Climate change investigation at a watershed-scale plays a significant role in revealing the historical evolution and future trend of the runoff variation in watershed. This study examines the multisource hydrological and meteorological variables over the source area of the Yellow River (SAYR) from 1961 to 2012 and the future climate scenarios in the region during 2006-2100 based on the CMIP5 projection data. It recognizes the significant characteristics of the recent climate change in the SAYR and predicts the change trend of future flow in the region. It is found that (1) The climate in the SAYR has experienced a significant warm-wet change since the early 2000s, which is very different from the antecedent warm-dry trend since the late 1980s; (2) The warm-wet trend in the northwestern SAYR (the headwater area of the Yellow River (HAYR), is more obvious than that in the whole SAYR; (3) With precipitation increase, the runoff in the region also experienced an increasing process since 2006. The runoff variations in the region are sensitive to the changes of precipitation, PET and maximum air temperature, but not very sensitive to changes in mean and minimum air temperatures; (4) Based on the CMIP5 projection data, the warm-wet climate trend in SAYR are likely to continue until 2049 if considering three different (i.e. RCP2.6, RCP4.5 and RCP8.5) greenhouse gas emission scenarios, and the precipitation in SAYR will not be less than the current level before 2100; however, it is estimated that the recent flow increase in the SAYR is likely to be the decadal change and it will at most continue until the 2020s; (5) The inter-annual variations of the East Asian winter monsoon are found to be closely related to the variations of annual precipitation in the region. Meanwhile, the increased precipitation as well as the increase of potential evapotranspiration (PET) being far less than that of precipitation in the recent period are the main climate causes for the flow increase in the region.

Sixty water samples (35 groundwater samples, 22 surface water samples and three hot-spring water samples) were collected at 36 points from villages and towns in Lhasa city, Nagchu (Nagqu) prefecture, Ali (Ngari) prefecture and Shigatse (Xigaze) prefecture (Tibet) in 2013 to study the hydrochemical characteristics and element contents of natural waters. The concentrations of elements were determined in the water samples and compared with the concentrations in water samples from other regions, such as southeast Qinghai, south Xinjiang, east Sichuan and west Tibet. The hydrochemical species in different areas were also studied. Water in most parts of Tibet reaches the requirements of the Chinese national standard and the World Health Organization international standard. The pH values of the water samples ranged from 6.75 to 8.21 and the value for the mean total dissolved solids was 225.54 mg/L. The concentration of arsenic in water from Ali prefecture exceeded the limit of both the Chinese national standard and the international standard and the concentration of fluoride in water from Shuanghu exceeded the limit of both the Chinese national standard and the international standard. The main hydrochemical species in water of Tibet is Ca (HCO₃)₂. From south to north, the main cation in water changes from Ca²⁺ to Na⁺, whereas the main anions in water change from HCO₃^- to Cl^- and SO₄^2-. The chemistry of river water and melt water from ice and snow is dominated by the rocks present at their source, whereas the chemistry of groundwater is affected by many factors. Tectonic divisions determine the concentrations of the main elements in water and also affect the hydrochemical species present.

The Manasarovar Basin in southern Tibet, which is considered a holy land in Buddhism, has drawn international academic attention because of its unique geographical environment. In this study, based on actual measurements of major ion concentrations in 43 water samples collected during the years 2005 and 2012, we analyzed systemically the spatial- temporal patterns of water chemistry and its controlling factors in the lake and inflowing rivers. The results reveal that the water in the Manasarovar Basin is slightly alkaline, with a pH ranging between 7.4-7.9. The amounts of total dissolved solids (TDS) in lake and river waters are approximately 325.4 and 88.7 mg/l, respectively, lower than that in most of the surface waters in the Tibetan Plateau. Because of the long-term effect of evaporative crystallization, in the lake, Na⁺ and HCO₃^- have the highest concentrations, accounting for 46.8% and 86.8% of the total cation and anion content. However, in the inflowing rivers, the dominant ions are Ca²⁺ and HCO₃^-, accounting for 59.6% and 75.4% of the total cation and anion content. The water exchange is insufficient for such a large lake, resulting in a remarkable spatial variation of ion composition. There are several large inflowing rivers on the north side of the lake, in which the ion concentrations are significantly higher than that on the other side of the lake, with a TDS of 468.9 and 254.9 mg/l, respectively. Under the influence of complicated surroundings, the spatial variations in water chemistry are even more significant in the rivers, with upstreams exhibiting a higher ionic content. The molar ratio between (Ca²⁺+Mg²⁺) and (Na⁺+K⁺) is much higher than 1.0, revealing that the main source of ions in the waters is carbonate weathering. Although natural processes, such as rock weathering, are the major factors controlling main ion chemistry in the basin, in the future we need to pay more attention to the anthropogenic influence.

Based on SPOT-5 images, 1:1 million topographic maps, the maps of the returning farmland to forest project and the Chongqing forest project, social and economic statistics, etc., this paper identifies the features and factors influencing farmland marginalization. The results showed: (1) During 2002-2012, the rate of farmland marginalization was 16.18%, which was mainly found in the high areas of northern Qiyao mountains and the medium-altitude areas of southern Qiyao mountains. And this farmland marginalization will increase, associated with non-agriculturalization of rural labourers and aging of the remaining labourers. (2) Elevation, distance radius from villages and road connections had a great influence on farmland marginalization. Farmland marginalization rates showed an increasing trend with the increase of elevation, and 60.88% of the total farmland marginalization area is found at an altitude greater than 1000 m above sea level. The marginalization trend also increases with slope and distance from the distribution network. (3) Farmland area per labourer and the average age of farm labourers were major factors driving farmland marginalization. Farmland transfer and small agricultural machinery sets affect farmland marginalization with respect to management and productivity efficiency. (4) Farmland with “comparative- disadvantage-dominated marginalization” accounted for 55.32% of the total farmland marginalization area, followed by “location-dominated marginalization” (33.80%). (5) According to the specifics of each real situation, different policies are suggested to mitigate the marginalization. A “continuous marginalization” policy will encourage the return of farmland to forest in “terrain-dominated marginalization”. An “anti-marginalization” policy is suggested to create new rural accommodation and improve the rural road system to counteract “terrain-dominated marginalization”. And another “anti-marginalization” policy is planned to improve management and micro-mechanization for “comparative-disadvantage-dominated marginalization”. A new idea was developed to integrate high resolution remote sensing and statistical data with survey information to identify land marginalization and its driving forces in mountainous areas.

Transport infrastructure plays an important role in shaping the configuration of spatial socio-economic structures and influencing regional accessibility. Although China’s transport infrastructure has been experiencing a rapid development in the last 100 years, there lacks a systematic examination of the complete evolution history of China’s transport development, particularly with all kinds of transport modes. This paper first aims to clarify the history of China’s transportation from 1910 to 2012, and divides its evolution process into five periods (1911, 1935, 1953, 1981 and 2012) whereby each period represents the preliminary development time for each transport mode. Second, the paper calculates the transport dominance and analyses its spatial distribution in each period, with county as the basic analysis unit. Transport dominance here is defined as an integrated indicator for evaluating regional transport conditions. The results demonstrate the following: (1) areas with relative good transport dominance have expanded from scattered dots such as Tianjin, Shanghai, Guangzhou in 1911 to extensive areas with each provincial city as cores in 2012; (2) transport development is improved by advances in transportation technology. The construction of modern transport infrastructures such as seaports, airports, high-speed rails (HSRs), and freeways lead the expansion of national territorial areas with good and excellent transport dominance and the increase of the value of transport dominance over time; (3) transport dominance is spatially unevenly distributed and exhibits resemblance with the expansion of transport network, which is closely related to China’s socio-economic development and policies.

Due to its great strategic significance in integrating regional coordinated development and enhancing the rise of Central China, urban agglomeration in the middle reaches of Changjiang (Yangtze) River has attracted much attention from both theoretical and practical aspects. Such research into the area’s economic network structure is beneficial for the formation of an urban- and regional-development strategy. This paper constructs an economic tie model based on a modified gravitation model. Subsequently, referring to social network analysis, the paper empirically studies the network density, network centrality, subgroups and structural holes of the middle reaches of Changjiang River’s urban agglomeration economic network. The findings are fourfold: (1) an economic network of urban agglomeration in the middle reaches of Changjiang River has been formed, and economic ties between the cities in this network are comparatively dense; (2) the urban agglomeration in the middle reaches of Changjiang River can be divided into four significant subgroups, with each subgroup having its own obvious economic communications, while there is less economic-behavioral heterogeneity among subgroups - this is especially true for the two subgroups that exist in the Poyang Lake Ecological Economic Zone; (3) an economy pattern driven by the central cities of Wuhan, Changsha and Nanchang has emerged in the urban agglomeration of the middle reaches of Changjiang River, while these three capital cities have exerted great radiation abilities to their surrounding cities, the latter are less able to absorb resources from the former; (4) the Wuhan Metropolitan Areas and the Poyang Lake Ecological Economic Zone have more structural holes than the Ring of Changsha, Zhuzhou and the Xiangtan City Clusters, meaning that cities at the periphery of these two areas are easily constrained by central cities. The Ring of Changsha, Zhuzhou and the Xiangtan City Clusters have fewer structural holes; thus, the cities in this area will not face as many constraints as those in the other two areas.

Urban population during the daytime and at night and their spatial distribution are important bases for planning urban infrastructure, public services and disaster relief. As current population statistics cannot distinguish urban population during the daytime from that at night, existed research in this field are quite limited. This paper tries to advance studies at this aspect by establishing a relationship model for the three components of ‘population, land use and time (daytime or night)’ to explore the temporal and spatial characteristics of different types of population, which is aimed to estimate urban population during the daytime and at night and to analyze their spatial characteristics at grid scale. Furthermore, an empirical case study has been carried out at the Haidian District in Beijing, China to test the model. The results are as follows: (1) The spatial structure of urban population during the daytime is significantly different from that at night. The spatial distribution of urban population during the daytime is more extensive and more agglomerated that that at night. (2) Several types of spatial coupling relationship between population during the daytime and that at night have been identified, such as sandwich mode, symmetry mode, convergence mode and single mode, etc. (3) The spatial distribution of daytime and nighttime population also reflects certain factors during the development of China, such as the distribution of old residential areas, the construction of new industrial districts, and the differences between urban and rural areas, which can provide reference points for studies in this field and other regional research.

The isotope-equipped GCMs (general circulation models) are useful tools to investigate the isoscape in precipitation and water vapor, especially for the regions without enough in-situ observations. To study the spatial distribution and seasonal variation of precipitation isotopic composition in arid central Asia, several isotope-equipped GCMs are applied, and the long-term observations in two stations are used to verify the GCM-simulated results. Generally, seasonality of isotopic composition can be well simulated in each GCM, and the values of δ¹⁸O in precipitation are larger in summer months (from April to October) and lower in winter months (from November to March). Higher latitude usually shows lower values of δ¹⁸O in precipitation, and lower latitude has higher values. The values of δ¹⁸O are relatively low in the eastern section, and higher in the western section. Among these simulations, ECHAM is good at describing the isotopic composition in the study region, which can be seen from the mean absolute error (MAE) and root-mean-square error (RMSE). The ECHAM-derived values of δ¹⁸O in precipitation positively correlate with the observed series, and the correlation coefficient based on ECHAM is the largest among these GCMs.

This study analyses spatial variability and trends in annual and monthly precipitation (amount and concentration) based on data from 42 stations in mainland Portugal during the period 1960-2011. Relationships between certain geographic variables (elevation, latitude and longitude) and precipitation variability were also determined in order to check for specific dependencies and spatial patterns in precipitation distribution, concentration and changing trends. Trends and relationships have been analysed using both parametric and non-parametric tests. The results showed that annual precipitation had decreased in all stations and that this trend is statistically significant for most of the time series (70% of the stations showed negative trends with at least a 0.1 significance level). The Annual Precipitation Concentration Index revealed an opposite behaviour pattern, suggesting that even though the annual trend for precipitation amount was negative overall, more than half of the udometric stations registered a more marked seasonality for precipitation during the period 1960-2011. However, only one station showed statistical significant time trend. Regarding the influence of geographical features, latitude is the most important variable, governing spatial distribution and variations in annual precipitation as well as its intra-annual changeability. These important changes in precipitation, involving both amount and concentration, may have severe consequences for ecosystems and societies.

Proxy records of the oxygen isotopic composition of meteorological precipitation (δ¹⁸O_p) preserved in archives such as ice cores, lacustrine carbonates and stalagmite calcite are important for paleoclimatic studies. Therefore, knowledge of the variations and controlling mechanisms of modern δ¹⁸O_p on different time scales is necessary. Here, we investigate the linear correlations between δ¹⁸O_p and corresponding temperature and precipitation on monthly and inter-annual timescales, using data from the Urumqi (1986-2003) and Hotan stations of the Global Network of Isotopes in Precipitation (GNIP), and δ¹⁸O data from 4 ice cores in the adjacent Tianshan Mountains. Consistent with previous reported results, modern δ¹⁸O_p variations on a seasonal time scale in the Tianshan region are mainly controlled by a ‘temperature effect’ (indicated by a significant positive correlation between δ¹⁸O_p and temperature), with more positive δ¹⁸O_p values occurring in summer. However, on an inter-annual timescale, there is a weak inverse correlation between weighted average annual δ¹⁸O_p and annual average temperature at Urumqi station. This finding is supported by the inversely varying trends of δ¹⁸O data from 4 ice cores in the central and eastern Tianshan Mountains compared to annual average temperatures in the same region during the past 40-50 years. The data from Urumqi station and the 4 ice cores demonstrate that there is inverse correlation between δ¹⁸O_p and temperature on inter-annual to decadal time scales. Analysis of water vapor sources and pathways for the warm year of 1997 and the cold year of 1988 reveal that relatively more water vapor for the Tianshan region was derived from long-distance transport from high-latitude sources than during the warm year of 1997; and that more water vapor was transported from more proximal sources from mid- to low-latitude areas during the cold year of 1988. In addition, the δ¹⁸O_p values are more negative in the high latitude areas than those in mid- to low-latitude areas in the Eurasian continent at the upper wind direction of Tianshan Mountains region, according to the weighted averaged warm season (May to September) δ¹⁸O_p values for 14 GNIP stations in the years 1997 and 1988. Due to the distribution of δ¹⁸O_p within the Eurasian continent, the relative shift of water vapor sources between warm and cold years convincingly explains the observed variations of δ¹⁸O_p in the Tianshan Mountains region. Therefore, we conclude that variations in δ¹⁸O_p in this region are mainly controlled by changes in water vapor sources which are ultimately caused by northward and southward shifts in the Westerly circulation.

Land function change has been the focus of scientific research and policy making worldwide. Agricultural development and land use demand at present in China shared common characteristics with the countries such as Japan, South Korea, USA, and European developed countries, which have undergone cultivated land function transition. Whether cultivated land function transition occurred is of significance for land change science and cultivated land protection in China. However, there has been no explicit methodology for cultivated land function change research. This paper firstly presents a methodology by integrating policy development analysis based on the normative connotation of cultivated land function or termed cultivated land function demand and quantitative assessment based on the positive connotation of cultivated land function or termed cultivated land function supply. Then, cultivated land function transition is diagnosed by analyzing cultivated land function change in 1949-2012. Results show that cultivated land function transition overall occurred in 2006. Specifically, the normative cultivated land function or cultivated land function demand fragmented into seven types in 1985 and upgraded in 2004. Total value of the positive cultivated land function or cultivated land function supply turned to rise with an increase from 2.40 to 2.45 as the coefficients of variability (CV) of the value of the seven functions decreased from 2.94 to 2.29 in 2006-2012. The two-year gap between these two aspects of transition mainly resulted from the time lag effects of policy implementation. In the process of the transition, co-ordination and malposition of supply and demand of cultivated land function coexisted with supply lag and function morphology distortion. Considering the transition experiences in the developed countries mentioned above, suggestions on multifunctional cultivated land management are proposed. Moreover, route of land use transition research is discussed.

The Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model is a widely used method to simulate land use change. An ordinary logistic regression model was integrated into the CLUE-S model to identify explanatory variables without considering the spatial autocorrelation effect. Using image-derived maps of the Changsha- Zhuzhou-Xiangtan urban agglomeration, the CLUE-S model was integrated with the ordinary logistic regression and autologistic regression models in this paper to simulate land use change in 2000, 2005 and 2009 based on an observation map from 1995. Significant positive spatial autocorrelation was detected in residuals of ordinary logistic models. Some variables that were much more significant than they should be were selected. Autologistic regression models, which used autocovariate incorporation, were better able to identify driving factors. The Receiver Operating Characteristic Curve (ROC) values of autologistic regression models were larger than 0.8 and the pseudo R² values were improved, compared with results of logistic regression model. By overlapping the observation maps, the Kappa values of the ordinary logistic regression model (OL)-CLUE-S and autologistic regression model (AL)-CLUE-S models were larger than 0.75. The results showed that the simulation results were indeed accurate. The Kappa fuzzy (Kfuzzy) values of the AL-CLUE-S models (0.780, 0.773, 0.606) were larger than the values of the OL-CLUE-S models (0.759, 0.760, 0.599) during the three periods. The AL-CLUE-S models performed better than the OL-CLUE-S models in the simulation of land use change. The results showed that it is reasonable to integrate autocovariates into CLUE-S models. However, the Kfuzzy values decreased with prolonged duration of simulation and the maximum range of time was not discussed in this paper.

Based on remote sensing data of the Yangtze River Delta (YRD) in the years of 1991, 2001 and 2008, the paper built an index system of land use potential restraint factors in YRD, according to geological condition, terrain condition, water area, natural reserve area and basic farmland, and evaluated construction land potential based on the platform of GIS spatial analysis model. The results showed that: (1) the construction land increased rapidly since 1991 and reached 24,951.21 km² in 2008, or 21.27% of the total area. Among all the cities in the YRD, Shanghai took the greatest percentage, followed by Jiangsu and Zhejiang. Spatially, areas where government departments are located became the growth center of construction land. Prefecture-level cities were the fastest growth region and the changing trend showed circle layered characteristics and significant increase with Shanghai and Suzhou as the core. (2) The higher the quality of construction land potentials (CLP), the smaller the number of CLP units. High sensitive area accounted for the largest percentage (40.14%) among all types of constraint regions and this was followed by medium sensitive region (31.53%) of the whole region. (3) The comprehensive CLP in the YRD was 24,989.65 km², or 21.76% of the total YRD. The land use potential showed spatial distribution imbalance. CLP of Zhejiang was obviously larger than that of Jiangsu. CLP was insufficient in regional central city. Moreover, CLP in the YRD formed a circle layered spatial pattern that increasingly expanded centered in prefecture-level cities. Low potential area expanded from north to south. High potential area was mainly located in south YRD. Areas with zero potential in the YRD formed a northwest-southeast “Y-shaped” spatial pattern in north Hangzhou Bay. (4) CLP per capita in YRD was 0.045 ha/person and also unevenly distributed. Some 25.57% of the study units at county level nearly had no construction land and 8.24% of the units had CLP per capita below the national average level. CLP per capita in less than 25% of the county-level units was larger than the YRD average level, which were mainly located in Zhejiang. Therefore, research on the construction potential area in YRD was favorable for analysis of the development status and potential space of this region under the background of rapid urbanization and industrialization.

Land suitability assessment (LSA) is one of the key processes of land-use planning. Given its particularity of land suitability assessment for post-earthquake reconstruction, this paper takes into account geological conditions, risk of disasters, water and land resources conditions, and eco-environmental suitability and emphasizes safety factor in the assessment. Taking the April 20, 2013 Mw 6.6 Lushan earthquake as a case, this assessment establishes factors system, uses GIS spatial analysis techniques and data of geology, topography, resources, and eco-environment to evaluate the land suitability for reconstruction. The results show that: (1) the spatial characteristics of land suitability for reconstruction at grid scale and administrative scale manifest that most of the piedmont plains in the east are suitable for large-scale population aggregation, industrialization, and urbanization development; and (2) for the six hard-hit counties, Mingshan is the preferred region for large-scale post-earthquake reconstruction due to its high construction index and suitable land per capita, and some plots of land in the valleys could be selected for in-situ small-scale reconstruction in Lushan. The land suitability assessment for post-earthquake reconstruction would be significant to making sound reconstruction planning for achieving sustainable regional development in the Mw 6.6 Lushan earthquake stricken area. This study could be used as a reference for the regions with similar events.

About 80% of global wetland resources are degrading or disappearing; thus the wetland ecosystem has become one of the most seriously threatened ecosystems in the world. As an area sensitive to global changes and acting as a security barrier for the Asian ecosystem, the Tibetan Plateau has about 13.19×10⁴ km² of wetlands of special significance within China. With the increasing application of remote sensing technology to wetland research, Tibetan Plateau wetland research has entered a period of rapid development. This paper summarizes the remote sensing research literature of the Tibetan Plateau wetlands from 1992 to 2014, and is intended to provide references for future research into the wetlands of the Tibetan Plateau. We have reviewed monitoring methods, research topics, and existing problems. Our review has revealed the following characteristics: (1) Over the past 40 years, the research paradigm of the Tibetan Plateau wetlands has undergone dynamic changes in the monitoring of wetland areas, landscape patterns and the eco-environment based on remote sensing technology. Attention has also been focused on constructing models with an ecological system perspective and analyzing three patterns of change trends within the Tibetan Plateau wetlands. (2) The results of Tibetan Plateau wetland research based on remote sensing were as follows: (a) between 1970 and 2006, the Tibetan Plateau wetland area decreased overall at a rate of 0.23%/a, and the landscape diversity declined at a rate of 0.17%/a; (b) by contrast, between 1976 and 2009, the lake area of the inland river basins in the Tibetan Plateau increased at a rate of 0.83%/a; and (c) the change trend in the Tibetan Plateau wetlands was controlled by climate change. Current problems relating to remote sensing (RS)-based research in the Tibetan Plateau wetlands are computer interpretation accuracy and the processing precision of cloud removal, and the lack of a comprehensive overview of the Tibetan Plateau wetland system. Finally, based on the review, some key activities for future study have been proposed, as follows: (1) Strengthening the integration of the Tibetan Plateau wetland research with remote sensing research; (2) discussing the response and adaptation mechanisms of the Tibetan Plateau wetland ecosystem within the context of global change; (3) strengthening the integration of remote sensing (RS), geographic information system (GIS), and global positioning system (GPS), and promoting the construction of a Tibetan Plateau wetland information platform.

The Beautiful China Initiative (BCI) is a plan for the sustainable development of the Chinese nation as well as for China to fulfill the United Nations’ 2030 Agenda for Sustainable Development. The Chinese government’s “five-in-one” approach provides strategic arrangements for developing the BCI, and President Xi Jinping proposed a timetable and “road map” for the BCI at the National Conference on Ecological and Environmental Protection. Nevertheless, the theoretical basis, evaluation index system, evaluation criteria and effectiveness of the BCI are currently unclear. This paper begins by exploring the basic content of the BCI from narrow and broad perspectives. It regards the theory of human-nature harmonious coexistence and the five-in-one beauty theory as the core theoretical bases of the BCI and constructs a five-element BCI evaluation index system (ecological environment, green development, social harmony, system perfection and cultural heritage) and utilizes the assessment method of the United Nations’ Human Development Index to assess scientifically the effectiveness of the BCI in 341 prefecture-level cities. The results show the average BCI index (the Chinese Academy of Sciences Beauty Index) score to be 0.28, which is quite low, while the average scores for the individual element indexes of the ecological environment index, green development index, social harmony index, system perfection index and cultural heritage index are 0.6, 0.22, 0.29, 0.22 and 0.07, respectively. All of these are relatively low values, with relatively large discrepancies in regional development, indicating that progress in the BCI is generally slow and unbalanced. To realize the BCI’s timetable and roadmap to a high quality and high standard, it is suggested that a common system for evaluating the progress of the BCI is developed and promulgated so that dynamic monitoring and phased evaluations can take place; BCI technical assessment standards are compiled and published; BCI comprehensive zoning is undertaken; pilot projects adapted to local conditions are launched in BCI sample areas; and BCI results are incorporated into performance indicators at all levels of government.

To resolve conflicts between development and the preservation of the natural environment, enable economic transformation, and achieve the global sustainable development goals (SDGs), green development (GD) is gradually becoming a major strategy in the construction of an ecological civilization and the ideal of building a “beautiful China”, alongside the transformation and reconstruction of the global economy. Based on a combination of the concept and implications of GD, we first used the Slacks Based Model with undesirable outputs (SBM-Undesirable), the Theil index, and the spatial Markov chain to measure the spatial patterns, regional differences, and spatio-temporal evolution of urban green development efficiency (UGDE) in China from 2005 to 2015. Second, by coupling natural and human factors, the mechanism influencing UGDE was quantitatively investigated under the framework of the human-environment interaction. The results showed that: (1) from 2005 to 2015, the UGDE increased from 0.475 to 0.523, i.e., an overall increase of 10%. In terms of temporal variation, there was a staged increase, with its evolution having the characteristics of a “W-shaped” pattern. (2) The regional differences in UGDE followed a pattern of eastern > central > western. For different types of urban agglomeration, the UGDE had inverted pyramid cluster growth characteristics that followed a pattern of “national level > regional level > local level”, forming a stable hierarchical scale structure of “super cities > mega cities > big cities > medium cities > small cities”. (3) UGDE in China has developed with significant spatial agglomeration characteristics. High-efficiency type cities have positive spillover effects, while low-efficiency cities have negative effects. Different types of urban evolution processes have a path dependence, and a spatial club convergence phenomenon exists, in which areas with high UGDE are concentrated and drive low UGDE elsewhere. (4) Under the framework of regional human-environment interaction, the degree of human and social influence on UGDE is greater than that of the natural background. The economic strength, industrial structure, openness, and climate conditions of China have positively promoted UGDE.

The Chinese government ratified the Paris Climate Agreement in 2016. Accordingly, China aims to reduce carbon dioxide emissions per unit of gross domestic product (carbon intensity) to 60%-65% of 2005 levels by 2030. However, since numerous factors influence carbon intensity in China, it is critical to assess their relative importance to determine the most important factors. As traditional methods are inadequate for identifying key factors from a range of factors acting in concert, machine learning was applied in this study. Specifically, random forest algorithm, which is based on decision tree theory, was employed because it is insensitive to multicollinearity, is robust to missing and unbalanced data, and provides reasonable predictive results. We identified the key factors affecting carbon intensity in China using random forest algorithm and analyzed the evolution in the key factors from 1980 to 2017. The dominant factors affecting carbon intensity in China from 1980 to 1991 included the scale and proportion of energy-intensive industry, the proportion of fossil fuel-based energy, and technological progress. The Chinese economy developed rapidly between 1992 and 2007; during this time, the effects of the proportion of service industry, price of fossil fuel, and traditional residential consumption on carbon intensity increased. Subsequently, the Chinese economy entered a period of structural adjustment after the 2008 global financial crisis; during this period, reductions in emissions and the availability of new energy types began to have effects on carbon intensity, and the importance of residential consumption increased. The results suggest that optimizing the energy and industrial structures, promoting technological advancement, increasing green consumption, and reducing emissions are keys to decreasing carbon intensity within China in the future. These approaches will help achieve the goal of reducing carbon intensity to 60%-65% of the 2005 level by 2030.

Climate change resulting from CO₂ emissions has become an important global environmental issue in recent years. Improving carbon emission performance is one way to reduce carbon emissions. Although carbon emission performance has been discussed at the national and industrial levels, city-level studies are lacking due to the limited availability of statistics on energy consumption. In this study, based on city-level remote sensing data on carbon emissions in China from 1992-2013, we used the slacks-based measure of super-efficiency to evaluate urban carbon emission performance. The traditional Markov probability transfer matrix and spatial Markov probability transfer matrix were constructed to explore the spatiotemporal evolution of urban carbon emission performance in China for the first time and predict long-term trends in carbon emission performance. The results show that urban carbon emission performance in China steadily increased during the study period with some fluctuations. However, the overall level of carbon emission performance remains low, indicating great potential for improvements in energy conservation and emission reduction. The spatial pattern of urban carbon emission performance in China can be described as “high in the south and low in the north,” and significant differences in carbon emission performance were found between cities. The spatial Markov probabilistic transfer matrix results indicate that the transfer of carbon emission performance in Chinese cities is stable, resulting in a “club convergence” phenomenon. Furthermore, neighborhood backgrounds play an important role in the transfer between carbon emission performance types. Based on the prediction of long-term trends in carbon emission performance, carbon emission performance is expected to improve gradually over time. Therefore, China should continue to strengthen research and development aimed at improving urban carbon emission performance and achieving the national energy conservation and emission reduction goals. Meanwhile, neighboring cities with different neighborhood backgrounds should pursue cooperative economic strategies that balance economic growth, energy conservation, and emission reductions to realize low-carbon construction and sustainable development.

Border area is not only an important gateway for inland opening-up, but also an important part of completing the building of a moderately prosperous society and optimizing national urban spatial pattern in China. Due to the location, natural resources endowment, and traffic accessibility, the urbanization speed is relatively slow in border areas. Therefore, it is a special area that needs to pay close attention to, especially under the background of the Belt and Road Initiative and China’s regional coordinated development program. Based on the county-level data from 2000 to 2015, this paper tries to analyze the spatio-temporal pattern of urbanization in 134 border counties, and applies geographical detector method to study the driving forces of urbanization in border areas. Conclusions are as follows: (1) From 2000 to 2015, urbanization rate in border areas has been lower than the national average, and the gap has been widening. Some border counties in southern Xinjiang, Tibet, northeast of Inner Mongolia, and Yunnan, are even facing the problem of population loss. (2) In the same period, urbanization rate in the northwestern and southwestern border is low, while their urbanization rate grows relatively faster comparing with other border counties; urbanization rate in Tibet border is the lowest and grows relatively slowly; urbanization rate in the northeastern and northern border is slightly higher, but it grows slowly or even stagnates. (3) Transportation and industry are the important driving forces of urbanization in border areas, while the driving forces of market is relatively weak. And there are obvious mutual reinforcements among the driving forces, while the effort and explanatory power of resource force increases obviously after interaction. (4) Urbanization rate in the northwestern and southwestern border areas grows relatively fast, with industrial force and transportation force, market force and administrative force as the main driving forces respectively. Tibet border area has the lowest urbanization rate and growth rate, as the driving force of urbanization with strong contribution has not yet formed in Tibet. In the northeastern and northern border areas, the contribution of transportation force to urbanization is greater than other forces, and its interaction with market and industry has obvious effects.

Finding accurate methods for estimating and mapping land prices at the macro-scale based on publicly accessible and low-cost spatial data is an essential step in producing a meaningful reference for regional planners. This asset would assist them in making economically justified decisions in favor of key investors for development projects and post-disaster recovery efforts. Since 2005, the Ministry of Land, Infrastructure, and Transport of Japan has made land price data open to the public in the form of observations at dispersed locations. Although this data is useful, it does not provide complete information at every site for all market participants. Therefore, estimating and mapping land prices based on sound statistical theories is required. This paper presents a comparative study of spatial prediction of land prices in 2015 in Fukushima prefecture based on geostatistical methods and machine learning algorithms. Land use, elevation, and socioeconomic factors, including population density and distance to railway stations, were used for modeling. Results show the superiority of the random forest algorithm. Overall, land prices are distributed unevenly across the prefecture with the most expensive land located in the western region characterized by flat topography and the availability of well-connected and highly dense economic hotspots.

Saltwater intrusion in the estuary area threatens the use of freshwater resources. If river discharge increases to a critical value, then saltwater intrusion frequency and salinity level decreases. In this study, long-term river discharge and tidal range data in the Yangtze River Estuary (YRE) and salinity data obtained in the upper South Branch of the YRE were used to analyze the characteristics of different variables and the basic law of their interactions. Two methods, namely, the material analysis method and empirical models, were applied to determine the critical river discharge for saltwater intrusion control. Results are as follows: (1) the salinity might exceed the drinking water standard of China when the river discharge was less than 30,000 m3/s. Approximately 69% of salinity excessive days occurred when the river discharge was less than 15,000 m3/s; (2) the tidal range in the YRE roughly varied in sinusoidal pattern with a 15-day cycle length. Exponential relationship existed between daily salinity (chlorinity) and daily mean tidal range. Combining these two features with the cumulative frequency statistics of tidal ranges, it was showed that notable saltwater intrusion occurred when the tidal range was more than 2.7 m at Qinglonggang station. Moreover, the critical discharge was found to be slightly higher than 11,000 m3/s; (3) various of empirical models for salinity prediction could be chosen to calculate the critical discharge. The values obtained by different models were in the range of 11,000-12,000 m3/s; (4) the proposed critical discharge to reduce notable saltwater intrusion was 11,500 m3/s. After the Three Gorges Reservoir operation, the minimum river discharge into the YRE in 2008-2017 was below the critical discharge, thereby suggesting an increase in the minimum river discharge by reservoir regulation in drought periods.

Extreme weather is an important noise factor in affecting dynamic access to river morphology information. The response characteristics of river channel on climate disturbances draw us to develop a method to investigate the dynamic evolution of bankfull channel geometries (including the hydraulic geometry variables and bankfull discharges) with stochastic differential equations in this study. Three different forms of random inputs, including single Gaussian white noise and compound Gaussian/Fractional white noise plus Poisson noise, are explored respectively on the basis of the classical deterministic models. The model parameters are consistently estimated by applying a composite nonparametric maximum likelihood estimation (MLE) method. Results of the model application in the Lower Yellow River reveal the potential responses of bankfull channel geometries to climate disturbances in a probabilistic way, and, the calculated average trends mainly run to synchronize with the measured values. Comparisons among the three models confirm the advantage of Fractional jump-diffusion model, and through further discussion, stream power based on such a model is concluded as a better systematic measure of river dynamics. The proposed method helps to offer an effective tool for analyzing fluvial relationships and improves the ability of crisis management of river system under varying environment conditions.

Understanding the interactions between humans and nature in the Anthropocene is central to the quest for both human wellbeing and global sustainability. However, the time-space compression, long range interactions, and reconstruction of socio-economic structures at the global scale all pose great challenges to the traditional analytical frameworks of human-nature systems. In this paper, we extend the connotation of coupled human and natural systems (CHANS) and their four dimensions—space, time, appearance, and organization, and propose a novel framework: “Coupled Human and Natural Cube” (CHNC) to explain the coupling mechanism between humans and the natural environment. Our proposition is inspired by theories based on the human-earth areal system, telecoupling framework, planetary urbanization, and perspectives from complexity science. We systematically introduce the concept, connotation, evolution rules, and analytical dimensions of the CHNC. Notably there exist various “coupling lines” in the CHNC, connecting different systems and elements at multiple scales and forming a large, nested, interconnected, organic system. The rotation of the CHNC represents spatiotemporal nonlinear fluctuations in CHANS in different regions. As a system continually exchanges energy with the environment, a critical phase transition occurs when fluctuations reach a certain threshold, leading to emergent behavior of the system. The CHNC has four dimensions—pericoupling and telecoupling, syncoupling and lagcoupling, apparent coupling and hidden coupling, and intra-organization coupling and inter-organizational coupling. We mainly focus on the theoretical connotation, research methods, and typical cases of telecoupling, lagcoupling, hidden coupling, and inter-organizational coupling, and put forward a human-nature coupling matrix to integrate multiple dimensions. In summary, the CHNC provides a more comprehensive and systematic research paradigm for understanding the evolution and coupling mechanism of the human-nature system, which expands the analytical dimension of CHANS. The CHNC also provides a theoretical support for formulating regional, sustainable development policies for human wellbeing.

To clarify the impact of non-agricultural employment on rural land circulation in China, we built logit models using the Chinese Household Income Project 2013 dataset, which includes 18,948 household samples over 15 provinces, 126 cities and 234 counties of China in 2013. We use the proportion of non-agricultural income, the proportion of non-agricultural laborers and non-agricultural fixed operating assets to reflect the degree of the households’ dependence on agriculture, the degree of the households’ laborers committed to non-agricultural employment and the stability of non-agricultural employment, respectively. The results show that the stability of non-agricultural employment is an important reason for farmers to transfer out their land, and an increase in non-agricultural income is the fundamental reason. The proportion of non-agricultural assets has the greatest impact on the decision to transfer land, followed by the proportion of non-agricultural income. Per unit increase in the non-agricultural income ratio has a stronger effect on the transfer-out decision than it does on the transfer-in decision, which is a 0.09 increase of the probability of transfer-out the land and a 0.07 decrease of the probability of transfer-in the land. In terms of regional differences, when considering the impact of non-agricultural employment on the land transfer-out decision, the impacts of non-agricultural income and labor force are the greatest in the Central region. The impact of non-agricultural assets is the greatest in the Eastern region. For the Eastern region, the decision to transfer out land is mainly affected by non-agricultural assets and the non-agricultural labor force, and the decision to transfer in land is mainly affected by non-agricultural assets. In the Central and Western regions, the decision to transfer out land is mainly affected by non-agricultural assets, non-agricultural income and the non-agricultural labor force, in that order. The decision to transfer in land in the Central region is not significantly affected by non-agricultural employment. The decision to transfer in land in the Western region is mainly affected by non-agricultural assets, non-agricultural labor force and non-agricultural income, in that order. We note that non-agricultural assets have a prominent impact on land transfer, which shows that the stability of non-agricultural employment has an important impact on land transfer decision-making. Vocational training for rural labor forces may be an effective means to promote stable non-agricultural employment and simultaneously facilitate rural land circulation, especially in Central and Western China.

Based on the comprehensive analyses of 18 core profiles’ sedimentary sequences and lithological characteristics in Jianghan-Dongting Basin of the middle reaches of the Yangtze River and the spatial-temporal distribution of archeological sites in this area, we reconstructed the Holocene hydro-environmental evolution, and its relationship with human occupation. The comparison reveals: 11.5-5.5 ka BP, the water level of rivers and lakes in the middle Yangtze River appeared a rising trend, concurrently, under the development of Neolithic culture and rice agricultural activities, human occupation extended from piedmont plain to inner basin plain in the study area. The water level fell in 5.5-4.0 ka BP, meanwhile, the number of human settlements of Qujialing-Shijiahe culture rapidly increased, especially in the inner basin plain. The water level rose again around 4.0 ka BP, floods spread massively in this period, which led to the decline of Shijiahe culture. The main causes for hydro-environmental evolution in the study area are the fluctuation of sea level and the aggradation of fluvio-lacustrine sediments.

Based on the measured discharge, sediment load, and cross-sectional data from 1986 to 2015 for the lower Yellow River, changes in the morphological parameters (width, depth, and cross-sectional geomorphic coef?cient) of the main channel are analyzed in this paper. The results show that before the operation of the Xiaolangdi Reservoir (XLDR) from 1986 to 1999, the main channel shrunk continually, with decreasing width and depth. The rate of reduction in its width decreased along the river whereas that of depth increased in the downstream direction. Because the rate of decrease in the width of the main channel was greater than that in channel depth, the cross-sectional geomorphic coef?cient decreased in the sub-reach above Gaocun. By contrast, for the sub-reach below Gaocun, the rate of decrease in channel width was smaller than that in channel depth, and the cross-sectional geomorphic coef?cient increased. Once the XLDR had begun operation, the main channel eroded continually, and both its width and depth increased from 2000 to 2015. The rate of increase in channel width decreased in the longitudinal direction, and the depth of the main channel in all sub-reaches increased by more than 2 m. Because the rate of increase in the depth of the main channel was clearly larger than that of its width, the cross-sectional geomorphic coef?cient decreased in all sub-reaches. The cross-sectional geometry of the main-channel of the lower Yellow River exhibited different adjustment patterns before and after the XLDR began operation. Before its operation, the main channel mainly narrowed in the transverse direction and silted in the vertical direction in the sub-reach above Aishan; in the sub-reach below Aishan, it primarily silted in the vertical direction. After the XLDR began operation, the main channel adjusted by widening in the transverse direction and deepening in the vertical direction in the sub-reach above Aishan; in the sub-reach below it, the main channel adjusted mainly by deepening in the vertical direction. Compared with the rates of decrease in the width and depth of the main channel during the siltation period, the rate of increase in channel width during the scouring period was clearly smaller while the rate of increase in channel depth was larger. After continual siltation and scouring from 1986 to 2015, the cross-sectional geometry of the main-channel changed from wide and shallow to relatively narrow and deep. The pattern of adjustment in the main channel was closely related to the water and sediment conditions. For the braided reach, the cross-sectional geomorphic coef?cient was negatively correlated with discharge and positively correlated with suspended sediment concentration (SSC) during the siltation period. By contrast, the cross-sectional geomorphic coef?cient was positively correlated with discharge and negatively correlated with SSC during the scouring period. For the transitional and meandering reaches, the cross-sectional geomorphic coef?cient was negatively correlated with discharge and positively correlated with SSC.

Since the reform and opening-up policy launched in 1978, the number of inbound tourists increased from 1.8 million in 1978 to 139.5 million in 2017, and that of domestic tourists increased from 344 million in 1991 to 5 billion in 2017. This article conducts research on how the geographical pattern of China’s tourism has evolved in the last four decades on the national-scale and regional-scale, for rare studies before could focus on such an extended date and utilize inbound and domestic tourism data simultaneously. Grounded on viable datasets and multiple vibrant data analysis approaches (including the Gini coefficient, primacy index analysis, hot spot analysis and Pearson correlation analysis), this article unpacks triple vital realities. (1) The overall geographical pattern of China’s tourism development can arguably summarize as “high in the eastern and low in the western part, high in the southern and low in the northern part.” Meanwhile, China’s inbound tourism has long shown a pattern of polarized distribution; While, domestic tourism has experienced a shift from the polarized distribution to the equilibrium distribution. (2) According to the features and characteristics, China's tourism development can be divided into four stages. They are precisely the initial modern tourism stage (1978-1988), the domestic tourism cultivating stage (1989-1996), the rapid development stage (1997-2007) and the new normal stage (2008-present). (3) This article also identified multiple factors underlying the inbound and domestic tourism development in China, including policies, management systems, tourism demand, tourist attractions, economic level, consumption level, industrial development, investment status, traffic conditions, accommodation services, intermediary services and degree of openness.

Based on the NOAA AVHRR-NDVI monthly data from 1981 to 2001, the spatial distribution and dynamic change of land cover along the Qinghai-Tibet Highway and Railway were studied. The results of the analytical data indicate that the NDVI values in July, August and September are rather high during a year, and a linear trend by calculating NDVI of each pixel computed based on the average values of NDVI in July, August and September were obtained. The results are as follows: 1) Land cover of the study area by NDVI displays high at two sides of the area and low in the center, and agriculture area > alpine meadow > alpine grassland > desert grassland. 2) In the study area, the amount of pixels with high increase, slight increase, no change, slight decrease and high decrease account for 0.29%, 14.86%, 67.61%, 16.7% and 0.57% of the whole area, respectively. The increase of land cover pixels is mainly in the agriculture and alpine meadow and the decrease pixels mainly in the alpine grassland, desert grassland and hungriness. Grassland and hungriness contribute to the decrease mostly and artificial land and meadow contribute to the increase mostly. 3) In the area where human beings live, the changing trend is obvious, such as the valleys of Lhasa River and Huangshui River and area along the Yellow River; in the high altitude area with fewer people living, the changing trend is relatively low, like the area of Hoh Xil. 4) Human being’s behaviors are a key factor followed by the climate changes affecting land cover.