Land use/cover change is an important parameter in the climate and ecological simulations. Although they had been widely used in the community, SAGE dataset and HYDE dataset, the two representative global historical land use datasets, were little assessed about their accuracies in regional scale. Here, we carried out some assessments for the traditional cultivated region of China (TCRC) over last 300 years, by comparing SAGE2010 and HYDE (v3.1) with Chinese Historical Cropland Dataset (CHCD). The comparisons were performed at three spatial scales: entire study area, provincial area and 60 km by 60 km grid cell. The results show that (1) the cropland area from SAGE2010 was much more than that from CHCD; moreover, the growth at a rate of 0.51% from 1700 to 1950 and -0.34% after 1950 were also inconsistent with that from CHCD. (2) HYDE dataset (v3.1) was closer to CHCD dataset than SAGE dataset on entire study area. However, the large biases could be detected at provincial scale and 60 km by 60 km grid cell scale. The percent of grid cells having biases greater than 70% (<-70% or >70%) and 90% (<-90% or >90%) accounted for 56%-63% and 40%-45% of the total grid cells respectively while those having biases range from -10% to 10% and from -30% to 30% account for only 5%-6% and 17% of the total grid cells respectively. (3) Using local historical archives to reconstruct historical dataset with high accuracy would be a valuable way to improve the accuracy of climate and ecological simulation.

Understanding the Changing Planet: Strategic Directions for the Geographical Sciences (UCP), published by the National Research Council (USA), and its comments in The Professional Geographer propose that uppercase and plural "Geographical Sciences" (GS) is the strategic direction for geography in the next decade for better understanding of our rapidly changing planet. According to these comments, UCP valued technologies and tools excessively ("task"), and did not pay much attention to methodology ("discipline"). Actually, both "task" and "discipline" are geographical wings, especially in the time of "big science". Enlightenment from UCP and its comments is the strategic direction that should be balanced between "task" and "discipline", GS should be a three-dimensional construct of a disciplinary system, methodology, and technologies and tools, and this system should be scientific humanism based on scientific spirit and directed by humanism. During the last 60 years, Chinese geographers devoted themselves to GS, including practice and theory. Obviously progress and outlook are proposed as interdisciplinary GS, Earth Surface Sciences (ESS) and Geographical Construction (GC). The disciplinary system of GS is very complex, and is composed of such human knowledge domains as sciences, technologies, engineering, and philosophy. The main mission is to research the open, complex, and macro earth system (not only scientifically, but also humanistically), and one significant methodology is "comprehensive integration of qualitative and quantitative means" (CIQQM). At the same time, another changing direction in Chinese geography is Human-Economic Geography (HEG).

Rubber plantation is the major land use type in Southeast Asia. Monitoring the spatial-temporal pattern of rubber plantation is significant for regional land resource development, eco-environmental protection, and maintaining border security. With remote sensing technologies, we analyzed the rubber distribution pattern and spatial-temporal dynamic; with GIS and a newly proposed index of Planted Intensity (PI), we further quantified the impacts and limits of topographical factors on rubber plantation in the border region of China, Laos and Myanmar (BRCLM) between 1980 and 2010. The results showed that: (1) As the dominant land use type in this border region, the acreage of rubber plantation was 6014 km² in 2010, accounting for 8.17% of the total area. Viewing from the rubber plantation structure, the ratio of mature- (≥10 year) and young rubber plantation (<10 year) was 5:7. (2) From 1980 to 2010, rubber plantation expanded significantly in BRCLM, from 705 km² to 6014 km², nearly nine times. The distribution characteristics of rubber plantation varied from concentrated toward dispersed, from border inside to outside, and expanded further in all directions with Jinghong City as the center. (3) Restricted by the topographical factors, more than 4/5 proportion of rubber plantation concentrated in the appropriate elevation gradients between 600 and 1000 m, rarely occurred in elevations beyond 1200 m in BRCLM. Nearly 2/3 of rubber plantation concentrated on slopes of 8°-25°, rarely distributed on slopes above 35°. Rubber plantation was primarily distributed in south and east aspects, relatively few in north and west aspects. Rubber planted intensity displayed the similar distribution trend. (4) Comparative studies of rubber plantation in different countries showed that there was a remarkable increase in area at higher elevations and steeper slopes in China, while there were large appropriate topographical gradients for rubber plantation in Laos and Myanmar which benefited China for rubber trans-boundary expansion. (5) Rubber plantation in BRCLM will definitely expend cross borders of China to the territories of Laos and Myanmar, and the continuous expansion in the border region of China will be inevitable.

The precipitation regime of the low latitude highlands of Yunnan in Southwest China is subject to the interactions between the East Asian Summer Monsoon and the Indian Summer Monsoon, and the influence of surface orography. An understanding of changes in its spatial and temporal patterns is urgently needed for climate change projection, hydrological impact modelling, and regional and downstream water resources management. Using daily precipitation records of the low latitude highlands over the last several decades (1950s-2007), a time series of precipitation indices, including annual precipitation, number of rainy days, mean annual precipitation intensity, the dates of the onset of the rainy season, degree and period of precipitation seasonal concentration, the highest 1-day, 3-day and 7-day precipitation, and precipitation amount and number of rainy days for precipitation above different intensities (such as ≥10 mm, ≥25 mm and ≥50 mm of daily precipitation), was constructed. The Trend-Free Pre-Whitening Mann-Kendall trend test was then used to detect trends of the time series data. The results show that there is no significant trend in annual precipitation and strong seasonal differentiation of precipitation trends across the low latitude highlands. Springs and winters are getting wetter and summers are getting drier. Autumns are getting drier in the east and wetter in the west. As a consequence, the seasonality of precipitation is weakening slightly. The beginning of the rainy season and the period of the highest precipitation tend to be earlier. In the meantime, the low latitude highlands has also witnessed less rainy days, more intense precipitation, slightly longer moderate and heavy precipitation events, and more frequent extreme precipitation events. Additionally, regional differentiation of precipitation trends is remarkable. These variations may be associated with weakening of the East Asian summer monsoon and strengthening of the South Asian summer monsoon, as well as the "corridor-barrier" effects of special mountainous terrain. However, the physical mechanisms involved still need to be uncovered in the future.

Snow disaster is one of the top ten natural disasters worldwide, and the most severe natural disaster to affect the pastoral areas of the Qinghai-Tibet Plateau. Based on the hazard harmfulness data collected from historical records and data collected from entities affected by this hazard in 2010, a comprehensive analysis of the 18 indexes of snow disaster on the Qinghai-Tibet Plateau was conducted, encompassing the hazard harmfulness, the amount of physical exposure the hazard-bearing entities face, the sensitivity to the hazard, and the capacity to respond to the disaster. The analysis indicates that: (1) areas at high-risk of snow disaster on the Qinghai-Tibet Plateau are located in certain areas of the counties of Yecheng and Pishan in the Xinjiang region; (2) areas at medium-risk of snow disaster are found between the Gangdise Mountains and the Himalayas in the central-western part of the Qinghai-Tibet Plateau, and the southeastern part of the southern Qinghai Plateau; (3) the risk of snow disaster is generally low throughout the large area to the south of 30°N and the region on the border of the eastern Qinghai-Tibet Plateau. Overall, the risk of snow disaster in high-altitude areas of the central Qinghai-Tibet Plateau is higher than that at the edge of the plateau.

The catchment of South Luohe River in Central China is an important region for investigating modern pollen-environment relationship, because it is located in the transitional zone between south and north China, an environment which is sensitive to climate changes. In this study, 40 surface samples under ten vegetation types were collected to reveal the relationship between pollen assemblages and vegetation. The results show that the surface pollen assemblages reflect the vegetation quite well. In forest topsoils, the average of arboreal pollen content is greater than 40%, and the Selaginella sinensis spore is high. As to sparse forest grassland and shrub community, the average arboreal pollen is 13.2% and 16.6% respectively, and the shrub pollen is relatively higher than that of grassland samples. The grassland and farmland are characterized by low percentage of tree and shrub pollen (<10% and <1%), and high percentage of herbs (>80%). Pinus, Quercus and some other arboreal pollen can indicate the regional vegetation because of their dispersal ability. Quercus pollen is under-representative and so is Pinus. Artemisia pollen is significantly over-represented, has poor correlation with the plant coverage, and may reflect human disturbance. Gramineae can indicate plant quite well, but with low representation. High content of Chenopodiaceae probably suggests human impact. Predominant Selaginella sinensis can be used as an indicator of forest environment. Cluster analysis and principal components analysis of pollen assemblages can distinguish forest and non-forest vegetation well. The former method is better at separating pine and mixed forests, while the latter is more stable and could better differentiate farmland and other non-forest area. The first axis of PCA mainly reflects the humidity.

Based on daily maximum and minimum temperature observed by the China Meteorological Administration at 115 meteorological stations in the Yangtze River Basin from 1962 to 2011, the methods of linear regression, principal component analysis and correlation analysis are employed to investigate the temporal variability and spatial distribution of temperature extremes. Sixteen indices of extreme temperature are selected. The results are as follows: (1) The occurrence of cold days, cold nights, ice days, frost days and cold spell duration indicator has significantly decreased by -0.84, -2.78, -0.48, -3.29 and -0.67 days per decade, respectively. While the occurrence of warm days, warm nights, summer days, tropical nights, warm spell duration indicator and growing season length shows statistically significant increasing trends at rates of 2.24, 2.86, 2.93, 1.80, 0.83 and 2.30 days per decade, respectively. The tendency rate of the coldest day, coldest night, warmest day, warmest night and diurnal temperature range is 0.33, 0.47, 0.16, 0.19 and -0.07℃ per decade, respectively. (2) The magnitudes of changes in cold indices (cold nights, coldest day and coldest night) are obviously greater than those of warm indices (warm nights, warmest day and warmest night). The change ranges of night indices (warm nights and cold nights) are larger than those of day indices (warm days and cold days), which indicates that the change of day and night temperature is asymmetrical. (3) Spatially, the regionally averaged values of cold indices in the upper reaches of the Yangtze River Basin are larger than those in the middle and lower reaches. However, the regionally averaged values of most warm indices (except warm spell duration indicator) and growing season length in the middle and lower reaches are larger than those in the upper reaches. (4) The extreme temperature indices are well correlated with each other except diurnal temperature range.

The implementation of new type industrialization and urbanization and agricultural modernization strategies lacks of a major hand grip and spatial supporting platform,due to long-term existed "dual-track" structure of rural-urban development in China as well as unstable rural development institution and mechanism. It is necessary to restructure rural production,living and ecological space by carrying out land consolidation,so as to establish a new platform for building new countryside and realizing urban-rural integration development in China. This paper develops the concept and connotation of rural spatial restructuring. Basing on the effects analysis of industrialization and urbanization on rural production,living and ecological space,the mechanism of pushing forward rural spatial restructuring by carrying out land consolidation is probed. A conceptualization of the models of rural production,living and ecological spatial restructuring is analyzed combining with agricultural land consolidation,hollowed villages consolidation and industrial and mining land consolidation. Finally,the author argues that a "bottom-up" restructuring strategy accompanied by a few "top-down" elements is helpful for smoothly pushing forward rural spatial restructuring in China. In addition,the optimization and restructuring of rural production,living and ecological space will rely on the innovations of regional engineering technology,policy and mechanism,and mode of rural land consolidation,and more attentions should be paid to rural space,the foundation base and platform for realizing urban-rural integration development.

Land-use/land-cover changes (LUCCs) have links to both human and nature interactions. China's Land-Use/cover Datasets (CLUDs) were updated regularly at 5-year intervals from the late 1980s to 2010,with standard procedures based on Landsat TM\ETM+ images. A land-use dynamic regionalization method was proposed to analyze major land-use conversions. The spatiotemporal characteristics,differences,and causes of land-use changes at a national scale were then examined. The main findings are summarized as follows. Land-use changes (LUCs) across China indicated a significant variation in spatial and temporal characteristics in the last 20 years (1990-2010). The area of cropland change decreased in the south and increased in the north,but the total area remained almost unchanged. The reclaimed cropland was shifted from the northeast to the northwest. The built-up lands expanded rapidly,were mainly distributed in the east,and gradually spread out to central and western China. Woodland decreased first,and then increased,but desert area was the opposite. Grassland continued decreasing. Different spatial patterns of LUC in China were found between the late 20th century and the early 21st century. The original 13 LUC zones were replaced by 15 units with changes of boundaries in some zones. The main spatial characteristics of these changes included (1) an accelerated expansion of built-up land in the Huang-Huai-Hai region,the southeastern coastal areas,the midstream area of the Yangtze River,and the Sichuan Basin;(2) shifted land reclamation in the north from northeast China and eastern Inner Mongolia to the oasis agricultural areas in northwest China;(3) continuous transformation from rain-fed farmlands in northeast China to paddy fields;and (4) effectiveness of the "Grain for Green" project in the southern agricultural-pastoral ecotones of Inner Mongolia,the Loess Plateau,and southwestern mountainous areas. In the last two decades,although climate change in the north affected the change in cropland,policy regulation and economic driving forces were still the primary causes of LUC across China. During the first decade of the 21st century,the anthropogenic factors that drove variations in land-use patterns have shifted the emphasis from one-way land development to both development and conservation.The "dynamic regionalization method" was used to analyze changes in the spatial patterns of zoning boundaries,the internal characteristics of zones,and the growth and decrease of units. The results revealed "the pattern of the change process," namely the process of LUC and regional differences in characteristics at different stages. The growth and decrease of zones during this dynamic LUC zoning,variations in unit boundaries,and the characteristics of change intensities between the former and latter decades were examined. The patterns of alternative transformation between the "pattern" and "process" of land use and the causes for changes in different types and different regions of land use were explored.

Based on the GIMMS AVHRR NDVI data (8 km spatial resolution) for 1982-2000,the SPOT VEGETATION NDVI data (1 km spatial resolution) for 1998-2009,and observational plant biomass data,the CASA model was used to model changes in alpine grassland net primary production (NPP) on the Tibetan Plateau (TP). This study will help to evaluate the health conditions of the alpine grassland ecosystem,and is of great importance to the promotion of sustainable development of plateau pasture and to the understanding of the function of the national ecological security shelter on the TP. The spatio-temporal characteristics of NPP change were investigated using spatial statistical analysis,separately on the basis of physico-geographical factors (natural zone,altitude,latitude and longitude),river basin,and county-level administrative area. Data processing was carried out using an ENVI 4.8 platform,while an ArcGIS 9.3 and ANUSPLIN platform was used to conduct the spatial analysis and mapping. The primary results are as follows:(1) The NPP of alpine grassland on the TP gradually decreases from the southeast to the northwest,which corresponds to gradients in precipitation and temperature. From 1982 to 2009,the average annual total NPP in the TP alpine grassland was 177.2×10¹² gC yr^-1(yr represents year),while the average annual NPP was 120.8 gC m^-2 yr^-1. (2) The annual NPP in alpine grassland on the TP fluctuates from year to year but shows an overall positive trend ranging from 114.7 gC m^-2 yr^-1 in 1982 to 129.9 gC m^-2 yr^-1 in 2009,with an overall increase of 13.3%;32.56% of the total alpine grassland on the TP showed a significant increase in NPP,while only 5.55% showed a significant decrease over this 28-year period. (3) Spatio-temporal characteristics are an important control on annual NPP in alpine grassland:a) NPP increased in most of the natural zones on the TP,only showing a slight decrease in the Ngari montane desert-steppe and desert zone. The positive trend in NPP in the high-cold shrub-meadow zone,high-cold meadow steppe zone and high-cold steppe zone is more significant than that of the high-cold desert zone;b) with increasing altitude,the percentage area with a positive trend in annual NPP follows a trend of "increasing-stable-decreasing",while the percentage area with a negative trend in annual NPP follows a trend of "decreasing-stable-increasing",with increasing altitude;c) the variation in annual NPP with latitude and longitude co-varies with the vegetation distribution;d) the variation in annual NPP within the major river basins has a generally positive trend,of which the growth in NPP in the Yellow River Basin is most significant. Results show that,based on changes in NPP trends,vegetation coverage and phonological phenomenon with time,NPP has been declining in certain places successively,while the overall health of the alpine grassland on the TP is improving.

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.

The concept of ‘Beautiful China’ is a new goal of ecological construction in the new era of socialism and aims to meet the needs of people as they strive for a better life. National land spatial planning is one major component of the Chinese state’s overall planning for various spatial types. The concept of ‘Beautiful China’ is thus a leading goal of Chinese development in the second centenary. The background of this concept aims for ‘ecological beauty’ as well as the combined beauty of ‘economy-politics-culture-society-ecology.’ The construction of ‘Beautiful China’ therefore necessitates a differentiated evaluation index system that is built on the basis of local conditions. This concept is intimately related to land spatial planning and the idea of Beautiful China guides an important direction for this planning which itself provides an important mechanism and spatial guarantee for construction. The establishment of land spatial planning nevertheless needs to strengthen further discussion of the regional system of human-land relationship, point axis system, main functional division, sustainable development, resources and environmental carrying capacity as well as new urbanization, and the rural multi-system. The aim of this paper is to summarize current thinking in land spatial planning, scientifically analyze the natural geographical conditions, the socioeconomic development, the interrelationship of the land space, plan the goal, vision and path of land space, encourage the public to participate in and carry out dynamic evaluation, build an intelligent system platform for land and spatial planning to realize the goal of ‘Beautiful China’ from a geographical perspective. And they can also present key ideas relating to the compilation and implementation of land spatial planning.

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.

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.

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.

Climate change will bring huge risks to human society and the economy. Regional climate change risk assessment is an important basic analysis for addressing climate change, which can be expressed as a regional system of comprehensive climate change risk. This study establishes regional systems of climate change risks under the proposed global warming targets. Results of this work are spatial patterns of climate change risks in China, indicated by the degree of climate change and the status of the risk receptors. Therefore, the risks show significant spatial differences. The high-risk regions are mainly distributed in East, South, and central China, while the medium-high risk regions are found in North and southwestern China. Under the 2°C warming target, more than 1/4 of China’s area would be at high and medium-high risk, which is more severe than under the 1.5°C warming target, and would extend to the western and northern regions. This work provides regional risk characteristics of climate change under different global warming targets as a foundation for dealing with climate change.

Climate change is expected to introduce more water demand in the face of diminishing water supplies, intensifying the degree of aridity observed in terrestrial ecosystems in the 21st century. This study investigated spatiotemporal variability within global aridity index (AI) values from 1970-2018. The results revealed an overall drying trend (0.0016 yr^-1, p<0.01), with humid and semi-humid regions experiencing more significant drying than other regions, including those classified as arid or semi-arid. In addition, the Qinghai-Tibet Plateau has gotten wetter, largely due to the increases in precipitation (PPT) observed in that region. Global drying is driven primarily by decreasing and increasing PPT and potential evapotranspiration (PET), respectively. Decreases in PPT alone or increases in PET also drive global aridification, though to a lesser extent. PPT and increasing potential evapotranspiration (PET), with increasing PET alone or decreasing PPT alone. Slightly less than half of the world’s land area has exhibited a wetting trend, largely owing to increases in regional PPT. In some parts of the world, the combined effects of increased PPT and decreased PET drives wetting, with decreases in PET alone explaining wetting in others. These results indicate that, without consideration of other factors (e.g., CO₂ fertilization), aridity may continue to intensify, especially in humid regions.

Phenology is an important indicator of climate change. Studying spatiotemporal variations in remote sensing phenology of vegetation can provide a basis for further analysis of global climate change. Based on time series data of MODIS-NDVI from 2000 to 2017, we extracted and analyzed four remote sensing phenological parameters of vegetation, including the Start of Season (SOS), the End of Season (EOS), the Middle of Season (MOS) and the Length of Season (LOS), in tundra-taiga transitional zone in the East Siberia, using asymmetric Gaussian function and dynamic threshold methods. Meanwhile, we analyzed the responses of the four phenological parameters to the temperature change based on the temperature change data from Climate Research Unit (CRU). The results show that: in regions south of 64°N, with the rise of temperature in April and May, the SOS in the corresponding area was 5-15 days ahead of schedule; in the area between 64°N and 72°N, with the rise of temperature in May and June, the SOS in the corresponding area was 10-25 days ahead of schedule; in the northernmost of the study area on the coast of the Arctic Ocean, with the drop of temperature in May and June, the SOS in the corresponding area was 15-25 days behind schedule; in the northwest of the study area in August and the southwest in September, with the drop of temperature, the EOS in the corresponding areas was 15-30 days ahead of schedule; in regions south of 67°N, with the rise of temperature in September and October, the EOS in the corresponding area was 5-30 days behind schedule; the change of the EOS in autumn was more sensitive to the change of the SOS in spring, because the smaller temperature fluctuation can cause the larger change of the EOS; the growth season of vegetation in the study area was generally moving forward, and the LOS in the northwest was shortened, while the LOS in the middle and south of the study area was prolonged.

Vegetation change is of significant concern because it plays a crucial role in the global carbon cycle and climate. Many studies have examined recent changes in vegetation growth and the associated drivers. These drivers include both natural and human activities, but few studies have identified the regulation factors. By employing normalized difference vegetation index (NDVI) data, we analyzed the spatiotemporal pattern of vegetation change in China and then explored the driving factors. It was found that the overall greening of China has improved significantly, especially in the Loess Plateau and southwest China. The Yangtze River Delta and Bohai Rim, however, have not seen as much growth. Natural conditions are conducive to vegetation growth. Although socioeconomic development will be more beneficial for vegetation restoration, the current level and speed of development have a negative effect on vegetation. The regulation factors are considered separately since they affect both directly and indirectly. Regulation factors have accelerated vegetation growth. By understanding the factors affecting the current vegetation growth, we can provide a guide for future vegetation recovery in China and other similar countries.

Land degradation affects extensive drylands around the world. Due to long-term misuse, the Israeli Sde Zin dryland site has faced severe degradation. The study objective was to assess the feasibility of passive restoration in recovering the site. The study was conducted in four land-units along a preservation-degradation continuum: (1) an area that has not faced anthropogenic disturbances (Ecological land); (2) an area that was proclaimed as a national park in the 1970s (Rehabilitation); (3) an area that was prone, until recently, to moderate anthropogenic pressures (Triangle); and (4) a dirt road that was subjected to long-term off-road traffic (Dirtroad). Soil was sampled and analyzed for its properties. The soil physical quality followed the trend of Ecological land > Rehabilitation > Triangle > Dirtroad. Specifically, high soil salinity in the latter three land-units is attributed to long-term erosional processes that exposed the underlying salic horizons. Herbaceous and shrubby vegetation cover was also monitored. The herbaceous vegetation cover followed the trend of Ecological land (86.4%) > Rehabilitation (40.3%) > Triangle (26.2%) > Dirtroad (2.1%), while the shrubby cover was 2.8% in the Ecological land-unit, and practically zero in the other land-units. It seems that despite the effectiveness of passive restoration in recovering the soil’s physical properties, the recovery of vegetation is limited by the severe soil salinity.

Given the importance of waterway depths in river development, the effects of the evolution of bars and troughs on waterway expansion play an important role in river management and water depth conservation. This study aims to expand the waterway dimensions of the Jingjiang Reach of the Yangtze River. To achieve this objective, determining the relationship between river evolution processes and the potential for waterway depth improvement and navigation hindrances is vital. Therefore, the sedimentation, hydrological, and terrain data of the Jingjiang Reach from 1955 to 2020 are analysed to elucidate the above-mentioned relationship. Since the commissioning of the Three Gorges Dam, the scouring of the low-flow channel has accounted for 90%-95% of all scouring in the Jingjiang Reach. Furthermore, the central bars and beaches have shrunk by 9.4% and 24.9%, respectively, and 18.3% overall. Considering the bed scouring and waterway regulation projects in the Jingjiang Reach, we investigated the continuity of a 4.5 m × 200 m × 1050 m (depth × width × bend radius) waterway along the Jingjiang Reach, and find that navigation-hindering channels account for over 5.3% of the waterway length. Furthermore, part of the Jingjiang Reach is an important nature reserve and shelters numerous water-related facilities, which inhibits the implementation of waterway deepening projects. The findings of this study demonstrate that numerous challenges are associated with increasing the waterway depths of the Jingjiang Reach.

Delayed response behaviour commonly occurs in conjunction with changes in riverbed scouring and sediment deposition and is a key component in understanding the intrinsic behaviour of reservoir siltation. Due to the complexity of the riverbed siltation process, the variability in the factors that influence siltation and the limitations of available research methods, the understanding of the delayed response behaviour of the sedimentation process in the Three Gorges Reservoir (TGR) is currently merely qualitative, and there is a lack of quantitative in-depth understanding. In addition, the effects of changes in water and sediment conditions on sedimentation in the TGR before and after cascade reservoir impoundment have not been quantified, so further studies are needed to provide a reference for better understanding the intrinsic behaviour of sedimentation in the TGR and the implications for the long-term use of the reservoir. Based on measured water and sediment data from 2003 to 2020 and topographic data from 2003 to 2018, a delayed response model for sedimentation in the TGR is constructed and combined with theoretical derivation to analyse the changes in the delayed response behaviour of the TGR before and after the impoundment of the cascade reservoirs and the associated causes. Then, the influence of changes in water and sediment conditions in previous years on sedimentation in the reservoir area is determined. The results show that (1) the improved delayed response model of sedimentation, which considers variations in external water and sediment conditions, reservoir scheduling, and riverbed adjustment rates, can effectively reflect the sedimentation process in the TGR, especially after the impoundment of the cascade reservoirs. Additionally, the typical section elevation delayed response model can simulate the section elevation adjustment process. (2) After the impoundment of the cascade reservoirs, the decreased variation in incoming water and sediment and more concentrated incoming sediment in the flood season increased the adjustment rate of the riverbed, and the delayed response time of TGR sedimentation was shortened from the previous 5 years to the previous 3 years. The impact of the previous water and sediment conditions is not negligible for the sedimentation process in the TGR, and the cumulative proportion of the previous influence reaches more than 60%. (3) The influence of incoming sediment on the sedimentation process and typical section adjustment process in the reservoir area increased after the impoundment of the cascade reservoirs, and the influence of the water level in front of the dam on sedimentation remained the largest.

Studies investigating innovation networks shaped by large innovative enterprises (LI-ENTs), which play a very important role in intercity diffusion of technology and knowledge, are rather thin on the ground. Using location information of LI-ENTs in China, we performed a headquarter-branch analysis to generate intercity innovation linkages and analyzed the patterns and dynamics of the generated network of knowledge diffusion. Although the network covers 353 cities across China, its spatial distribution is extremely uneven, with a few cities and city-dyads dominating the structure of the network. Furthermore, intercity linkages of innovation within and of urban agglomerations, as well as their central cities, stand out. With regard to network dynamics, the economic development level, innovation ability, and administrative level of cities, as well as the geographical, institutional, and technological proximity between cities are all found to have a positive impact on intercity linkages of innovations, whilst the impact of FDI on the national distribution of Chinese innovative enterprises is negative. Most importantly, the status of cities within the urban agglomeration exerts a significant positive effect in relation to the innovative enterprises’ expansions, which reflects that the top-down forces of government and the bottom-up forces of market function together.