The spatial organization of the Chinese petrochemical industry was optimized according to the status of development of the industry employing linear programming and ArcGIS spatial analysis tools. We first identified the indexes of the spatial organization of the petrochemical industry and established a comprehensive evaluation index system that includes four major categories and 11 indicators. The weight of each index was then determined by the analytical hierarchy process. Afterward, taking the 337 Chinese prefecture-level administrations as basic units and scientifically evaluating the potential comprehensive layout coefficients of the cities, 151 prefecture-level administrative units were selected as the basis for the choice of optimization sites with a linear programming model. Secondly, using the 151 prefecture-level administrative units and the maximum-coverage model, the optimal number and spatial distribution of refineries were identified for service radii of 100, 200 and 300 km. Thirdly, considering the actual distribution of China’s refineries, general rules for the number of refinery layout points and objective values were summarized, and 52 refinery layout points were selected for China. Finally, with ArcGIS spatial analysis tools, the spatial effect of the 52 optimal refinery layout points was simulated for the service scope and socioeconomic factors respectively, and the GDP and population data for each refinery layout point were then extracted within the service scope. On this basis and with estimation of the intensity of crude-oil consumption, final results were obtained for the optimal spatial organization of the Chinese refining capacity and ethylene production capacity.

From 1981 to 2010,the effects of climate change on evapotranspiration of the alpine ecosystem and the regional difference of effects in the Tibetan Plateau(TP)were studied based on the Lund-Potsdam-Jena dynamic vegetation model and data from 80 meteorological stations.Changes in actual evapotranspiration(AET)and water balance in TP were analyzed.Over the last 30 years,climate change in TP was characterized by sig- nificantly increased temperature,slightly increased precipitation,and decreased potential evapotranspiration(PET),which was significant before 2000.AET exhibited increasing trends in most parts of TP.The difference between precipitation and AET decreased in the south- eastern plateau and increased in the northwestern plateau.A decrease in atmospheric water demand will lead to a decreased trend in AET.However,AET in most regions increased be- cause of increased precipitation.Increased precipitation was observed in 86%of the areas with increased AET,whereas decreased precipitation was observed in 73%of the areas with decreased AET.

Based on the daily precipitation data of 27 meteorological stations from 1960 to 2009 in the Huaihe River Basin, spatio-temporal trend and statistical distribution of extreme precipitation events in this area are analyzed. Annual maximum series (AM) and peak over threshold series (POT) are selected to simulate the probability distribution of extreme precipitation. The results show that positive trend of annual maximum precipitation is detected at most of used stations, only a small number of stations are found to depict a negative trend during the past five decades, and none of the positive or negative trend is significant. The maximum precipitation event almost occurred in the flooding period during the 1960s and 1970s. By the L-moments method, the parameters of three extreme distributions, i.e., Generalized extreme value distribution (GEV), Generalized Pareto distribution (GP) and Gamma distribution are estimated. From the results of goodness of fit test and Kolmogorov-Smirnov (K-S) test, AM series can be better fitted by GEV model and POT series can be better fitted by GP model. By the comparison of the precipitation amounts under different return levels, it can be found that the values obtained from POT series are a little larger than the values from AM series, and they can better simulate the observed values in the Huaihe River Basin.

Based on China homogenized land surface air temperature and the National Centers for Environmental Prediction/Department of Energy (NCEP/DOE) Atmospheric Model Intercomparison Project (AMIP)-Ⅱ Reanalysis data (R-2), the main contributors to surface air temperature increase in Southeast China were investigated by comparing trends of urban and rural temperature series, as well as observed and R-2 data, covering two periods of 1954-2005 and 1979-2005. Results from urban-rural comparison indicate that urban heat island (UHI) effects on regional annual and autumn minimum temperature increases account for 10.5% and 12.0% since 1954, but with smaller warming attribution of 6.2% and 10.6% since 1979. The results by comparing observations with R-2 surface temperature data suggest that land use change accounts for 32.9% and 28.8% in regional annual and autumn minimum temperature increases since 1979. Accordingly, the influence of land use change on regional temperature increase in Southeast China is much more noticeable during the last 30 years. However, it indicates that UHI effect, overwhelmed by the warming change of background climate, does not play a significant role in regional warming over Southeast China during the last 50 years.

Sensitivity analysis of hydrological model is the key for model uncertainty quantification. However, how to effectively validate model and identify the dominant parameters for distributed hydrological models is a bottle-neck to achieve parameters optimization. For this reason, a new approach was proposed in this paper, in which the support vector machine was used to construct the response surface at first. Then it integrates the SVM-based response surface with the Sobol’ method, i.e. the RSMSobol’ method, to quantify the parameter sensitivities. In this work, the distributed time-variant gain model (DTVGM) was applied to the Huaihe River Basin, which was used as a case to verify its validity and feasibility. We selected three objective functions (i.e. water balance coefficient WB, Nash-Sutcliffe efficiency coefficient NS, and correlation coefficient RC) to assess the model performance as the output responses for sensitivity analysis. The results show that the parameters g₁ and g₂ are most important for all the objective functions, and they are almost the same to that of the classical approach. Furthermore, the RSMSobol method can not only achieve the quantification of the sensitivity, and also reduce the computational cost, with good accuracy compared to the classical approach. And this approach will be effective and reliable in the global sensitivity analysis for a complex modelling system.

Using the daily temperature data of 95 meteorological stations from Sichuan- Chongqing Region and its surrounding areas, this paper adopted these methods (e.g., linear regression, trend coefficient, geographical statistics, gray relational analysis and spatial analysis functions of GIS) to analyze the relations of temperature variability with topography, latitude and longitude. Moreover, the rank of gray correlation between temperature variability and elevation, longitude, latitude, topographic position and surface roughness also was measured. These results indicated: (1) The elevation affected temperature variability most obviously, followed by latitude, and longitude. The slope of the linear regression between temperature change rate and elevation, latitude and longitude was 0.4142, 0.0293 and -0.3270, respectively. (2) The rank of gray correlation between temperature change rate and geographic factors was elevation > latitude > surface roughness > topographic position > longitude. The gray correlation degree between temperature change rate and elevation was 0.865, followed by latitude with 0.796, and longitude with 0.671. (3) The rate of temperature change enhanced with the increase of elevation. Especially, the warming trend was significant in the plateau and mountain areas of western Sichuan, and mountain and valley areas of southwestern Sichuan (with the warming rate of 0.74℃/10a during the 1990s). However, there was a weak warming trend in Sichuan Basin and its surrounding low mountain and hilly areas. (4) The effects of latitude on temperature change rate presented the specific regulation, which the warming rate of low-latitude areas was more significant than that of high-latitude areas. However, they were consistent with the regulation that the increasing of low temperature controlled most of the warming trend, due to the effects of terrain and elevation on annual mean temperature. (5) Basically, temperature variability along longitude direction resulted from the regular change of elevation along longitude. It was suggested that, in Sichuan-Chongqing Region, special features of temperature variability largely depended on the terrain complexity (e.g., undulations, mutations and roughness). The elevation level controlled only high or low annual mean temperature and the range of temperature change rate in the macro sense.

By decomposing and reconstructing the runoff information from 1965 to 2007 of the hydrologic stations of Tuotuo River and Zhimenda in the source region of the Yangtze River, and Jimai and Tangnaihai in the source region of the Yellow River with db3 wavelet, runoff of different hydrologic stations tends to be declining in the seasons of spring flood, summer flood and dry ones except for that in Tuotuo River. The declining flood/dry seasons series was summer > spring > dry; while runoff of Tuotuo River was always increasing in different stages from 1965 to 2007 with a higher increase rate in summer flood seasons than that in spring ones. Complex Morlet wavelet was selected to detect runoff periodicity of the four hydrologic stations mentioned above. Over all seasons the periodicity was 11-12 years in the source region of the Yellow River. For the source region of the Yangtze River the periodicity was 4-6 years in the spring flood seasons and 13-14 years in the summer flood seasons. The differences of variations of flow periodicity between the upper catchment areas of the Yellow River and the Yangtze River and between seasons were considered in relation to glacial melt and annual snowfall and rainfall as providers of water for runoff.

To understand historical human-induced land cover change and its climatic effects, it is necessary to create historical land use datasets with explicit spatial information. Using the taxes-cropland area and number of families compiled from historical documents, we estimated the real cropland area and populations within each Lu (a province-level political region in the Northern Song Dynasty) in the mid-Northern Song Dynasty (AD1004-1085). The estimations were accomplished through analyzing the contemporary policies of tax, population and agricultural development. Then, we converted the political region-based cropland area to geographically explicit grid cell-based fractional cropland at the cell size of 60 km by 60 km. The conversion was based on calculating cultivation suitability of each grid cell using the topographic slope, altitude and population density as the independent variables. As a result, the total area of cropland within the Northern Song territory in the 1070s was estimated to be about 720 million mu (Chinese area unit, 1 mu = 666.7 m²), of which 40.1% and 59.9% occurred in the north and south respectively. The population was estimated to be about 87.2 million, of which 38.7% and 61.3% were in the north and south respectively, and per capita cropland area was about 8.2 mu. The national mean reclamation ratio (i.e. ratio of cropland area to total land area; RRA hereafter for short) was bout 16.6%. The plain areas, such as the North China Plain, the middle and lower reaches of the Yangtze River, Guanzhong Plain, plains surrounding the Dongting Lake and Poyang Lake and Sichuan Basin, had a higher RRA, being mostly over 40%; while the hilly and mountainous areas, such as south of Nanling Mountains, the southwest regions (excluding the Chengdu Plain), Loess Plateau and southeast coastal regions, had a lower RRA, being less than 20%. Moreover, RRA varied with topographic slope and altitude. In the areas of low altitude (≤250 m), middle altitude (250-100 m) and high altitude (1000-3500 m), there were 443 million, 215 million and 64 million mu of cropland respectively and their regional mean RRAs were 27.5%, 12.6% and 7.2% respectively. In the areas of flat slope, gentle slope, medium slope and steep slope, there were 116 million, 456 million, 144 million and 2 million mu of cropland respectively and their regional mean RRAs were 34.6%, 20.7%, 8.5% and 2.3% respectively.

The agricultural reclamations in the Xiliao River Valley since the Holocene have led to a huge landscape change from grassland to farmland. In this paper we reconsider the man-land relationship in the Xiliao River Valley by analyzing three major agricultural reclamations in prehistory, the Liao-Jin Dynasty and the period since the Qing Dynasty. We argue that when the demographic pressure appears in this area, especially during the last reclamation, the intraregional migration (second migration) is the major response to relieve such pressure, which also distinguishes two different settlement locations: “the initial area” and “the secondary area”. Due to the environmental differences between these two areas, the cultivation on the latter one has caused more serious disturbance to the local environment. Thus the secondary area has become the key region which needs environmental management seriously.

Cultivation is one of the most important human activities affecting the grassland ecosystem besides grazing, but its impacts on soil total organic carbon (C), especially on the liable organic C fractions have not been fully understood yet. In this paper, the role of cropping in soil organic C pool of different fractions was investigated in a meadow steppe region in Inner Mongolia of China, and the relationships between different C fractions were also discussed. The results indicated that the concentrations of different C fractions at steppe and cultivated land all decreased progressively with soil depth. After the conversion from steppe to spring wheat field for 36 years, total organic carbon (TOC) concentration at the 0 to 100 cm soil depth has decreased by 12.3% to 28.2%, and TOC of the surface soil horizon, especially those of 0-30 cm decreased more significantly (p<0.01). The dissolved organic carbon (DOC) and microbial biomass carbon (MBC) at the depth of 0-40 cm were found to have decreased by 66.7% to 77.1% and 36.5% to 42.4%, respectively. In the S.baicalensis steppe, the ratios of soil DOC to TOC varied between 0.52% and 0.60%, and those in the spring wheat field were only in the range of 0.18%-0.20%. The microbial quotients (qMBs) in the spring wheat field, varying from 1.11% to 1.40%, were also lower than those in the S. baicalensis steppe, which were in the range of 1.50%-1.63%. The change of DOC was much more sensitive to cultivation disturbance. Soil TOC, DOC, and MBC were significantly positive correlated with each other in the S. baicalensis steppe, but in the spring wheat field, the correlativity between DOC and TOC and that between DOC and MBC did not reach the significance level of 0.05.

Karamay City is a typical mining city, relying on oilfield exploration and development. After 60 years of construction and development, Karamay has become the first large oilfield and an important base of the national petroleum and petrochemical industry in China. Based on spatial analysis, and Geographic Information Systems (GIS) grid computing and overlay techniques, whilst considering the effect of oilfield development and aimed at the ecological problems of Karamay City in the Xinjiang Uygur Autonomous Region of China, we conducted research on the spatial characteristics of the comprehensive ecological sensitivity of Karamay. The ecological problems of natural environment evolution include soil erosion, land desertification, soil salinization, and biodiversity reduction. The most significant disturbance factor from the activities of humans in this area is oilfield exploitation. This study carries out an analysis of single factor ecological problem sensitivity and integrated ecological sensitivity. The results of the research are as follows: (1) Soil erosion is relatively sensitive, especially in Karamay district, Dushanzi district, north of Urho district and west of Baijiantan district, which is mainly a result of the vertical dropping slopes, serious rainfall erosion and the distribution of scattered woodland. (2) The main types of land desertification are represented by high and moderate grade sensitivities, and high and extremely high sensitive areas are distributed in the intersection of Karamay and Baijiantan districts. This is due to evaporation exceeding rainfall in these areas, and the soil mainly consists of sand and is seldom covered by vegetation. (3) The soil salinizatiion sensitivity grades are mainly moderate, high and extremely high. The highly sensitive areas are mainly distributed in southeast of Baijiantan district, north and east of Karamay district and east of Urho district. The primary causes are evaporation exceeding rainfall and extreme human activities. (4) The main types of biodiversity sensitivity are light and moderate grade. Highly sensitive areas are located in the east and south of Karamay district, north of the Baiyang River basin and parts of the wetland areas. (5) Oil fields development areas are highly ecologically sensitive, which are located in the northern oilfields of Urho district, western oilfields of Baijiantan district, northwestern oilfields of Karamay district and central oilfields of Dushanzi district. (6) The main types of integrated ecological sensitivity are high and moderate. The high and extremely highly sensitive areas are located in the central and northern parts of Karamay district, and southwest of Baijiantan district. The evaluation results will provide guidance for the future planning and development, the protection of the ecological environment and the realization of harmonious social, economic, and ecological development in Karamay City.

The IGU Regional Conference (UGI 2011) was held on November 14-18, 2011 in Santiago, Chile. It was organized by the Military Geographic Institute (IGM). Nearly 1000 geographers across the world participated in this event. The Geographical Society of China (GSC) sent a delegation consisting of more than 40 members to attend the conference.

Carrying capacity research has been carried out for a long time. However, synthesized carrying capacity researches based on systematic views began only in the 1970s. There is even less work done in China. This paper tries to address both synthesized carrying capacity research and its utilization in China. State spaces method from the systematic science was borrowed to construct the conceptual model of regional carrying capacity. Based on the conceptual model and the surveys in the Bohai Rim area, we construct a representative indicators system for quantifying regional carrying capacity in the Bohai Rim. While employing system dynamic models we simulated the evolving trend of both the regional carrying states and regional carrying capacity from 1999 to 2015. The results proved the statement that Bohai Rim is overall over-capacity for a long time and will be over-capacity in the foreseeable future. Among all the restriction factors, water shortage and environmental pollution stand out to be the two primary obstacles for Bohai Rim’s sustainable development. Regional differentiation analysis further indicates that coastal areas of the Bohai Rim burden more than its overall level. However, Shandong province shows some good signs in addressing the regional carrying capacity issues. The research is successful in addressing the quantification of regional carrying capacity issues, but nonetheless it needs further refinery and more information.

In this study, a monthly dataset of temperature time series (1961-2010) from 12 meteorological stations across the Three-River Headwater Region of Qinghai Province (THRHR) was used to analyze the climate change. The temperature variation and abrupt change analysis were examined by using moving average, linear regression, Spline interpolation, Mann-Kendall test and so on. Some important conclusions were obtained from this research, which mainly contained four aspects as follows. (1) There were several cold and warm fluctuations for the annual and seasonal average temperature in the THRHR and its three sub-headwater regions, but the temperature in these regions all had an obviously rising trend at the statistical significance level, especially after 2001. The spring, summer, autumn and annual average temperature increased evidently after the 1990s, and the winter average temperature exhibited an obvious upward trend after entering the 21st century. Except the standard value of spring temperature, the annual and seasonal temperature standard value in the THRHR and its three sub-headwater regions increased gradually, and the upward trend for the standard value of winter average temperature indicated significantly. (2) The tendency rate of annual average temperature in the THRHR was 0.36℃10a^-1, while the tendency rates in the Yellow River Headwater Region (YERHR), Lancangjiang River Headwater Region (LARHR) and Yangtze River Headwater Region (YARHR) were 0.37℃10a^-1, 0.37℃10a^-1 and 0.34℃10a^-1 respectively. The temperature increased significantly in the south of Yushu County and the north of Nangqian County. The rising trends of temperature in winter and autumn were higher than the upward trends in spring and summer. (3) The abrupt changes of annual, summer, autumn and winter average temperature were found in the THRHR, LARHR and YARHR, and were detected for the summer and autumn average temperature in the YERHR. The abrupt changes of annual and summer average temperatures were mainly in the late 1990s, while the abrupt changes of autumn and winter average temperatures appeared primarily in the early 1990s and the early 21st century respectively. (4) With the global warming, the diversities of altitude and underlying surface in different parts of the Tibetan Plateau were possibly the main reasons for the high increasing rate of temperature in the THRHR.

Employing DEA model and Malmquist productivity index, this paper probes into the urban efficiencies of 24 typical resources-based cities in China and their changes from 2000 to 2008. The research finds that the overall efficiencies of the resources-based cities are just at a general level, and only a few of them reach the optimal level. The scale efficiency is the major determining factor of the achievement of overall efficiency, the effect of which, nevertheless, is reducing. From the perspective of classification characteristics, the resources- based cities in northeastern region have been in the front rank in terms of overall efficiency, pure technical efficiency and scale efficiency. There is a certain positive correlation between urban population scale and urban efficiency. The analysis of urban efficiency changes shows that the changes in overall efficiency of resources-based cities from 2000 to 2008 had a weak improving tendency. Both the technical change index and productivity change index decreased, indicating that the urban efficiency did not improve during this period, and the tendency of technical recession and productivity decline was obvious. In terms of the classification of urban efficiency changes, the urban overall efficiency improved in each of the four regions from 2000 to 2008, among which western region witnessed the greatest increase. Cities with different resource types have improved their urban overall efficiencies except steel-based cities. The urban overall efficiency increased in resources-based cities of different scales, with greater improvement in small and medium-sized cities than in big cities.

Land use transition refers to the changes in land use morphology (both dominant morphology and recessive morphology) of a certain region over a certain period of time driven by socio-economic change and innovation, and it usually corresponds to the transition of socio-economic development phase. In China, farmland and rural housing land are the two major sources of land use transition. This paper analyzes the spatio-temporal coupling characteristics of farmland and rural housing land transition in China, using high-resolution Landsat TM (Thematic Mapper) data in 2000 and 2008, and the data from the Ministry of Land and Resources of China. The outcomes indicated that: (1) during 2000-2008, the correlation coefficient of farmland vs. rural housing land change is -0.921, and it shows that the change pattern of farmland and rural housing land is uncoordinated; (2) the result of Spearman rank correlation analysis shows that rural housing land change has played a major role in the mutual transformation of farmland and rural housing land; and (3) it shows a high-degree spatial coupling between farmland and rural housing land change in southeast China during 2000-2008. In general, farmland and rural housing land transition in China is driven by socio-economic, bio-physical and managerial three-dimensional driving factors through the interactions among rural population, farmland and rural housing land. However, the spatio-temporal coupling phenomenon and mechanism of farmland and rural housing land transition in China are largely due to the “dual-track” structure of rural-urban development.

This book, written by Tian-Xiang Yue, on surface modelling, was published by CRC Press. It consists of 20 chapters. Chapter 1 reviews the existing classical methods for surface modeling and analyzes their shortcomings.

Land system change has never been out of human concerns. It is always one of the hottest themes in global environmental change research (Seto et al., 2002; Gutman et al., 2004).

Central Asia features an arid and semi-arid climate, and the region is undergoing urbanization in the context of a fragile eco-environment. The influence of specific historical events in this region also persists on this ongoing urbanization. This study examines the mechanism of interaction between urbanization and the resource environment in Central Asia. The following results were obtained. (1) In different periods—Russian colonization, the era of the Soviet Union, and Central Asian countries as independent—the interactions between urbanization and the resource environment varied. (2) Variations in land use within 50 km of major cities of the region reflect both the trend of urbanization and that of variations in the eco-environment. In Kyrgyzstan and Tajikistan, where urbanization has been slow, the supportive effect of the eco-environment for urbanization was clear. In Uzbekistan and Turkmenistan, where freshwater resources are scarce, a close relationship was noted between urbanization and variations in the eco-environment. In Kazakhstan, fast urbanization has had a significant impact on the availability of water, grassland, and woodland in the relevant areas. (3) The efficiency of utilization of land and water resources is generally low. The compactness of the urban land of 47 major cities in Central Asia decreased from 0.44 in 1990 to 0.31 in 2015. Of them, 31 cities decreased in compactness, including all national capitals. Regardless of the level of urbanization, water consumption was high across the region. (4) The mechanisms of interaction between urbanization and the resource environment in Central Asia in the three stages were formulated to illustrate their specific temporal conductivity and spatial relevance.

In the context of accelerated development of the Silk Road Economic Belt, it is necessary to conduct in-depth research on urbanization of Central Asian countries. This paper analyzes the spatial and temporal patterns and evolution dynamics of urbanization during the period 1991-2017 from the perspective of internal-external forces. The results are as follows. (1) The urbanization process of the five Central Asian countries studied is significantly influenced by their political and economic situations and displays periodic characteristics. All five countries experienced a stagnation development stage at the beginning of independence, and then a rapid growth stage since the year 2000. The average annual growth rates of the two stages were 0.19% and 1.45%, respectively. (2) Differences in the urbanization of the studied countries are obvious, and the evolutionary characteristics of each subsystem of urbanization are different. It is therefore necessary to distinguish and clearly understand the urbanization process of each country. (3) Internal and external factors play a role in the urbanization processes of Central Asian countries. External railway transportation facilities are particularly important for the development of urbanization in these countries. The regression coefficients of railway construction length, total merchandise trade and actually utilized foreign capital are 0.5665, 0.0937 and 0.0806, respectively. (4) Countries with smaller populations and economic scales need to engage in international cooperation to promote healthy development of urbanization. The results of the study indicate that internal and external factors work together in the urbanization process of Central Asian countries, and external forces are particularly important for the development of such urbanization.

This study undertakes a systematic examination of characteristics of the spatio-temporal evolution of industrial economies in Central Asia from the perspectives of industrial scale, structural rationality, industrial competitiveness, and industrial isomorphism. The results show that industrial structures in Central Asian countries are becoming increasingly advanced, with certain differences among them in the characteristics of this evolution. Kazakhstan has long had a tertiary-secondary-primary industrial pattern, and productive services have played an increasingly prominent role in the development of its tertiary industry. The transformation of the industrial structure in Uzbekistan, from a secondary-tertiary- primary pattern at its independence from the Soviet Union to a tertiary-secondary-primary pattern, is apparent. Tajikistan’s industrial structure has also changed significantly in recent times. Its secondary industries shrunk while tertiary industries developed rapidly. In Kyrgyzstan, the ratios of secondary and tertiary industries to total industrial output have fluctuated significantly while considerable progress has been made in the service sector. The industrial structure of Turkmenistan is significantly lower than the other countries, and Turkmenistan is the only country in the Central Asian region which still shows a tertiary-secondary-primary industrial pattern. The feasibility and competitiveness of the industrial structures of these five Central Asian countries have different characteristics. Kazakhstan has structural advantages but lags in competitiveness, Uzbekistan is driven by both structural and competitive advantages, Tajikistan enjoys structural advantages while Kyrgyzstan lags behind in competitiveness, and Turkmenistan has a competitiveness-driven economy. Furthermore, values of the similar coefficient index of the three industrial structures in these countries were mostly above 0.95, the coefficients of the secondary industrial subdivisions in some countries were below 0.85, and those of tertiary industrial subdivisions among most countries were above 0.89, indicating considerable similarities in industrial structure among them. These findings are important in the context of establishing an effective industrial development strategy for the Silk Road Economic Belt, improving international cooperation, and upgrading industrial structures to achieve economic prosperity.

When viewed against the backdrop of globalization and the Belt and Road Initiative (BRI), Central Asia has ushered in new development opportunities. However, problems of ecological environment as a consequence of urbanization have begun to act as a constraint on the economic development of the region. the coupling coordination degree between the urbanization and ecological environment in Kazakhstan was analyzed by the coupling coordination degree model. The main controlling factors affecting its development were explored using a geographical detector. Several main conclusions can be drawn. (1) Kazakhstan's urbanization level, ecological environment level, and the coupling coordination degree between urbanization and ecological environment are all on the rise. (2) In terms of the comprehensive urbanization index, the western and eastern states have higher values than the southern and northern states. The spatial distribution pattern of the ecological environment index revealed high values in the eastern and western regions and low values in the central region. (3) The coupling coordination degree among the states of Kazakhstan is mostly at a low-moderate level. The spatial distribution shows that the coordination level of the east, middle, and west of the country is higher than that of south and north. (4) Indicators such as GDP per capita, social fixed asset investment per capita, employment in industry and services (% of total employment), and the number of college students per 10,000 people are important urbanization factors that affect the coupling coordination degree of urbanization and ecological environment. Indicators of farmland areas per capita, availability of water resources per capita, ecological land per capita and forest coverage in the ecological environment subsystem are important ecological environmental factors that affect the degree of coordination between urbanization and ecological environment in Kazakhstan. The interaction of the main elements in the two subsystems has a strong synergy.

Energy development has a significant impact on urbanization. This study employs the entropy method to evaluate the level of urbanization in Central Asia and further analyzes the possible dynamic transition mechanisms of the impact of energy development (characterized by energy development scale, energy trade, energy consumption, and energy endowment) on urbanization using the Panel Smooth Transition Regression model (PSTR). The results demonstrate that energy development in this region is characterized by “three highs and one low”, namely, high production volume, high export volume, high endowment, and low self-consumption, and plays a crucial role in the progress of urbanization. A nonlinear relationship is found to exist between energy development and comprehensive urbanization in the transition economies of Central Asia. Generally speaking, as energy development continues to expand, its impact on urbanization in this region has shifted from constraint to promotion, with the latter gradually tending to flatten out. Energy development characterized by energy development scale, energy consumption, and energy trade can prove the point, whose threshold is 1.47 million tons oil equivalent (Mtoe), 0.29 tons oil equivalent (toe) per capita, and 20.95 Mtoe, respectively. However, not all energy development models exhibit this behavior. Energy development characterized by energy endowment is such a case where the positive effect of it on comprehensive urbanization will be restrained when it exceeds 3.18. These findings can aid decision makers in seeking a better energy development model to promote the sustainable development of urbanization in Central Asia, avoiding energy resources waste and disorderly development.

Central Asia is emerging as an important pole of global economic and political power, thanks to its unique location at the heart of Eurasia and its abundance in energy reserves. This study explores the social power change in Central Asia from the perspective of cross-border mergers and acquisitions (M&A) by using the social network method. The main results are as follows: (1) The complexity of the energy M&A network has significantly decreased after the financial crisis in 2008. In the meantime, energy M&A became an important way to enhance energy power for buyer countries. Betweenness centrality is becoming the most significant factor affecting energy power, yet the effect of out-degree is weakening. (2) The community underwent multifaceted restructuring, which reflected the shift of energy power in Central Asia. Kazakhstan is the most powerful country in the energy sector in Central Asia. In addition, East Asian countries/regions, represented by China, are actively enhancing their energy power. (3) Different M&A modes reflect various M&A motivations of countries in the energy sector. In the future, more efforts should be made to promote the establishment of a pragmatic and efficient multilateral energy cooperation mechanism and strength the cooperation of the economy and energy finance when China participates in the energy market in Central Asia.

To ensure adequate oil supply and mitigate geopolitical uncertainties, China has diversified its sources of crude oil imports in recent years. Central Asia is a neighbor region of China, rich in oil and natural gas reserves, which can play an important role in China’s strategy to reduce its dependence on energy supplies from the Middle East. The geopolitical attributes of energy and the geopolitical situation in Central Asia determine that Central Asia’s energy development and cooperation are disturbed by domestic and foreign factors, and also face the risks of complex energy structural evolution and geopolitical games, which create a unique energy geopolitical pattern in Central Asia. This study proposes an analysis framework for energy geopolitics in Central Asia, arguing that the complexity of energy geopolitics in Central Asia can be demonstrated from the perspectives of both the main countries of energy development (game actors) and the whole-industry-chain of energy development (game themes). The most obvious feature of Central Asian energy geopolitics is the fierce game that is played between key countries and regions, Russia, the United States, China, the European Union (EU), Japan, India, Iran, and Turkey. Strategic geopolitical considerations and resource requirements necessitate the active participation of these players in Central Asian energy development and mean that the foreign policy agendas of states in this region are likely to become ever more crowded. Therefore, the energy cooperation between China and Central Asia faces the geopolitical risks of the great power games. It is necessary to develop reasonable and effective policies to establish guarantee mechanisms to minimize the risks of energy cooperation. This study characterizes the energy geopolitical strategies of Russia, the United States, China, and other related powers in Central Asia. It also assesses the country risks faced by energy cooperation between China and Central Asian countries. To withstand possible geopolitical and country risks, this study develops a series of policy frameworks which can be used to fortify the stability of the energy cooperation between China and Central Asian countries, and can also be effective in responding to the array of risks that might be encountered in the coming years.

Based on methods such as stochastic frontier production function, this paper analyses the changes of single factor productivity (SFP) and total factor productivity (TFP) of agriculture in the five Central Asian countries, during the period of 1992 to 2017. The research results show that the agricultural output in most of the five Central Asian countries has increased steadily, while agricultural labor productivity has shown a growth trend. With the exception of Kazakhstan, the land productivity of the other four countries shows a growth trend. In terms of factor input, the number of agricultural workers in the five Central Asian countries mainly shows a trend of decrease, with the input of chemical fertilizer increasing, and the amount of agricultural machinery increasing or decreasing within a small range. The total factor productivity in the five Central Asian countries has improved, but it is still at a low level. The policy suggestions contained in the research conclusions are as follows: (1) Promote the growth of agricultural TFP in the five Central Asian countries, and strengthen the emphasis on the input and allocation of agricultural factors; (2) be aware of the innovation of agricultural technology, as well as the promotion and diffusion of existing agricultural technologies, and improve the overall technical efficiency of agriculture; and (3) accelerate the effective flow of capital and other elements to the agricultural sector, improve infrastructure, better release the “dividend” of science and technology, and enhance the output efficiency.

In recent years, flows of many rivers and lakes have become reduced in arid and semi-arid regions around the world. The most typical examples of this phenomenon occur in Central Asia, and the reduction of the Aral Sea area is closely related to agricultural water use. However, due to a lack of continuous data in Central Asia spanning many years, “virtual water” is used to evaluate changes in agricultural water use. Based on virtual water theory, 325 kinds of agricultural products in eight categories are selected as the research object, and changes in virtual water are calculated for Central Asia from 1992 to 2016. Results indicate that: (1) The average annual net export of agricultural virtual water (TVWNE) in Central Asia is about 9 billion m3, concentrated in Kazakhstan, whose annual TVWNE reaches 8.1 billion m ³. (2) Since 2007, the TVWNE in Central Asia has dropped significantly, with a drop rate of 86%, while the total volume of agricultural virtual water has gradually increased since 1998. (3) The upstream and downstream countries in Central Asia have different characteristics in the change of virtual water quantity.

Rivers in deserts present unique geographical features owing to aeolian-fluvial interactions. In this study, 510 surface sediment samples were gathered from eight watersheds to systematically examine the major element characteristics of riparian sand dunes in northern China deserts. The findings revealed that these dunes could be categorized into three primary zones: Type I, comprising Keriya, Tora, Heihe, and Langqu rivers in the west; Type II, featuring the Maquan River in the Tibetan Plateau; and Type III, including Mu Bulag, Kuye, and Xar Moron rivers in the east. Specifically, the Type III region is characterized by a limited fresh material supply, a relatively high Chemical Index of Alteration (CIA), and the influence of nearby rivers on the provenance of riparian dunes, leading to a higher degree of chemical weathering than that of Type I in the west. Notably, Type II is marked by weak-moderate chemical weathering degree and a comparatively higher CIA value. These classifications and their difference of degree of chemical weathering are possibly governed by the type of parent rock and the availability of material. This research offers new insights into the classification of riparian dunes impacted by aeolian-fluvial interactions in arid regions of the northern China deserts. Furthermore, it provides valuable implications for studies focusing on the provenance of sediments.

Glaciers in the Tianshan Mountains are an essential water resource in Central Asia, and it is necessary to identify their variations at large spatial scales with high resolution. We combined optical and SAR images, based on several machine learning algorithms and ERA-5 land data provided by Google Earth Engine, to map and explore the glacier distribution and changes in the Tianshan in 2001, 2011, and 2021. Random forest was the best performing classifier, and the overall glacier area retreat rate showed acceleration from 0.87%/a to 1.49%/a, while among the sub-regions, Dzhungarsky Alatau, Central and Northern/Western Tianshan, and Eastern Tianshan showed a slower, stable, and sharp increase rates after 2011, respectively. Glacier retreat was more severe in the mountain periphery, low plains and valleys, with more area lost near the glacier equilibrium line. The sustained increase in summer temperatures was the primary driver of accelerated glacier retreat. Our work demonstrates the advantage and reliability of fusing multisource images to map glacier distributions with high spatial and temporal resolutions using Google Earth Engine. Its high recognition accuracy helped to conduct more accurate and time-continuous glacier change studies for the study area.

Situated in the hinterland of Eurasia, Central Asia is characterized by an arid climate and sparse rainfall. The uneven spatial distribution of water and land resources across the region has pressured economic and social development. An accurate understanding of Central Asia's water resources carrying capacity (WRCC) is vital for enhancing the sustainability of water resources utilization and guiding regional economic and social activities. This study aims to facilitate the sustainability of water resources utilization by evaluating the region's WRCC from the viewpoints of economic and technological conditions and social welfare. A concise yet effective model with relatively fewer parameters was established by adopting water resources data from the Food and Agriculture Organization (FAO) and socioeconomic data from the World Bank. The results indicated that the WRCC of all five Central Asian countries showed an increasing trend with improved water use efficiency from 1995 to 2020. Kazakhstan's WRCC was significantly higher than the other four countries, reaching 54.03 million people in 2020. The water resources carrying index (WRCI) of the five Central Asian countries varied considerably, with the actual population sizes of Turkmenistan and Uzbekistan highly overloaded. Although there has been a decrease in Central Asian countries’ WRCI between 1995 and 2020, water resources utilization problems in the region remain prominent. Based on the water resources carrying capacity evaluation system, to increase available water resources and improve production water use efficiency are key to address these issues. In light of this, this study offers practical and feasible solutions at the policy level: (1) The implementation of signed multilateral agreements on transboundary water resources allocation must proceed through joint governmental efforts. (2) Investments in advancing science and technology need to be increased to improve water use efficiency in irrigation systems. (3) The output of water-intensive crops should be reduced. (4) The industrial structure could be further optimized so that non-agricultural uses are the primary drivers of gross domestic product (GDP) growth.