improving the consistency between village spatial distribution and historical geography and provides a useful theoretical reference for the sustainable development of China's traditional villages. [ABSTRACT FROM AUTHOR]

Tea plants are evergreen broad-leaved perennial shrubs, and their spectral characteristics are very similar to those of other evergreen vegetation, making it difficult to distinguish them. Currently, the most commonly used method of tea plantation extraction is machine learning, which classifies tea plantation through various feature combinations and algorithms. The disadvantage of these methods is that they require a large number of local training samples, making it challenging to produce an accurate model applicable to a large region. Furthermore, complex feature combinations and indicators may result in over-fitting, reducing the accuracy of the results. Therefore, it is necessary to develop a new algorithm suitable for tea plantation extraction in extensive regions. This paper uses Shihe District, Henan Province, China as a case in 2019, combined with Landsat-7/8 and Sentinel-2A/B images, and develops a new phenological-based algorithm to extract the tea plantation area. Firstly, we generated an evergreen vegetation map. Secondly, based on high-quality time series curves, the tea plant growth period was divided into seven parts to extract phenological indicators for classification. Finally, the tea plantation in the study area was extracted on a per-pixel basis. The overall accuracy of the algorithm is 87.59%, and the Kappa coefficient is 0.80. This study demonstrates the potential of the phenology-algorithms in extracting tea plantation areas and provides an advanced scheme and scientific basis for extracting tea plantation in other years, and also offers a reference for identifying tea plantation in other regions. Additionally, this paper generated a map of classified phenological indicators to provide guidance for monitoring tea plants growth. [ABSTRACT FROM AUTHOR]

Due to the co-combustion of hydrogen-rich atmosphere and coal in power plants has a great influence on NO X emission, it has been studied by more and more researchers. Therefore, the study of the effect of hydrogen-rich atmosphere on coal pyrolysis mechanism provides a theoretical basis for subsequent application in power plants. In this paper, reaction molecular dynamics simulation is used to investigate the pyrolysis mechanism of Henan anthracite coal within the temperature range of 300–3600 K. The consistency between the activation energy, TG curve, and gas release characteristics derived from the ReaxFF simulation and the experimental results provides evidence for the validity of this method in investigating the pyrolysis mechanism of coal. Furthermore, the pyrolysis behavior of Henan anthracite coal in N 2 , H 2 , and NH 3 atmospheres with varying temperatures are studied. The pyrolysis of Henan anthracite coal can be categorized into three distinct stages under varying atmospheric conditions, as revealed by the simulation findings. Compared with N 2 pyrolysis atmosphere, H 2 and NH 3 pyrolysis atmospheres can reduce the release of CO, reduce the activation energy, promote the degree of pyrolysis and accelerate the pyrolysis process. NH 3 atmosphere has more obvious influence on the coal pyrolysis process. Also, HCN (NO X precursor) generation reactions during pyrolysis are revealed in N 2 , H 2 and NH 3 atmosphere. H 2 and NH 3 pyrolysis atmospheres can increase the number of HCN generation reactions and change the distribution of HCN generation reactions. The analysis of HCN formation reaction shows that CN and H 2 CN are the main precursors of HCN. • Henan coal pyrolysis is studied via ReaxFF MD. • The macromolecular model of Henan coal has been verified. • In NH 3 atmosphere, the activation energy of Henan coal pyrolysis is reduced. • The HCN generation reaction in different atmosphere is proposed. [ABSTRACT FROM AUTHOR]

To meet the needs of professional development promotion through cross-university collaborative construction in the era of Internet + , a new model of cross-university teaching and research organization is proposed by constructing a regional virtual teaching and research room for remote teaching and research activities among grassroots teaching organizations of different universities, utilizing modern information technology. Led by the national first-class specialty construction site of Building Electrical and Intelligent Specialty at Zhengzhou University of Light Industry, a cross-university regional virtual teaching and research room for this specialty is established in collaboration with other universities offering the same specialty in Henan province. This paper outlines the efficient and stable operation mechanism for the regional virtual teaching and research room's multi-university collaborative construction and explores the co-construction path for cross-university regional virtual teaching and research rooms. A high-quality resource sharing platform for multi-university collaborative construction is built within the regional virtual teaching and research room, enabling intercollegiate high-quality resource and outstanding teaching team interconnection, co-construction, and sharing. This approach aims to fully leverage the distinctive features and advantages of the Building Electrical and Intelligent Specialty in each university in the region, promote cooperative development and interdisciplinary integration among partnering universities, and improve the quality of talent cultivation. It may also provide valuable reference and guidance for the collaborative construction of virtual teaching and research rooms across a broader range of universities. [ABSTRACT FROM AUTHOR]

Carbon emission reduction is an important part of regional low-carbon economic development. In this paper, gray correlation analysis, neural network model, Gaussian multi-mode fitting and other methods were used to analyze the relationship between total carbon emissions and regional economic development, industrial structure, and energy consumption in Henan Province. On this basis, the future development of carbon emissions is predicted. The calculation results showed that the correlation between the three industries and carbon emissions in Henan Province is more than .7, among which the secondary industry has the highest correlation (.77). In the secondary industry, the correlation coefficient between coal and carbon emissions is the highest .87, while the correlation coefficient between other energy sources is about .5. In the neural network prediction model, the correlation coefficient between the prediction curve and the actual total carbon emission curve is .989, and the prediction results have a good degree of fit. The carbon emission prediction curve was divided into two parts: a linear decline stage from 2018 to 2024, and a rapid decline stage after 2024.The results showed that more efforts should be made in industrial structure, energy consumption structure and environmental protection to achieve low-carbon development in Henan province. [ABSTRACT FROM AUTHOR]

Ammonia emission has attracted considerable attention concerning environmental protection in the world. About 33% of the atmospheric ammonia emission comes from farmland fertilization, so the monitoring of ammonia emissions from farmland is of great significance for controlling atmospheric ammonia pollution. In recent years, tuneable diode laser absorption spectroscopy (TDLAS) has been applied to the measurement of farmland ammonia emission; however, the spectral signal of the open optical path is susceptible to distortion due to temperature, noise, turbulence, etc. Meanwhile, the inversion of the distorted spectrum will result in abnormal concentration values that reduce the detection accuracy. This paper proposes a TDLAS spectral quality evaluation method based on dynamic time warping (DTW) algorithm and support vector data description (SVDD) algorithm. DTW algorithm was used to analyse the similarity between the measured spectrum and the reference spectrum, then SVDD algorithm was used to generate a classification model according to the results of DTW algorithm. DTWSVDD algorithm could effectively avoid obtaining wrong inversion concentration and improve the accuracy of concentration monitoring with identification accuracy of spectral quality reached more than 98%. Applied to the measurement of farmland ammonia emission in Fengqiu, Henan Province, China at the Agricultural Ecological Experiment Station of Chinese Academy of Sciences in November 2021, this method could effectively reduce the dispersion degree of measured concentration trend, as a result, which was better than that of the reported correlation coefficient method. DTW-SVDD algorithm should be of further research value for the application of the analysis of the Big Data of atmospheric composition detection based on grand-based optical remote sensing system. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the temporal and spatial variation of PM2.5 pollution in Henan Province in 2021, based on monitoring and meteorological data. The findings indicate that areas with high concentrations of PM2.5 are primarily distributed in the central and northern parts of Henan Province, while areas with low values are primarily distributed in the southeast part of Henan Province. In winter, PM2.5 concentrations are high in the southwest and east-central parts, and lower in the southeast and northwest. The seasonal variation of PM2.5 concentration is low in summer and high in spring and winter. The monthly average of PM2.5 concentration exhibits a U-shaped pattern, with low values in the summer and higher values in the winter. The difference between workday and weekend PM2.5 concentrations is minor, and the daily average presents a pulse-type fluctuation. Peak PM2.5 concentrations occur in the morning in all seasons, while in winter the peak time is significantly postponed compared to other seasons. The most polluted cities distributed in northeastern Henan Province form a high-high agglomeration, and the cities located in northwestern Henan Province form a low-low agglomeration. [ABSTRACT FROM AUTHOR]

[Display omitted] • Environmental performances of plastic bag and alternatives are assessed in China. • Multi-regional scenarios are evaluated considering the uneven waste management. • Overall, HDPE plastic bags cause the lowest environmental impacts. • Using alternatives will induce the largest GWP changes in Henan and Hebei. • Introducing alternatives requires systematic thinking especially waste disposal. Single-use plastics (SUPs) have been the focus of plastic pollution control, and limiting their use while shifting to other alternatives have been widely promoted in various countries. This study tries to verify the life cycle environmental performances of single-use plastic bag and its alternatives under different scenarios in real world. China is chosen as case study, where provincial variability is prominent in waste disposal, and strictest plastics ban has issued lately in this worldwide biggest market. The study found that HDPE plastic bags have relatively lowest environmental footprints regarding to Acidification Potential, Global Warming Potential, Chemical Oxygen Demand, Eutrophication Potential, Fossil Fuel Depletion Potential and Water Use. Sticking to current waste treatment, large-scale promotion of degradable products will increase environmental impacts by 1.4–22.6 times nationwide. Xinjiang has highest impact of using plastic bag at household level, due to its long-distance transport and high landfill ratio. Henan and Hebei will trigger the most significant changes in Global Warming Potential of 4.6 and 4.4 times if single-use plastic bags are all replaced with other alternatives. Uncertainty and sensitivity test further prove the robustness of results, and extends geographical implications of the findings. These suggest that introduction of new alternatives requires systematic deployment with full life cycle thinking, and SUPs pollution control should be a holistic transformation. Reducing bag weight while ensuring carrying capacity, purchasing local products to shorten transportation distances and shifting towards cleaner energy sources are synergetic ways to reduce the environmental impact of single-use plastic products. [ABSTRACT FROM AUTHOR]

Since China's reform and opening up in 1978, the acceleration of industrialization and urbanization in China had led to dramatic changes in the pattern of urban-rural land use. In this paper, we focused on the rural industrialized areas in central China (Xinxiang County and Changyuan City of Henan Province). We used the average nearest neighbor index, spatial statistical analysis, and a structural equation model to analyze the spatiotemporal evolution and influencing factors of urban-rural construction land based on multi-source spatial data and survey data. The results showed that: 1) from 1975 to 2019, the spatial distribution of urban-rural construction land in rural industrialized areas had evolved from homogeneous distribution to local agglomeration. In terms of comparative analysis of cases, the spatial distribution of urban-rural construction land in Changyuan City had shown a trend from diffusion to agglomeration, and Xinxiang County had overall shown a spatial change from homogenization to agglomeration and then to regional integration development. 2) The hot spots with increased urban-rural construction land significantly expanded, and they had a high degree of spatial overlap with industrial development. Among them, Xinxiang County was concentrated in central and marginal areas, and Changyuan was mainly concentrated in central urban areas. 3) From the evolution of spatial proximity of urban-rural construction land, rural industrialized areas generally decline, showing the characteristics of internal differentiation in the rate of change. 4) Industrial development, social economy, the policy environment, and urban development played a positive role in promoting the expansion of urban-rural construction land in rural industrialized areas. To promote the optimal use of regional land and the integrated development of urban-rural areas, we should combine the advantages of regional endowment, formulate development strategies according to local conditions, and adjust the way that land is used in a timely manner. [ABSTRACT FROM AUTHOR]

Eucommia ulmoides Oliver. (E. ulmoides) is a species of small tree native to China. It is a valuable medicinal herb that can be used to treat Alzheimer's disease, diabetes, hypertension, and other diseases. In addition, E. ulmoides is a source of rubber. It has both medicinal and ecological value. As ecological problems become increasingly prominent, accurate information on the cultivated area of E. ulmoides is important for understanding the carbon sequestration capacity and ecological suitability zoning of E. ulmoides. In previous tree mapping studies, no studies on the spectral characteristics of E. ulmoides and its remote sensing mapping have been seen. We use Ruyang County, Henan Province, China, as the study area. Firstly, using the 2021 Gao Fen-6 (GF-6) Wide Field of View (WFV) time series images covering the different growth stages of E. ulmoides based on the participation of red-edge bands, several band combination schemes were constructed. The optimal time window to identify E. ulmoides was selected by calculating the separability of E. ulmoides from other land cover types for different schemes. Secondly, a random forest algorithm based on several band combination schemes was investigated to map the E. ulmoides planting areas in Ruyang County. Thirdly, the annual NPP values of E. ulmoides were estimated using an improved Carnegie Ames Stanford Approach (CASA) to a light energy utilization model, which, in turn, was used to assess the carbon sequestration capacity. Finally, the ecologically suitable distribution zone of E. ulmoides under near current and future (2041–2060) climatic conditions was predicted using the MaxEnt model. The results showed that the participation of the red-edge band of the GF-6 data in the classification could effectively improve the recognition accuracy of E. ulmoides, making its overall accuracy reach 96.62%; the high NPP value of E. ulmoides was mainly concentrated in the south of Ruyang County, with a total annual carbon sequestration of 540.104835 t CM−2·a−1. The ecological suitability zone of E. ulmoides can be divided into four classes: unsuitable area, low suitable area, medium suitable area, and high suitable area. The method proposed in this paper applies to the real-time monitoring of E. ulmoides, highlighting its potential ecological value and providing theoretical reference and data support for the reasonable layout of E. ulmoides. [ABSTRACT FROM AUTHOR]

Based on panel data of 285 Chinese cities from 2005 to 2020, this paper uses a set of regional economic analysis tools to explore the spatial and temporal characteristics of urban industrial pollution and its drivers. The results of the research show that the Urban Industrial Pollution Index (UIPI) has shown a significant downward trend overall. However, high levels of industrial pollution are found in the areas where the four major industrial bases are located. The overall development gap of the UIPI shows a fluctuating upward trend. In terms of the contribution of development differences, supervisory density is the highest, followed by intra-regional differences, and inter-regional differences are the lowest. The UIPI has a strong spatial dependence, with a concentration in Henan Province. It is spatially distributed in a “northeast-southwest” direction, with a tendency of diffusion and transfer to surrounding cities. Urban industrial pollution is significantly suppressed by human capital, capital stock, technological innovation and economic agglomeration. Human capital and economic agglomeration can suppress industrial pollution in surrounding cities through spatial spillovers. In addition, a number of influencing factors have a heterogeneous impact on urban industrial pollution across regions. [ABSTRACT FROM AUTHOR]

[Objective] The present paper aimed to explore the grain production pattern and influencing factors in the major production areas, provided a certain basis for stabilizing the overall situation of national food security and formulating differentiated grain policies. [Method] By means of concentration degree, gini coefficient, logarithmic mean divisia index and cultivated land pressure index, quantitatively analyzed the factors influencing the increase of grain production in major grain producing areas from 2000 to 2020, such as the change of grain production center, variety structure, contribution to increase production, resource bearing capacity and production cost. [ Result] ( i) From the change of grain production center, more than 95 % of the grain increment came from the major grain producing areas, and the major producing areas in the north contributed more to the increase, especially Shandong, Henan and Heilongjiang, which occupied the top three areas of grain output and sown area for a long time. (ii) In terms of the production centers of different food crops, the production centers of wheat, com and beans were stable in the major grain producing areas in the north for a long time, while the production centers of rice and potato were mainly concentrated in the major grain producing areas in the south, but the production centers of rice gradually showed a trend of northward deviation. (iii) From the perspective of contributing factors, the grain increase in the major grain producing areas mainly depended on the increase of yield per unit area, and the contribution rate of yield per unit area to grain increase reached 61. 16%. The grain increase in the major grain producing areas in the north was due to the combined effect of cultivated land area, multiple cropping index, grain crop proportion and yield per unit area. Due to the decrease of cultivated land area in the major grain producing areas in the south had a negative effect on grain increase, the grain yield increase was more dependent on unit yield increase and multiple cropping index. (iv) From the perspective of resource carrying capacity of grain production, the dilemma of uneven distribution of water and soil resources has not been improved for a long time. The constraints of water resources in the major grain producing areas in the north were increasingly strengthened, while the pressure of cultivated land resources in the major grain producing areas in the south was continuously high. ( v) From the change and structure of grain production cost, the average grain production cost in the major grain producing areas was rising continuously. The land cost in the major grain producing areas in the north was higher, and the labor cost in the major grain producing areas in the south was higher. The grain production cost in the major grain producing areas in the north was higher than the whole country and the major grain producing areas in the south for a long time, and the rising rate was slightly faster than that in the major grain producing areas in the south. [Conclusion] Establishing the food security responsibility mechanism shared by the producing and marketing areas, constructing the differentiated compensation mechanism; Strictly observing the grain sown area, adjusting the structure of regional grain varieties; Consolidating scientific and technological support for grain increase, promoting coordinated development of water and soil resources and grain production; Taking multiple measures to improve grain production efficiency, and enhancing the enthusiasm of various subjects to grow grain. [ABSTRACT FROM AUTHOR]

• The matrix representation of grey possibility function is provided. • The solution method of possibility function's turning points is given. • The "maximum criterion" decision paradox is solved. • A variable stage self-correcting grey clustering model is proposed. • The meteorological drought grade of 17 stations in china henan province is evaluated. The grey clustering model based on the possibility function is frequently used in system evaluation, but the setting of the possibility function is frequently subjective, which results in the weak credibility of the clustering results. In addition, the "maximum criterion" decision paradox of the model has fuzzy boundaries, making the clustering process impossible to program. Based on this, the possibility function is represented as a matrix in the paper, and the possibility function is calculated by an optimization model to guarantee the objectivity of the clustering results. A variable stage self-correcting grey clustering model is built by using the kernel weight transformation as the primary tool, "entropy subtraction" as the signal of the decision paradox, and "entropy non-subtraction" as the model's termination signal. The model's Matlab source code is provided to reduce the complexity of the model. The illustration and comparative analysis demonstrate the model's logic and efficacy. Using the model for the evaluation of the meteorological drought grade in Henan Province can offer a fresh perspective for meteorological departments to make choices and assessments. [ABSTRACT FROM AUTHOR]

Wanmai 788 is a new wheat variety bred by Nanyang Academy of Agricultural Sciences and approved by Henan Province in 2021. This variety is characterized by high yield, multiple resistance, wide adaptability and high quality weak gluten, and is suitable for planting in wheat areas in the middle and lower reaches of the Yangtze River in the central and southern part of Henan Province. This paper introduces the breeding process, characteristics, yield performance and brief cultivation techniques of Wanmai 788, and discusses the key breeding techniques of the variety. [ABSTRACT FROM AUTHOR]

The development and utilization of biomass energy based on the thermochemical conversion of crop biomass to produce hydrogen are of great significance for promoting China's ecological civilization construction, energy revolution, and low-carbon economic development. Henan province is one of the largest agricultural and pasturage provinces in China. Based on the analysis of the status and trends of Henan's biomass energy (BE) development, this paper summarizes the present status of the construction of ecological civilization (CEC) and the factors restricting its development. Challenges in developing biomass energy are analyzed systematically, and strategies and key technical directions for future biomass energy development are discussed. Finally, the paper presents countermeasures and suggestions for CEC based on the development of BE, which will vigorously promote the development and utilization of BE and the process of CEC. This research provides a reference for the further development of BE and CEC in the future. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to propose a pseudo-grey metabolic grey Markov model to deal with the prediction issue in which the original sequences are oscillation sequences. Design/methodology/approach: First, the original sequences were processed with the accelerated advection transformation and the weighted mean generation transformation to make them smoother. Then, the mean GM (1, 1) model was applied to the multi-step prediction of the pre-processed data sequences. Finally, with the help of the optimal partitioning method, the pseudo-grey metabolic Markov model was used to correct the prediction results and determine the final prediction values. Findings: The results demonstrate that the accuracy of this model is significantly higher than that of the traditional grey Markov model, which further verifies the rationality of the proposed model. Therefore, scientific and reasonable prediction of urban rainfall is of great theoretical significance and application value for the government and decision-making departments to formulate drought prevention and disaster mitigation measures. Originality/value: The model in this paper not only provides new ideas for the data preprocessing problem of the grey Markov model, but also solves the problem of errors due to individual subjectivity in state interval division. It provides a novel idea for the development of grey prediction models. The rationality and validity of the model are illustrated by taking the Zhengzhou City of Henan Province as examples. [ABSTRACT FROM AUTHOR]

In order to explore the technical methods to improve the ecological carrying capacity of regional land under the premise of limited land use area, an open ecological footprint model is established based on the traditional ecological footprint model. Using the two models, this paper evaluates the ecological carrying capacity of Henan Province in 2017. The results indicate that the ecological productive footprint of cultivated land in Henan Province is much larger than the ecological carrying capacity, but the ecological consumption footprint is lower than the ecological carrying capacity. The open ecological footprint model can clearly distinguish the internal and the external ecological consumption footprint after corrected by the consumption adjustment coefficient and the land-use structure adjustment coefficient. Based on the open ecological footprint model, the ecological carrying capacity evaluation results of Henan Province are more realistic. The comprehensive ecological carrying capacity in Henan Province has a surplus, but there are significant differences among different land use types. The cultivated land has the largest ecological carrying capacity surplus, while the fossil energy land has a larger ecological carrying capacity deficit. In the process of achieving sustainable development, Henan Province should focus on reducing energy consumption and improving the ecological carrying capacity of fossil energy land. The paper concludes that the open ecological footprint model can simulate the ecological carrying capacity under different land use structures and different consumption structures. According to the simulation results, the technical methods to improve the ecological carrying capacity under the premise of limited land use scale can be proposed. The research can provide reference for land use structure adjustment, land use planning and land protection in Henan Province. It can also provide scientific basis for ecological protection and high-quality development of the Yellow River basin. [ABSTRACT FROM AUTHOR]

Analyzing the working conditions of a dam using safety monitoring indices (SMIs) is a relatively intuitive and effective method for dam safety evaluation. Therefore, a reasonable and accurate method for determining the SMIs of a dam is of vital importance for dam safety assessment. However, the current methods for determining the SMIs of dams, especially roller-compacted concrete (RCC) dams, have many shortcomings, such as ignoring the construction process of the dam, the coupling effect among multiple physical fields, etc. In this paper, a novel SMI determination method considering the seepage–stress coupling effects was proposed for RCC dams with the assistance of a constructed seepage and stress coupling model so as to address the deficiency of existing RCC dams in determining SMIs. The coupled mathematical model was developed in COMSOL Multiphysics to establish a finite element analysis model of an RCC gravity dam in Henan Province, China. Moreover, the seepage anisotropy of the RCC construction layers was also considered in the model. Finally, the seepage, stress, and deformation characteristics of the RCC dam were analyzed based on the model, and the seepage and deformation SMIs of the dam were determined and compared with traditional methods. The results show that seepage, stress, and displacement fields are distributed similarly for both coupled and uncoupled models. However, in contrast to the uncoupled model, the hydraulic head contour distribution is more dispersed in the coupled model. Additionally, the stress and displacement simulated by the coupled model increase at different rates, with a more pronounced stress concentration near the dam heel. Comparing the seepage and stress SMIs of RCC dam obtained from different methods, it was found that the indices of dam seepage discharge and crest displacement that are calculated by considering the seepage–stress coupling effect and anisotropic characteristics of RCC construction layers are 34.78% and 31.98% lower than results obtained by ignoring these two effects, respectively. Therefore, it is crucial to consider the seepage–stress coupling effect and the anisotropic characteristics of RCC when determining the SMIs for RCC dams. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, the phase-out of coal from the energy structure has resulted in numerous old coal mines that possess abundant underground space resources suitable for underground pumped hydroelectric energy storage (UPHES). Site selection and estimation of potential are critical to the planning and implementation of UPHES in old coal mines. This paper introduces a two-step site selection concept, including a screening assessment followed by a comprehensive assessment, to determine suitable locations for UPHES. The screening indicators in the screening assessment comprise geological features, mine water disasters, and minimum installed capacity, while the analytic hierarchy process (AHP) is applied in the comprehensive assessment. Additionally, coal mines in Henan Province are preliminarily screened through the screening assessment and the potential for UPHES is thoroughly investigated. The estimated volume of the drifts and shafts in old coal mines is approximately 1.35 × 107 m3, while in producing coal mines, it is around 2.96 × 107 m3. Furthermore, the corresponding annual potential for UPHES is 1468.9 GWh and 3226.3 GWh, respectively. By consuming surplus wind and solar power, UPHES is able to reduce 4.68 × 105 tonnes of carbon dioxide (CO2) emissions. The study provides preliminary guidance for policy-makers in developing UPHES in old coal mines. [ABSTRACT FROM AUTHOR]

Farmers' green production transformation can ensure the quality and security of agricultural products to a certain extent and alleviate the pressure of the agricultural environment. It is essential to understand the impact of socialized agricultural services on the degree of farmers' green production transformation. Based on 1018 survey responses of farmers in Henan, Shandong, and Shanxi provinces, this paper used the finite mixture model to calculate the degree of farmers' green production transformation and used the propensity score matching (PSM) model to construct the counterfactual hypothesis to estimate the average processing effect and heterogeneity of socialized agricultural services on the degree of farmers' green production transformation. The results showed that: 1 The production mode of wheat growers could be divided into traditional production mode and green production mode. The proportion of wheat growers engaged in green production accounted for 20.33%; their fertilizer application was reduced by 363.35 kg/hm², and their pesticide cost was reduced by 418.73 yuan/hm². 2 Fertilization services and plant protection services could significantly promote the wheat growers' green production transformation, and their average treatment effects were 0.109 and 0.152, respectively. Compared with fertilization services, plant protection services promoted wheat growers' green production transformation to a greater extent. After farmers purchased fertilization services and plant protection services, the corresponding chemical input costs per hectare were reduced by 204.06 yuan and 284.56 yuan, respectively. 3 The impact of socialized agricultural services on farmers' green production transformation was significantly heterogeneous. The average treatment effect on green production transformation was more significant for part-time farmers and farmers trained in agricultural technology who purchased the services. Therefore, we should vigorously cultivate the socialized agricultural service market, strengthen the support for such services in different sectors, guide farmers with different endowments to reasonably purchase such services, and promote farmers' green production transformation. [ABSTRACT FROM AUTHOR]

Regional land-use change is the leading cause of ecosystem carbon stock change; it is essential to investigate the response of LUCC to carbon stock to achieve the strategic goal of "double carbon" in a region. This paper proposes a residual network algorithm, the Residual Multi-module Fusion Network (R-MFNet), to address the problems of blurred feature boundary information, low classification accuracy, and high noise, which are often encountered in traditional classification methods. The network algorithm uses an R-ASPP module to expand the receptive field of the feature map to extract sufficient and multi-scale target features; it uses the attention mechanism to assign weights to the multi-scale information of each channel and space. It can fully preserve the remote sensing image features extracted by the convolutional layer through the residual connection. Using this classification network method, the classification of three Landsat-TM/OLI images of Zhengzhou City (the capital of Henan Province) from 2001 to 2020 was realized (the years that the three images were taken are 2001, 2009, and 2020). Compared with SVM, 2D-CNN, and deep residual networks (ResNet), the overall accuracy of the test dataset is increased by 10.07%, 3.96%, and 1.33%, respectively. The classification achieved using this method is closer to the real land surface, and its accuracy is higher than that of the finished product data obtained using the traditional classification method, providing high-precision land-use classification data for the subsequent carbon storage estimation research. Based on the land-use classification data and the carbon density data corrected by meteorological data (temperature and precipitation data), the InVEST model is used to analyze the land-use change and its impact on carbon storage in the region. The results showed that, from 2001 to 2020, the carbon stock in the study area showed a downward trend, with a total decrease of 1.48 × 10 7 t. Over the course of this 19-year period, the farmland area in Zhengzhou decreased by 1101.72 km 2 , and the built land area increased sharply by 936.16 km 2 . The area of land transfer accounted for 29.26% of the total area of Zhengzhou City from 2001 to 2009, and 31.20% from 2009 to 2020. The conversion of farmland to built land is the primary type of land transfer and the most important reason for decreasing carbon stock. The research results can provide support, in the form of scientific data, for land-use management decisions and carbon storage function protections in Zhengzhou and other cities around the world undergoing rapid urbanization. [ABSTRACT FROM AUTHOR]

Under the background of global urbanization, the continuous expansion and extensive utilization of urban and rural construction land has caused a large amount of arable land to be occupied, which seriously threatens national food security. This paper describes the spatio-temporal patterns of urban and rural construction land expansion and its occupation of arable land by using the urban and rural construction land expansion intensity, the urban and rural construction land expansion intensity difference index, and geo-detector model. It also explores the mechanisms through which the arable land was occupied. Results showed that construction land in both urban and rural areas expanded over the period 2009–2018 despite a large number of rural and urban migrants, and the major contributor to the rapid urbanization in China. This dual expansion could mainly be attributed to the tendency of these migrants to keep or even enlarge their rural construction land, which also resulted in a severer arable land loss than that caused by the expansion of urban construction land. Second, the rate of arable land occupied by urban and rural construction land in Henan province has been gradually slowing down, whereas the expansion of rural construction land is most dependent on arable land occupation. Third, according to the geo-detector model, the relationship between urbanization level and arable land occupied by urban and rural construction was the strongest, followed by the growth rate of fixed asset investment and the proportion of secondary and tertiary industries in GDP. [ABSTRACT FROM AUTHOR]

In recent years, the survival and development of traditional villages in China have been serious challenges. Rural tourism is regarded as an important way to solve rural problems, and the combination of rural culture and tourism has become a new power point for rural development. Therefore, it is necessary to explore the spatial distribution structure between traditional villages and rural tourism. In this paper, rural tourism was represented by the rural tourism characteristic village (RTCV), and Henan Province, China, was taken as a study area to analyze the distribution pattern and spatial correlation of rural tourism and traditional village (TV) and discuss the relationship between the spatial correlation and regional natural environment and socioeconomic factors. The results show that the coupling of the spatial correlation between RTCVs and TVs in Henan was clear. They could be divided into 5 regions based on geographical factors. In addition, the research summarized 4 typical spatial structures between TVs and RTCVs in Henan based on the regional symbiosis theory, and the spatial pattern formation mechanism of TVs and RTCVs was discussed based on three driving mechanisms. The spatial structure of the two can provide reference value for other developing countries and regions to achieve sustainable rural development. [ABSTRACT FROM AUTHOR]

Although vegetation index time series from optical images are widely used for crop mapping, it remains difficult to obtain sufficient time-series data because of satellite revisit time and weather in some areas. To address this situation, this paper considered Wen County, Henan Province, Central China as the research area and fused multi-source features such as backscatter coefficient, vegetation index, and time series based on Sentinel-1 and -2 data to identify crops. Through comparative experiments, this paper studied the feasibility of identifying crops with multi-temporal data and fused data. The results showed that the accuracy of multi-temporal Sentinel-2 data increased by 9.2% compared with single-temporal Sentinel-2 data, and the accuracy of multi-temporal fusion data improved by 17.1% and 2.9%, respectively, compared with multi-temporal Sentinel-1 and Sentinel-2 data. Multi-temporal data well-characterizes the phenological stages of crop growth, thereby improving the classification accuracy. The fusion of Sentinel-1 synthetic aperture radar data and Sentinel-2 optical data provide sufficient time-series data for crop identification. This research can provide a reference for crop recognition in precision agriculture. [ABSTRACT FROM AUTHOR]

Under the background of the new normal economy, ecotourism maintains a good momentum of development. Therefore, it can be foreseen that industrial integration is an inevitable trend in the development of contemporary industries, and the integration of cultural industries and tourism industries will bring good effects to regional economic development. In order to fully study the impact of ecotourism and its applied technologies on regional economy and culture, this paper proposes research on the application of virtual reality technology in the coordination and interaction of regional economy and culture in the sustainable development of ecotourism. The approach of this paper is to study VR technology in digital tourism and then to evaluate the sustainability of ecotourism and economic culture. The role of these methods is to study the interaction process between the tourism industry, regional economy, and cultural industry. It explores the law of action between the three so as to achieve the purpose of system optimization. Taking Henan Province, China, as an example, this paper discusses the application of virtual reality technology in ecotourism and studies the impact of ecotourism on economy and culture. The experimental results show that the average value of ecotourism-economic-cultural coordination degree in Henan Province is 0.399, and it is urgent to apply virtual reality technology in ecotourism. [ABSTRACT FROM AUTHOR]

This paper explored the transmission mechanism of the public sense of gain (PSG) and YB conservation and development, suggested to take the PSG as a better regulation and guidance for the sound development of the Yellow River Basin. Based on the data of CSS2019, this paper tried to exam the PSG at the opening stage of Chinese major strategy on YB Conservation and Development. An evaluation index system including 5 factor dimensions and 25 indices was constructed, and the normal distribution was used to fitting the survey data, after that, the dominance matrix method was applied to make decision based on PROMETHEE?. The empirical analysis results indicated that the PSG of the middle and upper reaches of the Yellow River was lower than the overall level of China, while that of Henan and Shandong in the lower Yellow River were both higher than its national average; and the public generally had a higher sense of gain on government public service and social civilization, however, the PSG on individual self-fulfillments of Henan and Shandong and that on economic situations of the middle and upper reaches of the Yellow River were both at a lower level. [ABSTRACT FROM AUTHOR]

Crop-type mapping is the foundation of grain security and digital agricultural management. Accuracy, efficiency and large-scale scene consistency are required to perform crop classification from remote sensing images. Many current remote-sensing crop extraction methods based on deep learning cannot account for adaptation effects in large-scale, complex scenes. Therefore, this study proposes a novel adaptive feature-fusion network for crop classification using single-temporal Sentinel-2 images. The selective patch module implemented in the network can adaptively integrate the features of different patch sizes to assess complex scenes better. TabNet was used simultaneously to extract spectral information from the center pixels of the patches. Multitask learning was used to supervise the extraction process to improve the weight of the spectral characteristics while mitigating the negative impact of a small sample size. In the network, superpixel optimization was applied to post-process the classification results to improve the crop edges. By conducting the crop classification of peanut, rice, and corn based on Sentinel-2 images in 2022 in Henan Province, China, the novel method proposed in this paper was more accurate, indicated by an F1 score of 96.53%, than other mainstream methods. This indicates our model's potential for application in crop classification in large scenes. [ABSTRACT FROM AUTHOR]

【Objective】The present paper aimed to scientifically quantify the development level of digital countryside, effectively promote the comprehensive and organic integration of modern information technology and rural areas, and help rural revitalization.【Method】Based on the latest research results and practical research, and the panel data of 18 prefectures and cities in Henan Province during 2014-2021, 20 indicators were selected from four dimensions: rural digital information basis, new business forms of rural digital economy, agricultural digital transformation, and digitalized rural life, to construct an evaluation index system for the development level of digital countryside. Methods such as entropy weight method, TOPSIS method, Kernel density estimation, Theil index and Moran’s I were comprehensively used to measure the development level of digital countryside in Henan province, and analyze its regional differences and spatial-temporal evolution.【Result】(i) From the perspective of development level, during the investigation period, the development level of digital countryside in Henan province showed an increasing trend year by year. Although the overall development level was not high, the sustainable development momentum was strong.(ii) From the perspective of regional differences, the overall difference of the development level of Henan digital countryside showed a trend of steady decline. Among them, the regional differences contributed the most to the overall differences, and the differences between Central Plains urban agglomeration and Huang-Huai region were the most obvious. The intra-regional differences showed a decreasing trend of Central Plains urban agglomeration, western Henan southwestern Henan, northern Henan and Huang-Huai region.(iii)From the perspective of spatial-temporal evolution, there was an obvious and stable positive correlation among the four economic zones. The Central Plains urban agglomeration was mostly high agglomeration, while the Huang-Huai area was basically low agglomeration. 【Conclusion】The development of digital countryside in Henan province should be combined with provincial conditions and regional characteristics to lay out comprehensively, promote overally, develop stably, bridge the gap, and improve rapidly. [ABSTRACT FROM AUTHOR]

Social media has become an essential channel for the public to create and obtain information during emergencies. As the theme of public concern for emergencies changes over time, there is a lack of research on its dynamic evolution from its latent stage. This paper selects the Henan rainstorm event as a case study and extracts the theme characteristics by combining the life cycle theory and Latent Dirichlet Allocation (LDA) model. It integrates the Term Frequency–Inverse Document Frequency (TF-IDF) and Pointwise Mutual Information (PMI) algorithms as the theme-coding data source to build a dynamic theme propagation model for emergencies. Our research results showed that the theme coding effectively verified the assumption of latent development trends. The dynamic theme model could reveal the theme characteristics of different time series stages of emergencies, analyze the law of the theme evolution of the network's public opinion, and provide practical and theoretical insights for the emergency management of urban cities. [ABSTRACT FROM AUTHOR]

A clear understanding of the spatial and temporal distribution characteristics of water resources is essential for the optimal allocation and sustainable utilization of water resources. In this paper, the spatial and temporal distribution characteristics of water resources in Henan Province were studied based on GIS, combining the Mann-Kendall (M-K) nonparametric test and rescaled range (R/S) analysis. In addition, SPSS software was used to analyze the influence of climate and land use type on water resources. The results indicated that (1) the hot spots of water resources were concentrated in the southwest, while the low values were concentrated in the northeast, and the distribution of water resources decreased from southwest to northeast. (2) In the past 21 years, spatiotemporal mutations in the water resource sequence occurred between 2010 and 2014. The Z-values of the M-K trend test were all less than 0, the H-values of groundwater resources (GWRs) were mostly greater than 0.5, and the h-values of surface water resources (SWRs) and total water resources (TWRs) were less than 0.5, showing an overall declining trend. However, this trend may change in the future. (3) From the correlation analysis, climate change had a greater impact on water resources than land use changes did. [ABSTRACT FROM AUTHOR]

The development of Chinese ceramics culminated during the Song dynasty. At this time, exquisite celadon works emerged, such as Ru Guan celadon and Southern Song dynasty official kiln celadon, which exhibited the glory of their era. Since the excavation of Zhanggongxiang kiln celadon in Ruzhou city, Henan province, China, it has been attracting widespread scholarly attention at home and abroad. Most scholars have suggested that Zhanggongxiang is the official kiln of the Northern Song dynasty. In this paper, taking the celadon unearthed from the Zhanggongxiang kiln as a sample, the combination of laser Raman spectrum and thermal expansion methods is used to study the inheritance relationship between Zhanggongxiang celadon and Ru Guan celadon in the firing process. Meanwhile, the rationality of using Raman Ip value to evaluate the firing temperature of ceramics is reviewed. The main conclusions are as follows. First, the firing temperature of Zhanggongxiang celadon with various glaze colours is quite different, whereas the firing temperature of the same glaze colour is similar, thereby inheriting the firing technology of Ru Guan porcelain. Second, the Ip value of glaze cannot evaluate the firing temperature of porcelain with similar firing temperature. The Ip value corresponds to a range, within which it does not fully conform to the rule that the larger the Ip value, the higher the firing temperature. The Ip value is also associated with the formulation in addition to firing temperature. It is applicable to evaluating porcelains with a similar formulation but a large temperature difference. [ABSTRACT FROM AUTHOR]

UAV (unmanned aerial vehicle) remote sensing provides the feasibility of high-throughput phenotype nondestructive acquisition at the field scale. However, accurate remote sensing of crop physicochemical parameters from UAV optical measurements still needs to be further studied. For this purpose, we put forward a crop phenotype inversion framework based on the optimal estimation (OE) theory in this paper, originating from UAV low-altitude hyperspectral/multispectral data. The newly developed unified linearized vector radiative transfer model (UNL-VRTM), combined with the classical PROSAIL model, is used as the forward model, and the forward model was verified by the wheat canopy reflectance data, collected using the FieldSpec Handheld in Qi County, Henan Province. To test the self-consistency of the OE-based framework, we conducted forward simulations for the UAV multispectral sensors (DJI P4 Multispectral) with different observation geometries and aerosol loadings, and a total of 801 sets of validation data were obtained. In addition, parameter sensitivity analysis and information content analysis were performed to determine the contribution of crop parameters to the UAV measurements. Results showed that: (1) the forward model has a strong coupling between vegetation canopy and atmosphere environment, and the modeling process is reasonable. (2) The OE-based inversion framework can make full use of the available radiometric spectral information and had good convergence and self-consistency. (3) The UAV multispectral observations can support the synchronous retrieval of LAI (leaf area index) and Cab (chlorophyll a and b content) based on the proposed algorithm. The proposed inversion framework is expected to be a new way for phenotypic parameter extraction of crops in field environments and had some potential and feasibility for UAV remote sensing. [ABSTRACT FROM AUTHOR]

Flood hazards resulting from short-term severe precipitation have caused serious social and economic losses and have posed extraordinary threats to the safety of lives and property. Vulnerability, which reflects the degree of the adverse impact of flooding on a city, the sensitivity of the environment, and the extent to which rescues are possible during flooding, is one of the significant factors of the disaster risk assessment. Because of this, this paper proposes an Environmental Vulnerability Analysis Model (EVAM), based on comprehensively evaluating multi-source remote sensing data. The EVAM includes a two-stage, short-term flood vulnerability assessment. In the first stage, the flood's areal extension and land-use classification are extracted, based on the U-NET++ network, using multi-source satellite remote sensing images. The results from the first stage are used in the second stage of vulnerability assessment. In the second stage, combining multi-source data with associated feature extraction results establishes the Exposure–Sensitivity–Adaptive capacity framework. The short-term flood vulnerability index is leveraged through the analytic hierarchy process (AHP) and the entropy method is calculated for an environmental vulnerability evaluation. This novel proposed framework for short-term flood vulnerability evaluation is demonstrated for the Henan Province. The experimental results show that the proportion of vulnerable cities in the Henan Province ranging from high to low is 22.22%, 22.22%, 38.89%, and 16.67%, respectively. The relevant conclusions can provide a scientific basis for regional flood control and risk management as well as corresponding data support for post-disaster reconstruction in disaster regions. [ABSTRACT FROM AUTHOR]

BACKGROUND: Perlite is a vitreous rock formed by rapid cooling of volcanic eruptive acidic lava. It is a very important non-metallic mineral, because of its brittleness, light weight, rapid expansion on heating, and other excellent characteristics, and is widely used in construction, water treatment, agriculture and other fields. However, according to the International Database for Certified Reference Materials ( COMAR), there is no reference material for perlite composition analysis at home and abroad. So, in order to meet the research needs of perlite, it is necessary to develop one. OBJECTIVES: To develop a reference material for composition analysis of perlite. The reference material can basically cover the chemical composition needed by the market. METHODS: Perlite samples were collected from Shangcheng County, Henan Province. The collected samples were dried and picked out, the bulk ore was crushed and ground in a ball mill for 40h, then the samples were coarse crushed and discharged, and the debris was removed by 1mm sieve. The samples were dried at 105℃ for 24h, dehydrated and inactivated. After drying, the samples were crushed in a grinder containing high -alumina ceramic balls, and the grinding time was determined by the time required to meet the particle size requirements of the first class standard substance. The processed samples were stored temporarily in polyethylene plastic vats under constant temperature and clean conditions, then sub-packed at 70g per bottle for test. Random samples were taken for homogeneity and stability tests. Through nine collaborative laboratories, more targeted valuation methods such as the gravimetric method, volumetric method, inductively coupled plasma - mass spectrometry, and inductively coupled plasma-optical emission spectrometry were used to ensure the accuracy of the perlite valued components. RESULTS: Fifteen items of 60 components were tested for uniformity and stability, including Ag, As, B, Ba, Be, Bi, Cd, Co, Cr, Cs, Cu, Ga, Hf, Hg, In, Li, Mo, Nb, Ni, Pb, Rb, Sb, Sc, Sn, Sr, Ta, Th, U, V, W, Zn, Zr, SiO2, Al2O3, TFe2O3, FeO, MgO, CaO, Na2O, K2O, MnO, TiO2, P2O5, LOI, TC, and rare earth elements. The RSD of most of the components was less than 3%, and the F value of the variance test was less than the critical value [F0. 05 (29,60) = 1. 65], indicating that the homogeneity of the reference material was good. During the stability inspection period, there was no significant difference in the content of the 60 components, indicating that the reference material was stable. The data were processed in accordance with General and Statistical Principles for Characterization of Reference Materials and outlier tests were performed using the Grubbs and Dixon methods. According to statistics, there were 2500 original data of perlite reference material, and 68 outliers were eliminated, with an elimination rate of 2. 7%. The standard value and uncertainty of the certified reference material for perlite composition analysis were determined by statistical processing of the constant value test data. The normal distribution of the mean data set was tested by the method of Shapiro-wilk, and the test results were all normal distribution. The final values were 63 components, covering major, trace, and all rare earth elements. The contents of three major components MgO, CaO and TFe2O3 were all less than 1%, which formed a gradient with the existing silicate reference material content. CONCLUSIONS: The certified reference material for perlite composition analysis developed in this paper has met the requirements of Technical Norm of Primary Reference Material ( JJF1006—94 ) by processing, crushing, homogeneity and stability test of the candidate. The test for uniformity and stability adopts the same detection technology as the fixed value method, and the selected fixed value technology is suitable and accurate, which ensures the accuracy of the fixed value data. The development of perlite composition analysis standard material has enriched the series of China geological mineral composition analysis standard material, and its chemical composition is numerous, it provides important technical support for instrument calibration, analysis method verification, quality control and quantity traceability of modern analytical technology. [ABSTRACT FROM AUTHOR]