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Spatiotemporal variations of industrial carbon emissions (IE) must be scientifically understood, which will be helpful to formulate reasonable emission reduction strategies. Given that spatial distribution of IE is irrelevant to space agents commonly used (such as population and nighttime light), estimation and spatialization methods for total carbon dioxide (CO2) emissions are not entirely suitable for IE. Therefore, this paper used greenhouse gases observing satellite level 4A product to estimate IE at the city level and used industrial land density to obtain the distribution of IE within the administrative districts. Sectoral emission inventories of 182 cities and a mosaic Asian anthropogenic emission inventory named MIX were used to verify the results. Then, spatiotemporal variation characteristics of China's IE were analyzed from multiple levels. Results showed that (1) the mean relative error of estimation results was 56.11%, among which 62 cities had relative error of less than 30%. Gridded IE in this paper had high consistency with MIX. (2) Cities with high IE experienced rapid growth from 2009 to 2012, followed by slower growth from 2012 to 2017. (3) Centroid of significant cold and hot spots moved to the southeast and northwest, respectively. Most cities with high annual IE growth had relatively low emission efficiency, mainly located in Inner Mongolia and Xinjiang. Aggregation of medium and high IE grids may represent high emission efficiency. Significant differences still exist between cities in IE, and sustainable development strategies should be formulated according to local conditions. Regions with high annual growth or low emission efficiency are the key to achieving IE reduction targets in future.

MicroRNAs (miRNAs) are endogenous noncoding small molecule RNAs that regulate cell proliferation, differentiation, fat metabolism, and hormone secretion. Studies have shown that miRNAs regulate the processes related to osteoporosis, including the differentiation of osteoblasts, osteoclasts, and chondrocytes, and are one of the important regulatory factors of some bone metabolic diseases. In our previous study, it has been revealed that natural compound Polygonatum sibiricum polysaccharide (PSP) can promote osteoblast formation and block osteoclastogenesis through Wnt/β-catenin signaling pathway. This study was designed to investigate whether PSP can inhibit expression of osteoclast-related genes by Hippo signaling pathway, which was prevented by effectively blocking the expression of miR-1224. This study showed that there were 27 differentially expressed miRNAs when PSP inhibits osteoclastogenesis, the most notable of which was miR-1224. Furthermore, the study showed that PSP increased the level of Limd1, which was the target gene of miR-1224. In conclusion, these findings demonstrate that PSP suppressed osteoclastogenesis in vitro through the Hippo signaling pathway based on miR-1224. This study may aid in the development of a therapeutic approach utilizing PSP for the enhancement of bone health and prevention of osteoporosis.

Background/Aims: miR-136-5p participates in recovery after spinal cord injury (SCI) via an unknown mechanism. We investigated the mechanism underlying the involvement of miR-136-5p in the inflammatory response in a rat model of SCI. Methods: Sprague-Dawley rat astrocytes were cultured in vitro to construct a reporter plasmid. Luciferase assays were used to detect the ability of miR-136-5p to target the IKKβ and A20 genes. Next, recombinant lentiviral vectors were constructed, which either overexpressed miR-136-5p or inhibited its expression. The influence of miR-136-5p overexpression and miR-136-5p silencing on inflammation was observed in vivo in an SCI rat model. The expression of IL-1β, IL-6, TNF-α, IFN-α, and related proteins (A20, IKKβ, and NF-κB) was detected. Results: In vitro studies showed that luciferase activity was significantly activated in the presence of the 3’ untranslated region (UTR) region of the IKKβ gene after stimulation of cells with miR-136-5p. However, luciferase activity was significantly inhibited in the presence of the 3’UTR region of the A20 gene. Thus, miR-136-5p may act directly on the 3’UTR regions of the IKKβ and A20 genes to regulate their expression. miR-136-5p overexpression promoted the production of related cytokines and NF-κB in SCI rats and inhibited the expression of A20 protein. Conclusion: Overexpression of miR-136-5p promotes the generation of IL-1β, IL-6, TNF-α, IFN-α, IKKβ, and NF-κB in SCI rats but inhibits the expression of A20. Under these conditions, inflammatory cell infiltration into the rat spinal cord increases and injury is significantly aggravated. Silencing of miR-136-5p significantly reduces the protein expression results described after miR-136-5p overexpression and ameliorates the inflammatory cell infiltration and damage to the spinal cord. Therefore, miR-136-5p might be a new target for the treatment of SCI.

Farmland soil environmental quality is important for farmland management. To precisely classify the environmental quality grades of farmland soil, additional samples may be required for multistage sampling or supplementary investigations. Compared with the sampling optimization methods used for mapping or estimating global means, environmental quality grade classifications are primarily focused on estimating the relationships between the values of unsampled locations and the thresholds that classify the environment quality grades. Such classifications must use a sampling layout optimization method to distribute additional sampling units into areas with a high risk of misclassification. To resolve such problems, this paper provides an additional sampling layout optimization method that initially develops a classification error index by building a multi-Gaussian model with the predicted values and error variances of unsampled locations and then calculates the probability of a threshold value occurring in the standardized Gaussian distribution. The average error indexes of all locations in the study area are then set as the objectivity function of the additional sampling layout optimization, and the spatial simulated annealing is adopted to obtain the optimized sampling layout by minimizing the objectivity function. The performance of the error index sampling layout optimization method was demonstrated in a case study using chromium concentration data for Hunan Province, China. The results showed that the additional samples generated by the proposed method produce lower and more stable classification error rates than the minimization of the mean of the shortest distances and spatially random sample methods. The proposed method can be used to improve the efficiency of additional sampling for environmental quality grade classifications of farmland soil.

Understanding the spatiotemporal trends of temperature in the context of global warming is significant for public health. Although many studies have examined changes in temperature and the impacts on human health over the past few decades in many regions, they have often been carried out in data-rich regions and have rarely considered acclimatization explicitly. The most frequent temperature (MFT) indicator provides us with the ability to solve this problem. MFT is defined as the longest period of temperature throughout the year to which a human is exposed and therefore acclimates. In this study, we propose a new method to estimate the number of heat exposure days from the perspective of temperature distribution and MFT, based on the daily mean temperature readings of 2142 weather stations in eight major climate zones in China over the past 20 years. This method can be used to calculate the number of heat exposure days in terms of heat-related mortality risk without the need for mortality data. We estimated the distribution and changes of annual mean temperature (AMT), minimum mortality temperature (MMT), and the number of heat exposure days in different climate zones in China. The AMT, MMT, and number of heat exposure days vary considerably across China. They all tend to decrease gradually from low to high latitudes. Heat exposure days are closely related to the risk of heat-related mortality. In addition, we utilized multiple linear regression (MLR) to analyze the association between the risk of heat-related mortality and the city and its climatic characteristics. Results showed that the number of heat exposure days, GDP per capita, urban population ratio, proportion of elderly population, and climate zone were found to modify the estimate on heat effect, with an R2 of 0.71. These findings will be helpful for the creation of public policies protecting against high-temperature-induced mortalities.

With the rapid increase in the costs of rural labour and the adjustment of planting structures, the phenomenon of farmland abandonment has appeared in China. It is of great significance to promptly and accurately grasp the information on dynamic temporal and spatial changes in abandoned farmland to ensure national food security and the sustainable use of cultivated land. Luquan District in Hebei, China was selected as the research area based on multispectral images from Sentinel-2A, Landsat-7, and Landsat-8 combined with methods of random forest (RF) classification and vegetation index change detection. Rules for the identification of abandoned farmland were also developed, and remote sensing monitoring of the abandonment status of the cultivated land was also carried out in the study area. We also obtained the spatial distribution of abandoned and reclaimed farmland and analysed the frequency of farmland abandonment. The results show that the overall accuracy of the land-use time-series map ranged from 90.20% to 96.92% for the study period of 2010–2020. The average rate of farmland abandonment in the study area was 10.62%, with the lowest rate (5.83%) in 2020 and the highest (14.09%) in 2012. From 2011 to 2020, the maximum farmland abandonment area was 3906.02 hm2, and the minimum area was 1618.74 hm2. The farmland abandonment area showed a trend of first increasing and then decreasing. From 2012 to 2020, the maximum area of reclaimed farmland was 291.49 hm2, and the highest rate of reclamation was 14.26%. The overall reclamation rate was low. The abandonment frequency of most of the abandoned farmland was 1–3 years, covering an area of 8193.73 hm2, which comprised 79% of the total area of abandoned farmland. The frequency of abandonment was inversely proportional to the area of abandoned farmland. Farmland abandonment mainly occurred in hilly areas. We expect that our results can provide case studies for long time series in farmland abandonment research and can provide a reference for studying the driving factors, risk assessment, and policymaking with respect to abandoned farmland.

Soil contaminant grades classified by thresholds of concentrations are important for land use and management. Mapping of the soil contaminant grades only focuses on the precise prediction of the relationship between the contaminant concentration of each spatial units and a predefined threshold. Thus, unlike sampling for other purposes, additional sampling should add more sites in areas with a high possibility of misclassification and fewer or no sites in areas with a low possibility of misclassification. To guide additional sampling for mapping of the soil contaminant grades, an error index based on Indicator Kriging (IK) is proposed in this paper. By linear transformation of the predicted value of IK and summing the standard variance of the prediction error, the error index contains both the closeness of predicted value to the threshold and the uncertainty of the prediction, and can reflect the possibility of misclassification of the soil contaminant grades. Also, due to the adoption of IK, it can avoid the smoothing effect, remove or lower the unstationary variation of original data by indicator transform, and do not required normal distribution to model the error variance. Based on the error index, an optimization method for additional sampling to map soil contaminant grades is then put forward by defining an objective function and employing the Spatial Simulated Annealing optimization method. The chromium concentration data of the study area in central China were used as a case study. According to a comparison of the proposed additional sampling optimization method with spatially even sampling method and spatially random sampling method, the case study demonstrated that the proposed optimization method based on the error index is superior to the other methods in improving the prediction precision of soil contaminant grades and that its performance is stable. The results suggest that the error index proposed in this paper can be used to generate a design for additional sampling to improve the mapping precision of soil contaminant grades.

MicroRNAs (miRNAs) are endogenous noncoding small molecule RNAs that regulate cell proliferation, differentiation, fat metabolism, and hormone secretion. Studies have shown that miRNAs regulate the processes related to osteoporosis, including the differentiation of osteoblasts, osteoclasts, and chondrocytes, and are one of the important regulatory factors of some bone metabolic diseases. In our previous study, it has been revealed that natural compound

Vegetation is essential for the provision of ecosystem services. To ensure that ecosystem services are provided, urban planning must consider vegetation cover in both urban core areas and in peripheral areas. This study explored changes in vegetation cover in both urban core and peripheral areas (buffers of 5, 10 and 15 km from the urban core areas) and the relationships between these changes and urban development. To compare the differences in vegetation cover between the urban core and peripheral areas, we developed two vegetation indices, the vegetation influence strength index (VISI) and the vegetation restoration index (VRI), using normalized difference vegetation index datasets and nighttime stable light data from 50 cities in southern China. Using these two indices, we clustered the cities into four types based on their vegetation cover characteristics. The city types varied among the different regions of the study area and cities of the same type tended to occur together geographically. In addition, the two indices showed temporal changes during the study period: A downtrend from 1992 to 2000, an uptrend from 2000 to 2005, and stability from 2005 to 2013. Furthermore, in all cities, the range of the VISI was larger in the peripheral areas than in the urban core areas. However, the range of the VRI was smaller in the peripheral areas than in the urban core areas. As the distance to the urban core areas increased, the fluctuation range of both the VISI and VRI decreased, suggesting that there was less vegetation disturbance farther from the urban core areas. We also showed that changes in vegetation cover were related to differences in urbanization rates, gross domestic products, population densities, and stages of urban development among the cities. These results provide scientific support for urban planning and sustainable development in rapid urbanization areas.

Spatial sampling survey is the most basic work, and the even distribution of sampling sites is the important optimization target of sampling layout design and the key factor of the later data detection and evaluation of the samples. This paper presents an evenness detection method for sample distribution of agricultural heavy metal in the fragmented regions for Beijing, China. The even variation values for 171 samples of the agricultural heavy metal were calculated based on Thiessen polygons, and then the even variation index and even variation curve of samples were constructed to detect the evenness of sampling sites. The results showed that the even variation index of sample distribution of agricultural heavy metal in the fragmented regions for Beijing was 0.63, and there were four abnormal samples according to the comparisons of the even variation curve of sampling sites and the simulated standard curve based on spatial simulated annealing (SSA) and minimization of the mean of shortest distances (MMSD) criterion. Four abnormal samples will be adopted for detailed analysis to support further data refinement and mining of sampling sites. The method developed in this study can accurately and effectively detect the sampling evenness of agricultural heavy metal in the fragmented regions. This study provides a robust operational tool and technical method for the regional data quality evaluation and has broad potential in the agricultural soil pollution and prevention, the detailed investigation of soil pollution, and the monitoring of agricultural product origins. The method is effective to improve the monitoring and supervision levels of the agricultural and ecological environment.

The conventional approach to estimate the global mean under preferential spatial sampling gets a larger deviation and further influences the precision of the subsequent model calculation and analysis. Zoning or declustering methods can effectively improve the estimation precision of preferential sampling. In this paper, we propose a novel method, which uses self-organizing dual-zoning method to estimate the global mean, in which the Self-Organizing Feature Map (SOFM) and the Voronoi diagram are utilized to realize classification and zoning. By comparing with arithmetic mean method, polygonal declustering method, and cell declustering method, we got that arithmetic mean method could not satisfy the special properties of the preferential sampling, and self-organizing dual-zoning method gets more accurate zoning results and more stable global means with different sample sizes and Feature Deviation Index (FDI).

With the development of the economy and industry, the landuse behaviors that violate law and regulations frequently happen in China. In order to guarantee that the landuse behavior are rational and obeying the landuse planning, efficient supervision should be performed to regulate construction landuse. The construction landuse data are the base of supervision by the government at a higher level and other third parties, so access to the supervision data should be provided thought the web for query and analysis according to users' authority. The spatio-temporal data of the construction landuse supervision is comprised by multi-stages and contains different kinds of data with complex relationships. How to share them on the web to provide easy and efficient data accessing needs to be addressed. Aiming at provide uniform, efficient and easy to use access to construction landuse supervision data, this paper put forward to construct data operating service, tracing service, and landuse index service conforming the REST style, to keep the hierarchical and procedural structure of supervision data and overcome the shortage of SOAP based Web Service and OWS of OGC. The resource, service URI and resource representation of REST service for construction landuse supervision data management was designed and realized. In the realization of the REST Services for construction landuse supervision data management, Restlet, an open-source software which provide a good framework for implementing REST service, was adopted.

Scientific and accurate cultivated quality grade results are an important guarantee for applications. However, the phenomenon of abnormal cultivated land quality is always occurred due to the error of investigation or computation, so exploring effective method to inspect abnormal data of the grade results is an important problem to be solved. Cultivated land quality grade results of Wuhan Hannan district are selected as the research data, and several typical relative indexes of cultivated land quality are researched as spatial variables, including natural index, use index and economic index, etc. Global Moran's I and Local Moran's I index are used to analyze spatial structural characteristic and clustering rules of cultivated land quality, and then put forward cultivated land quality outlier detect standard based on the research of the front. The results showed that: On the whole, natural index, use index and economic index all showed strong positive spatial correlation and the aggregation degree is high; On the local, the cultivated land quality form “high — high” and “low — low” spatial cluster, accompanied with “high — low”, “low — high” space isolation area, which formed a horizontal Mosaic distribution pattern of “patches” and “gaps”. Further study to the “high-low”, “low — high” space isolation zone with significance analysis can effectively detect the cultivated land quality abnormal data. This method improves the traditional statistics due to ignoring the spatial correlation in space anomaly inspection and provides a new train of thought for cultivated land quality data outliers detection.

With the rapid development of agriculture and industry, the soil heavy metal pollution is becoming more prominent. It is necessary to know the content and spatial distribution of heavy metal in soil. The soil heavy metal content is not only affected by natural factors such as parent material, climate, biology, topography et al, but also the man-made pollution factors such as pesticide and fertilizer use, sewage irrigation, solid waste accumulation et al. Compared to natural factors, the man-made pollution factors are most often spatially heterogeneous. The Sandwich model proposed by Jingfeng Wang can be used to mapping the distribution of regional variable with spatially stratified heterogeneity. The Sandwich model has three key layers: sampling layer, zooning layer and reporting layer, the information of sampling data is firstly transferred into zooning layer, and then transferred from zoning layer to reporting layer to get estimated mean and related error for each report unit. In this paper, the Sandwich model was used to mapping the spatial distribution of heavy metal (As) content in the soil of South part of Daxing District, Beijing. The sampling data was used as the sampling layer, then the parent material data, and sample clusters were integrated to divide the study area into zones, and the administrative villages were the units of reporting layer. The estimation results show that the average content of As in these villages is about 6mg kg−1, most middle part of whole region is from 4.5 mg kg−1 to 7 mg kg−1, and the content of boundary part is less, and individual area has extremely higher content. By comparing with the results obtained by Ordinary Kriging interpolation, Stratified estimation. The mapping result of soil heavy metal content results show that Sandwich Model has better performance than the other two estimation methods.

At present, irrigation decision-making systems applied to the field of agriculture were mostly aimed at a given area and specific crops. It was difficult to be applied in different areas and different crops. In this paper, a precision irrigation decision-making system has done something to solve this problem. The paper, on the one hand, has synthesized multi-areas and multi-crops in one decision; on the other hand, the key was that it used an advanced design idea, which quickly builds a system by using SOA architecture and fully meets different needs of users based on the maximum reuse of services. The paper arranges services in BPM. First of all, user programmed areas, crop types and the water supply. Secondly, the system selects optimum services from the BPM based on different inputs, and then quickly builds a suitable model. Moreover, it gave precise guidance for crop irrigation processes. The precision irrigation decision support system provides an on-demand decision-making model for agricultural production. Applied results show that, through the test on Xiao Tangshan winter wheat, Da Xing vegetables and rice in central China, the system can quickly build a decision-making model to meet the needs of irrigation for different users. In addition, it shows a good reflection and wide use.

Giving an appropriate weight to each sampling point is essential to global mean estimation. The objective of this paper was to develop a global mean estimation method with preferential samples. The procedure for this estimation method was to first zone the study area based on self-organizing dual-zoning method and then to estimate the mean according to stratified sampling method. In this method, spreading of points in both feature and geographical space is considered. The method is tested in a case study on the metal Mn concentrations in Jilin provinces of China. Six sample patterns are selected to estimate the global mean and compared with the global mean calculated by direct arithmetic mean method, polygon method, and cell method. The results show that the proposed method produces more accurate and stable mean estimates under different feature deviation index (FDI) values and sample sizes. The relative errors of the global mean calculated by the proposed method are from 0.14 to 1.47 % and they are the largest (4.83–8.84 %) by direct arithmetic mean method. At the same time, the mean results calculated by the other three methods are sensitive to the FDI values and sample sizes.

The basic farmland within the protection areas was required to be of high-quality and connective in the general plans for land use. A new method was developed to delineate the boundaries of high-quality, concentrated and connective cultivated land. Based on mathematical morphology principles and GIS methods, the high quality of cultivated land blocks could be identified through dilation and erosion operations according to this rule that which inside distance was less than threshold d1 and the number of blocks was larger than 3. This method was validated with the farmland classification data of Miyun County and Pinggu District in Beijing City, and 91% of high-quality, concentrated and the connective cultivated land could be identified by this method, so it would provide the reference method for delineating the basic farmland areas scientifically and reasonably in the general plans for land use.

Statistical analysis of land-use change plays an important role in sustainable land management and has received increasing attention from scholars and administrative departments. However, the statistical process involving spatial overlay analysis remains difficult and needs improvement to deal with mass land-use data. In this paper, we introduce a spatio-temporal flow network model to reveal the hidden relational information among spatio-temporal entities. Based on graph theory, the constant condition of saturated multi-commodity flow is derived. A new method based on a network partition technique of spatio-temporal flow network are proposed to optimize the transition statistical process. The effectiveness and efficiency of the proposed method is verified through experiments using land-use data in Hunan from 2009 to 2014. In the comparison among three different land-use change statistical methods, the proposed method exhibits remarkable superiority in efficiency.