There is a lack of simple ways to predict the vegetation responses to the East Asian Monsoon (EAM) variability in China due to the complexity of the monsoon system. In this study, we found the variation of the Western Pacific Subtropical High (WPSH), which is one of the major components of the EAM, has a profound influence on the vegetation growth in China. When the WPSH is located more to the west of its climate average, the eastern and northwestern parts experience increased yearly-averaged normalized difference vegetation index (NDVI) and gross primary productivity (GPP) by 0.3%-2.2%, and 0.2%-2.2%, respectively. In contrast, when the WPSH is located more to the east of its climate average, the above areas experience decreased yearly-averaged NDVI and GPP by 0.4% to 1.6%, and 1.3% to 4.5%, respectively. The WPSH serves as a major circulation index to predict the response of vegetation to monsoon.

Soil humic carbon is an important component of soil organic carbon (SOC) in terrestrial ecosystems. However, no study to date has investigated its geographical patterns and the main factors that influence it at a large scale, despite the fact that it is critical for exploring the influence of climate change on soil C storage and turnover. We measured levels of SOC, humic acid carbon (HAC), fulvic acid carbon (FAC), humin carbon (HUC), and extractable humus carbon (HEC) in the 0-10 cm soil layer in nine typical forests along the 3800-km North-South Transect of Eastern China (NSTEC) to elucidate the latitudinal patterns of soil humic carbon fractions and their main influencing factors. SOC, HAC, FAC, HUC, and HEC increased with increasing latitude (all P<0.001), and exhibited a general trend of tropical < subtropical < temperate. The ratios of humic C fractions to SOC were 9.48%-12.27% (HAC), 20.68%-29.31% (FAC), and 59.37%-61.38% (HUC). Climate, soil texture, and soil microbes jointly explained more than 90% of the latitudinal variation in SOC, HAC, FAC, HEC, and HUC, and interactive effects were important. These findings elucidate latitudinal patterns of soil humic C fractions in forests at a large scale, and may improve models of soil C turnover and storage.

The influence of monsoon climatic characteristics makes the tropics of China different from those of other parts of the world. Therefore, the location of the northern boundary of China’s tropical zone has been one of the most controversial issues in the study of comprehensive physical regionalisation in China. This paper introduces developments in the study of the northern boundary of China’s tropical zone, in which different scholars delimit the boundary with great differences based on different regionalisation objectives, indexes, and methods. The main divergence of opinion is found in different understandings of zonal vegetation, agricultural vegetation type, cropping systems, tropical soil type and tropical characteristics. In this study, we applied the GeoDetector model, which measures the spatial stratified heterogeneity, to validate the northern boundaries of the tropical zone delimited by six principal scholars. The results show that the mean q-statistic value of the higher latitude boundary delimited by Ren Mei’e is the largest (q=0.37), suggesting that, of the rival views, it best reflects the regional differences between China’s tropical and subtropical zones, but it is not necessarily suitable for guiding the development of tropical agriculture. The mean values of the q-statistics of Zheng Du’s line and Yu Xianfang’s line around the Leizhou Peninsula at a lower latitude were smaller, at 0.10 and 0.08 respectively, indicating that the regional differences were smaller than those of Ren Mei’e’s boundary. Against the background of global climate change, the climate itself is changing in fluctuation. It is, thus, worth our further research whether the northern boundary of the tropical zone should not be a fixed line but rather should fluctuate within a certain scope to reflect these changes.

China’s investments, financial incentives and deductions in terms of ecological conservation are based at the county level. Therefore, the monitoring and assessment of the effects of ecological conservation at the county level is important to provide a scientific basis for the assessment of the ecological and environmental quality at the county scale. This paper quantitatively estimated the dynamics of high-quality ecosystems and vegetation coverage over the past 15 years, and their relationships with the number of ecological conservation programs at the county level were analyzed. Then, the effects of ecological conservation measures on ecological changes at the county level and their regional suitability were assessed and discussed. The results showed that counties with a percentage of high-quality ecosystems greater than 50% were primarily distributed in northeastern China, southern subtropical China and the southeastern Qinghai-Tibet Plateau, and those with a percentage lower than 20% were mostly distributed in northwestern China, the southwestern karst region and the North China Plain. In recent decades, ecological conservation has focused on ecologically fragile regions; more than five ecological conservation programs have been implemented in most counties of the Three River Source Region in Qinghai Province, southeastern Tibet, western Sichuan, the Qilian Mountains, southern Xinjiang and other western regions, while only one or zero have been implemented in the eastern coastal area of China. Over the past 15 years, the proportional area of high-quality ecosystems has increased in approximately 53% of counties. The vegetation coverage of counties in the Loess Plateau, Huang-Huai-Hai Plain, Beijing-Tianjin-Hebei (Jing-Jin-Ji), Sichuan-Guizhou-Chongqing, and Guangdong-Guangxi provincial-level areas has increased significantly. However, it decreased in northern Xinjiang, central Tibet, central and eastern Inner Mongolia, the Yangtze River Delta and other regions. The relationships between the numbers of ecological conservation programs and the indicators of ecosystem restoration response, such as high-quality ecosystem and vegetation coverage, do not show positive correlations. These results suggest that ecological conservation programs should be planned and implemented according to the distribution patterns of high-quality ecosystems and that restoration measures such as afforestation should follow natural principles and regional differentiation under the background of climate change.

This review summarizes the effects of vegetation on runoff and soil loss in three dimensions: vertical vegetation structures (aboveground vegetation cover, surface litter layer and underground roots), plant diversity, vegetation patterns and their scale characteristics. Quantitative relationships between vegetation factors with runoff and soil loss are described. A framework for describing relationships involving vegetation, erosion and scale is proposed. The relative importance of each vegetation dimension for various erosion processes changes across scales. With the development of erosion features (i.e., splash, interrill, rill and gully), the main factor of vertical vegetation structures in controlling runoff and soil loss changes from aboveground biomass to roots. Plant diversity levels are correlated with vertical vegetation structures and play a key role at small scales, while vegetation patterns also maintain a critical function across scales (i.e., patch, slope, catchment and basin/region). Several topics for future study are proposed in this review, such as to determine efficient vegetation architectures for ecological restoration, to consider the dynamics of vegetation patterns, and to identify the interactions involving the three dimensions of vegetation.

This study presents a soil and water integrated model (SWIM) and associated statistical analyses for the Huaihe River Basin (HRB) based on daily meteorological, river runoff, and water resource data encompassing the period between 1959 and 2015. The aim of this research is to quantitatively analyze the rate of contribution of upstream runoff to that of the midstream as well as the influence of climate change and human activities in this section of the river. Our goal is to explain why extreme precipitation is concentrated in the upper reaches of the HRB while floods tend to occur frequently in the middle reaches of this river basin. Results show that the rate of contribution of precipitation to runoff in the upper reaches of the HRB is significantly higher than temperature. Data show that the maximum contribution rate of upstream runoff to that of the midstream can be as high as 2.23%, while the contribution of temperature is just 0.38%. In contrast, the rate of contribution of human activities to runoff is 87.20% in the middle reaches of the HRB, while that due to climate change is 12.80%. Frequent flood disasters therefore occur in the middle reaches of the HRB because of the combined effects of extreme precipitation in the upper reaches and human activities in the middle sections.

In this paper we establish a model that expresses the coupled relationship between grain yield and agricultural labor changes in China, and present a preliminary discussion of the coupled processes involved in changes in these factors at the county level. Thus, we develop two coefficients on the basis of county-level statistical data for grain yield and agricultural labor for the years 1991, 2000, and 2010, namely, the grain-labor elasticity coefficient (GLEC) and the agricultural labor-transfer effect coefficient (ALTEC). The results of this study show that during the transformation process of agricultural development in China, different kinds of coupled relationships between grain yield and agricultural labor changes co-existed at the same time. For example, between 1991 and 2010, counties characterized by three different coupled modes (i.e., increasing grain yield and decreasing agricultural labor, increasing grain yield and agricultural labor, and decreasing grain yield and agricultural labor) account for 48.85%, 29.11%, and 19.74% of the total across the study area, respectively. Interestingly, a coupled relationship between increasing grain yield and decreasing agricultural labor is mainly concentrated in the traditional farming areas of China, while a coupled relationship between increasing grain yield and agricultural labor is primarily concentrated in pastoral areas and agro-pastoral ecotones in underdeveloped western China. At the same time, a coupled relationship between decreasing grain yield and agricultural labor is concentrated in areas that have experienced a rapid development transition in agriculture, especially the developed southeastern coast of China. The results of this study also show that between 1991 and 2010, 1961 counties experienced a decline in the proportion of agricultural labor; of these, 1452 are also characterized by increasing grain yield, 72.38% of the total. This coupled relationship between grain yield and changes in the proportion of agricultural labor shows a stepped fluctuation and has continually strengthened over time. Data show that mean values for the GLEC and ALTEC increased from -0.25 and -2.93 between 1991 and 2000 to -0.16 and -1.78 between 2000 and 2010, respectively. These changes in GLEC and ALTEC illustrate that the influence of agricultural labor changes on increasing grain yields has gradually diminished. Finally, the results of this study reveal that the ‘Hu Huanyong Line’ is a significant boundary sub-dividing this coupled relationship between grain yield and changes in agricultural labor.

Development of Xiong'an New District (XND) is integral to the implementation of the Beijing-Tianjin-Hebei (BTH) Integration Initiative. It is intended to ease the non-capital functions of Beijing, optimize regional spatial patterns, and enhance ecosystem services and living environment in this urban agglomeration. Applying multi-stage remote sensing (RS) images, land use/cover change (LUCC) data, ecosystem services assessment data, and high-precision urban land-cover information, we reveal the regional land-cover characteristics of this new district as well as across the planned area of the entire BTH urban agglomeration. Corresponding ecological protection and management strategies are also proposed. Results indicated that built-up areas were rapidly expanding, leading to a continuous impervious surface at high density. Urban and impervious surface areas (ISAs) grew at rates 1.27 and 1.43 times higher than that in the 2000s, respectively, seriously affecting about 15% area of the sub-basins. Construction of XND mainly encompasses Xiongxian, Rongcheng, and Anxin counties, areas which predominantly comprise farmland, townships and rural settlements, water, and wetland ecosystems. The development and construction of XND should ease the non-capital functions of Beijing, as well as moderately control population and industrial growth. Thus, this development should be included within the national ‘sponge city’ construction pilot area in early planning stages, and reference should be made to international low-impact development modes in order to strengthen urban green infrastructural construction. Early stage planning based on the existing characteristics of the underlying surface should consider the construction of green ecological patches and ecological corridors between XND and the cities of Baoding, Beijing, and Tianjin. The proportion of impervious surfaces should not exceed 60%, while that of the core area should not exceed 70%. The development of XND needs to initiate the concept of ‘planning a city according to water resource amount’ and incorporate rainwater collection and recycling.

Overall population exposure is measured by multiplying the annual average number of extremely hot days by the number of people exposed to the resultant heat. Extreme heat is also subdivided into high temperature (HT) and extremely high temperature (EHT) in cases where daily maximum temperature exceeds 35℃ and 40℃, respectively. Chinese population exposure to HT and EHT over four periods in the future (i.e., 2021-2040, 2041-2060, 2060-2081 and 2081-2100) were projected at the grid cell level in this study using daily maximum temperature based on an ensemble mean of 21 global climate models under the RCP8.5 scenario and with a population projection based on the A2r socio-economic scenario. The relative importance of population and climate as drivers of population exposure was evaluated at different spatial scales including national and meteorological geographical divisions. Results show that, compared with population exposure seen during 1981-2010, the base period, exposure to HT in China is likely to increase by 1.3, 2.0, 3.6, and 5.9 times, respectively, over the four periods, while concomitant exposure to EHT is likely to increase by 2.0, 8.3, 24.2, and 82.7 times, respectively. Data show that population exposure to HT is likely to increase significantly in Jianghuai region, Southwest China and Jianghan region, in particular in North China, Huanghuai region, South China and Jiangnan region. Population exposure to EHT is also likely to increase significantly in Southwest China and Jianghan region, especially in North China, Huanghuai, Jiangnan, and Jianghuai regions. Results reveal that climate is the most important factor driving the level of population exposure in Huanghuai, Jianghuai, Jianghan, and Jiangnan regions, as well as in South and Southwest China, followed by the interactive effect between population and climate. Data show that the climatic factor is also most significant at the national level, followed by the interactive effect between population and climate. The rate of contribution of climate to national-level projected changes in exposure is likely to decrease gradually from ca. 70% to ca. 60%, while the rate of contribution of concurrent changes in both population and climate is likely to increase gradually from ca. 20% to ca. 40% over the four future periods in this analysis.

Extreme rainstorm and the subsequent flood increasingly threaten the security of human society and ecological environment with aggravation of global climate change and anthropogenic activity in recent years. Therefore, the research on flood mitigation service (FMS) of ecosystem should be paid more attention to mitigate the risk. In this paper, we assessed FMS in the Upper Reaches of Hanjiang River (URHR), China from 2000 to 2014 using the Soil Conservation Service Curve Number (SCS-CN) model, and further simulated the future FMS under two climate scenarios (in 2020 and 2030). The results reveal that the FMS presented a fluctuating rising trend in the URHR from 2000 to 2014. The FMS in southern URHR was higher than that of northern URHR, and the change rate of FMS in the upstream of URHR (western URHR) was higher than the downstream of URHR (eastern URHR). The future FMS under scenarios of Medium-High Emissions (A2) and Medium-Low Emissions (B2) will decrease consistently. As land use/land cover changes in the URHR are negligible, we concluded that the change in FMS was mainly driven by climate change, such as storm and runoff. Our study highlights that climate scenarios analysis should be incorporated into the assessment of hydrologic-related services to facilitate regional water resources management.

Although several previous studies in Inner Mongolia examined the effects of ecological conservation on the delivery of ecosystem services, they were often limited in scope (few ecosystem services were assessed) and often suffered from confounding by spatial variation. In this study, we examined the impact of conservation measures (changes in grassland utilization patterns) on the provision of selected ecosystem services in three types of grasslands (meadow steppe in Hulun Buir, typical steppe in Xilin Gol, and semi-desert steppe in Ordos) in Inner Mongolia. We examined five utilization patterns: no use (natural grasslands), light use, moderate use, intensive use, and recovery sites (degraded sites protected from further use). Through household surveys and vegetation and soil surveys, we measured the differences in ecosystem services among the different grassland utilization patterns. We also identified spatial factors that confounded the quantification of ecosystem services in different types of grasslands. We found that light use generally provided high levels of ecosystem services in meadow steppe and typical steppe, with the main differences in the supporting ecosystem services. Surprisingly, we found no consistently positive impacts of strict conservation activities across the sites, since the results varied spatially and with respect to differences in the land-use patterns. Our study suggests that appropriate grassland utilization patterns can enhance the supply of ecosystem services and reduce negative effects on both household livelihoods and the environment.

Soil erosion has become a major global environmental problem and is particularly acute on the Loess Plateau (LP), China. It is therefore highly important to control this process in order to improve ecosystems, protect ecological security, and maintain the harmonious relationship between humans and nature. We compared the effects of rainfall and land use (LU) patterns on soil erosion in different LP watersheds in this study in order to augment and improve soil erosion models. As most research on this theme has so far been focused on individual study areas, limited analyses of rainfall and LU patterns on soil erosion within different-scale watersheds has so far been performed, a discrepancy which might influence the simulation accuracies of soil erosion models. We therefore developed rainfall and LU pattern indices in this study using the soil erosion evaluation index as a reference and applied them to predict the extent of this process in different-scale watersheds, an approach which is likely to play a crucial role in enabling the comprehensive management of this phenomenon as well as the optimized design of LU patterns. The areas considered in this study included the Qingjian, Fenchuan, Yanhe, and Dali river watersheds. Results showed that the rainfall erosivity factor (R) tended to increase in these areas from 2006 to 2012, while the vegetation cover and management factor (C) tended to decrease. Results showed that as watershed area increased, the effect of rainfall pattern on soil erosion gradually decreased while patterns in LU trended in the opposite direction, as the relative proportion of woodland decreased and the different forms of steep slope vegetation cover became more homogenous. As watershed area increased, loose soil and craggy terrain properties led to additional gravitational erosion and enhanced the effects of both soil and topography.

As the largest developing country in the world, China’s rural areas face many poverty-related issues. It is imperative to assess poverty dynamics in a timely and effective manner in China’s rural areas. Therefore, we used the poverty gap index to investigate the poverty dynamics in China’s rural areas during 2000-2014 at the national, contiguous poor areas with particular difficulties and county scales. We found that China made significant achievements in poverty alleviation during 2000-2014. At the national scale, the number of impoverished counties decreased by 1428, a reduction of 97.28%. The rural population in impoverished counties decreased by 493.94 million people or 98.76%. Poverty alleviation was closely associated with economic development, especially with industrial development. Among all 15 socioeconomic indicators, the industrial added value had the highest correlation coefficient with the poverty gap index (r = -0.458, p<0.01). Meanwhile, the inequality of income distribution in the out-of-poverty counties has been aggravated. The urban-rural income gap among the out-of-poverty counties increased by 1.67-fold, and the coefficient of variation in rural per-capita income among the out-of-poverty counties also increased by 9.09%. Thus, we argued that special attention should be paid to reducing income inequality for sustainable development in China’s rural areas.

Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error (LSE) model and spatial econometric analysis model to identify the villages’ poverty types and poverty difference. The case study shows that: (1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang. (2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions. (3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type. (4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of poverty alleviation at all levels to mobilize all kinds of anti-poverty resources.

Household CO₂ emissions were increasing due to rapid economic growth and different household lifestyle. We assessed per capita household CO₂ emissions (PHCEs) based on different household consuming demands (including clothing, food, residence, transportation and service) by using provincial capital city level survey data in China. The results showed that: (1) there was a declining trend moving from eastward to westward as well as moving from northward to southward in the distribution of PHCEs. (2) PHCEs from residence demand were the largest which accounted for 44% of the total. (3) Correlation analysis and spatial analysis (Spatial Lag Model (SLM) and Spatial Error Model (SEM)) were used to evaluate the complex determinants of PHCEs. Per capita income (PI) and household size (HS) were analyzed as the key influencing factors. We concluded that PHCEs would increase by 0.2951% and decrease by 0.5114% for every 1% increase in PI and HS, respectively. According to the results, policy-makers should consider household consuming demand, income disparity and household size on the variations of PHCEs. The urgency was to improve technology and change household consuming lifestyle to reduce PHCEs.

This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province’s future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows: (1) Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low. (2) Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others. (3) Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising 221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.

From the development of modern transportation to the current era of high-speed transportation networks, the Beijing-Tianjin-Hebei (BTH) region has always played a national leading role in land transportation development of China. In order to explore the long-term evolutionary characteristics of land transportation in the BTH region, this paper utilized a temporal scale of 100 years to systematically interpret the development process of the land transportation network. Taking 13 cities within the BTH region as research anchor cities, we took into account “leaping” mode of transportation in order to investigate the evolution of accessibility. Our research shows the following results: (1) The land transportation network in the BTH region has undergone five stages of development: the initial period of modernization (1881-1937); the period of stagnation of transportation development (1937-1949); the network expansion period (1949-1980); the period of trunk construction (1980-1995), and the period of high-speed transportation network development (1995-present). The network structure centered around Beijing has existed from the outset of modern transportation development. (2) The accessibility spatial pattern of land transportation in BTH region has evolved from expansion along traffic corridors to the formation of concentric circles. The stratified circular structure of transportation in anchor cities has gradually developed into a contiguous development pattern. (3) There are clear hierarchical differences in the transportation structures of anchor cities. Beijing has always been at the top of this hierarchy, while the hierarchical position of Zhangjiakou has fallen noticeably since 1949. The Beijing-Tianjin region was the first region to form a short-duration transportation circle structure, while the transportation advantages of the central part of Hebei Province, which is located in the center of the BTH transportation region, have yet to be realized.

In order to advance land use and land cover change (LUCC) research in Nepal, it is essential to reconstruct both the spatiotemporal distribution of agricultural land cover as well as scenarios that can explain these changes at the national and regional levels. Because of rapid population growth, the status of agricultural land in Nepal has changed markedly over the last 100 years. Historical data is used in this study, encompassing soils, populations, climatic variables, and topography. Data were revised to a series of 30 m grid cells utilized for agricultural land suitability and allocation models and were analyzed using a suite of advanced geographical tools. Our reconstructions for the spatiotemporal distribution of agricultural land in Nepal reveal an increasing trend between 1910 and 2010 (from 151.2 × 10² km² to 438.8 × 10² km²). This expanded rate of increase in agricultural land has varied between different eco, physiographic, and altitudinal regions of the country, significantly driven by population changes and policies over the period of this investigation. The historical dataset presented in this paper fills an existing gap in studies of agricultural land change and can be applied to other carbon cycle and climate modeling studies, as well as to impact assessments of agricultural land change in Nepal.

Despite many studies on land degradation in the Highlands of Northern Ethiopia, quantitative information regarding long-term changes in land use/cover (LUC) is rare. Hence, this study aims to investigate the LUC changes in the Geba catchment (5142 km²), Northern Ethiopia, over 80 years (1935-2014). Aerial photographs (APs) of the 1930s and Google Earth (GE) images (2014) were used. The point-count technique was utilized by overlaying a grid on APs and GE images. The occurrence of cropland, forest, grassland, shrubland, bare land, built-up areas and water body was counted to compute their fractions. A multivariate adaptive regression spline was applied to identify the explanatory factors of LUC and to create fractional maps of LUC. The results indicate significant changes of most types, except for forest and cropland. In the 1930s, shrubland (48%) was dominant, followed by cropland (39%). The fraction of cropland in 2014 (42%) remained approximately the same as in the 1930s, while shrubland significantly dropped to 37%. Forests shrank further from a meagre 6.3% in the 1930s to 2.3% in 2014. High overall accuracies (93% and 83%) and strong Kappa coefficients (89% and 72%) for point counts and fractional maps respectively indicate the validity of the techniques used for LUC mapping.

The continuing use of petrochemicals in mineral nitrogen (N) production may be affected by supply or cost issues and climate agreements. Without mineral N, a larger area of cropland is required to produce the same amount of food, impacting biodiversity. Alternative N sources include solar and wind to power the Haber-Bosch process, and the organic options such as green manures, marine algae and aquatic azolla. Solar power was the most land-efficient renewable source of N, with using a tenth as much land as wind energy, and at least 100th as much land as organic sources of N. In this paper, we developed a decision tree to locate these different sources of N at a global scale, or the first time taking into account their spatial footprint and the impact on terrestrial biodiversity while avoiding impact on albedo and cropland, based on global resource and impact datasets. This produced relatively few areas suitable for solar power in the western Americas, central southern Africa, eastern Asia and southern Australia, with areas most suited to wind at more extreme latitudes. Only about 2% of existing solar power stations are in very suitable locations. In regions such as coastal north Africa and central Asia where solar power is less accessible due to lack of farm income, green manures could be used, however, due to their very large spatial footprint only a small area of low productivity and low biodiversity was suitable for this option. Europe in particular faces challenges because it has access to a relatively small area which is suitable for solar or wind power. If we are to make informed decisions about the sourcing of alternative N supplies in the future, and our energy supply more generally, a decision-making mechanism is needed to take global considerations into account in regional land-use planning.

The Belt and Road Initiative (BRI)-a development strategy proposed by China - provides unprecedented opportunities for multi-dimensional communication and cooperation across Asia, Africa and Europe. In this study, we analyse the spatio-temporal changes in cultivated land in the BRI countries (64 in total) to better understand the land use status of China along with its periphery for targeting specific collaboration. We apply FAO statistics and GlobeLand30 (the world’s finest land cover data at a 30-m resolution), and develop three indicator groups (namely quantity, conversion, and utilization degree) for the analysis. The results show that cultivated land area in the BRI region increased 3.73×10⁴ km² between 2000 and 2010. The increased cultivated land was mainly found in Central and Eastern Europe and Southeast Asia, while the decreased cultivated land was mostly concentrated in China. Russia ranks first with an increase of 1.59×10⁴ km² cultivated land area, followed by Hungary (0.66×10⁴ km²) and India (0.57×10⁴ km²). China decreased 1.95×10⁴ km² cultivated land area, followed by Bangladesh (-0.22×10⁴ km²) and Thailand (-0.22×10⁴ km²). Cultivated land was mainly transferred to/from forest, grassland, artificial surfaces and bare land, and transfer types in different regions have different characteristics: while large amount of cultivated land in China was converted to artificial surfaces, considerable forest was converted to cultivated land in Southeast Asia. The increase of multi-cropping index dominated the region except the Central and Eastern Europe, while the increase of fragmentation index was prevailing in the region except for a few South Asian countries. Our results indicate that the negative consequence of cultivated land loss in China might be underestimated by the domestic-focused studies, as none of its close neighbours experienced such obvious cultivated land losses. Nevertheless, the increased cultivated land area in Southeast Asia and the extensive cultivated land use in Ukraine and Russia imply that the regional food production would be greatly improved if China’ “Go Out policy” would help those countries to intensify their cultivated land use.

Over the past few decades, built-up land in China has increasingly expanded with rapid urbanization, industrialization and rural settlements construction. The expansions encroached upon a large amount of cropland, placing great challenges on national food security. Although the impacts of urban expansion on cropland have been intensively illustrated, few attentions have been paid to differentiating the effects of growing urban areas, rural settlements, and industrial/transportation land. To fill this gap and offer comprehensive implications on framing policies for cropland protection, this study investigates and compares the spatio-temporal patterns of cropland conversion to urban areas, rural settlements, and industrial/transportation land from 1987 to 2010, based on land use maps interpreted from remote sensing imagery. Five indicators were developed to analyze the impacts of built-up land expansion on cropland in China. We find that 42,822 km² of cropland were converted into built-up land in China, accounting for 43.8% of total cropland loss during 1987-2010. Urban growth showed a greater impact on cropland loss than the expansion of rural settlements and the expansion of industrial/transportation land after 2000. The contribution of rural settlement expansion decreased; however, rural settlement saw the highest percentage of traditional cropland loss which is generally in high quality. The contribution of industrial/transportation land expansion increased dramatically and was mainly distributed in major food production regions. These changes were closely related to the economic restructuring, urban-rural transformation and government policies in China. Future cropland conservation should focus on not only finding a reasonable urbanization mode, but also solving the “hollowing village” problem and balancing the industrial transformations.

Land use and its dynamics have attracted considerable scientific attention for their significant ecological and socioeconomic implications. Many studies have investigated the past changes in land use, but efforts exploring the potential changes in land use and implications under future scenarios are still lacking. Here we simulate the future land use changes and their impacts on ecosystem services in Northeast China (NEC) over the period of 2000-2050 using the CLUE-S (Conversion of Land Use and its Effects at Small regional extent) model under the scenarios of ecological security (ESS), food security (FSS) and comprehensive development (CDS). The model was validated against remote sensing data in 2005. Overall, the accuracy of the CLUE-S model was evaluated at 82.5%. Obtained results show that future cropland changes mainly occur in the Songnen Plain and the Liaohe Plain, forest and grassland changes are concentrated in the southern Lesser Khingan Mountains and the western Changbai Mountains, while the Sanjiang Plain will witness major changes of the wetlands. Our results also show that even though CDS is defined based on the goals of the regional development plan, the ecological service value (ESV) under CDS is RMB 2656.18 billion in 2050. The ESV of CDS is lower compared with the other scenarios. Thus, CDS is not an optimum scenario for eco-environmental protection, especially for the wetlands, which should be given higher priority for future development. The issue of coordination is also critical in future development. The results can help to assist structural adjustments for agriculture and to guide policy interventions in NEC.

This study developed a comprehensive system to evaluate the intensity of cropland use and evolution of cropland use in the Huang-Huai-Hai Plain. Delphi-entropy methods were adopted to determine the weight of the index, and the GeoDetector model was established to explore the influencing factors. The results are summarized as follows: (1) The intensity of inputs, degree of utilization, and production increased continuously, but the intensity of continuous conditions experienced an overall decline followed by a rebound towards the end of the study period. The number of counties with high and moderately high intensity increased by 56.8% and 14.6%, respectively, from 1996 to 2011. The number of counties with moderately low and low intensity declined by 35.9 % and 11.9 %, respectively. Areas with significant increases in intensity were mainly distributed in northeast Hebei Province, northwest Shandong Province, and north Jiangsu Province. The intensity is high in northern Jiangsu and Anhui; the output effect remained above moderate intensity mainly near Beijing, Tianjin, Tangshan, and counties in the suburbs of Shijiazhuang. (2) Natural disasters, elevation, slope, and road networks were the main factors influencing the intensity of cropland use in this region, with influence values of 0.158, 0.143, 0.129, and 0.054, respectively. Areas with moderately high and high levels of intensity were distributed in low-lying areas. Uneven distribution of precipitation, seasonal drought, and flood disasters can directly affect the stability index of croplands and reduce the intensity of cropland use. Developed road networks are associated with moderately high intensity. Our results suggest recommendations such as promoting agricultural intensification and large-scale management, promoting the construction of road networks, improving early warning systems for drought and flood disasters, and promoting moderate and intensive use of arable land, and focusing on restoration and sustainable use of cropland.

Increasing soil organic carbon (SOC) sequestration is not only an efficient method to address climate change problems but also a useful way to improve land productivity. It has been reported by many studies that land-use changes can significantly influence the sequestration of SOC. However, the SOC sequestration potential (SOCP, the difference between the saturation and the existing content of SOC) caused by land-use change, and the effects of land-use optimization on the SOCP are still not well understood. In this research, we modeled the effects of land-use optimization on SOCP in Beijing. We simulated three land-use optimization scenarios (uncontrolled scenario, scale control scenario, and spatial restriction scenario) and assessed their effects on SOCP. The total SOCP (0-20 cm) in Beijing in 2010 was estimated as 23.82 Tg C or 18.27 t C/ha. In the uncontrolled scenario, the built-up land area of Beijing would increase by 951 km² from 2010 to 2030, and the SOCP would decrease by 1.73 Tg C. In the scale control scenario, the built-up land area would decrease by 25 km² and the SOCP would increase by 0.07 Tg C from 2010 to 2030. Compared to the uncontrolled scenario, the SOCP in 2030 of Beijing would increase by 0.77 Tg C or 0.64 t C/ha in the spatial restriction scenario. This research provides evidence to guide planning authorities in conducting land-use optimization strategies and estimating their effects on the carbon sequestration function of land-use systems.

Understanding the spatial and temporal variations of cropping systems is very important for agricultural policymaking and food security assessment, and can provide a basis for national policies regarding cropping systems adjustment and agricultural adaptation to climate change. With rapid development of society and the economy, China’s cropping structure has profoundly changed since the reform and opening up in 1978, but there has been no systematic investigation of the pattern, process and characteristics of these changes. In view of this, a crop area database for China was acquired and compiled at the county level for the period 1980-2011, and linear regression and spatial analysis were employed to investigate the cropping structure type and cropping proportion changes at the national level. This research had three main findings: (1) China’s cropping structure has undergone significant changes since 2002; the richness of cropping structure types has increased significantly and a diversified-type structure has gradually replaced the single types. The single-crop types—dominated by rice, wheat or maize—declined, affected by the combination of these three major food crops in mixed plantings and conversion of some of their planting area to other crops. (2) In the top 10 types, 82.7% of the county-level cropping structure was rice, wheat, maize and their combinations in 1980; however, this proportion decreased to 50.7% in 2011, indicating an adjustment period of China’s cropping structure. Spatial analysis showed that 63.8% of China’s counties adjusted their cropping structure, with the general change toward reducing the main food types and increasing fruits and vegetables during 1980-2011. (3) At the national level, the grain-planting pattern dominated by rice shifted to coexistence of rice, wheat and maize during this period. There were significant decreasing trends for 47% of rice, 61% of wheat and 29.6% of maize cropping counties. The pattern of maize cropping had the most significant change, with the maize proportion decreasing in the zone from northeastern to southwestern China during this period. Cities and their surroundings were hotspots for cropping structural adjustment. Urbanization has significantly changed cropping structure, with most of these regions showing rapid increases in the proportion of fruit and vegetables. Our research suggests that the policy of cropping structural adjustment needs to consider geographical characteristics and spatial planning of cropping systems. In this way, the future direction of cropping structural adjustment will be appropriate and scientifically based, such as where there is a need to maintain or increase rice and wheat cropping, increase soybean and decrease maize, and increase the supply of fruit and vegetables.

Spatial distribution changes in major crops can reveal important information about cropping systems. Here, a new centroid method that applies physics and mathematics to spatial pattern analysis in agriculture is proposed to quantitatively describe the historical centroids of rice, maize and wheat in China from 1949 to 2014. The geographical centroids of the rice area moved 413.39 km in a 34.32° northeasterly (latitude 3.08°N, longitude 2.10°E) direction at a speed of 6.36 km/year from central Hunan province to Hubei province, while the geographical centroids of rice production moved 509.26 km in the direction of 45.44° northeasterly (latitude 3.22°N, longitude 3.27°E) at a speed of 7.83 km/year from central Hunan province to Henan province. The geographical centroids of the maize area and production moved 307.15 km in the direction of 34.33° northeasterly (latitude 2.29°N, longitude 1.56°E) and 308.16 km in the direction of 30.79° northeasterly (latitude 2.39°N, longitude 1.42°E), respectively. However, the geographical centroids of the wheat area and production were randomly distributed along the border of Shanxi and Henan provinces. We divided the wheat into spring wheat and winter wheat and found that the geographical centroids of the spring wheat area and production were distributed within Inner Mongolia, while the geographical centroids of winter wheat were distributed in Shanxi and Henan provinces. We found that the hotspots of crop cultivation area and production do not always change concordantly at a larger, regional scale, suggesting that the changing amplitude and rate of each crops’ yield differ between different regions in China. Thus, relevant adaptation measures should be taken at a regional level to prevent production damage in those with increasing area but decreasing production.

Multiple cropping index (MCI) is the ratio of total sown area and cropland area in a region, which represents the regional time intensity of planting crops. Multiple cropping systems have effectively improved the utilization efficiency and production of cropland by increasing cropping frequency in one year. Meanwhile, it has also significantly altered biogeochemical cycles. Therefore, exploring the spatio-temporal dynamics of multiple cropping intensity is of great significance for ensuring food and ecological security. In this study, MCI of Huang-Huai-Hai agricultural region with intensive cropping practices was extracted based on a cropping intensity mapping algorithm using MODIS Enhanced Vegetation Index (EVI) time series at 500-m spatial resolution and 8-day time intervals. Then the physical characteristics and landscape pattern of MCI trends were analyzed from 2000-2012. Results showed that MCI in Huang-Huai-Hai agricultural region has increased from 152% to 156% in the 12 years. Topography is a primary factor in determining the spatial pattern dynamics of MCI, which is more stable in hilly area than in plain area. An increase from 158% to 164% of MCI occurred in plain area while there was almost no change in hilly area with single cropping. The most active region of MCI change was the intersection zone between the hilly area and plain area. In spatial patterns, landscape of multiple cropping systems tended to be homogenized reflected by a reduction in the degree of fragmentation and an increase in the degree of concentration of cropland with the same cropping system.

Rapeseed is one of the major oil crops in China and it is very sensitive to climate change. The Yangtze River Basin is the main rapeseed production area in China. Therefore, a better understanding of the impact of climate change on rapeseed production in the basin is of both scientific and practical importance to Chinese oil industry and food security. In this study, based on climate data from 5 General Circulation Models (GCMs) with 4 representative concentration pathways (RCPs) in 2011-2040 (2020s), 2041-2070 (2050s) and 2071-2100 (2080s), we assessed the changes in rapeseed production potential between the baseline climatology of 1981-2010 and the future climatology of the 2020s, 2050s, and 2080s, respectively. The key modelling tool - the AEZ model - was updated and validated based on the observation records of 10 representative sites in the basin. Our simulations revealed that: (1) the uncertainty of the impact of climate change on rapeseed production increases with time; (2) in the middle of this century (2050s), total rapeseed production would increase significantly; (3) the average production potential increase in the 2050s for the upper, middle and lower reaches of the Yangtze River Basin is 0.939, 1.639 and 0.339 million tons respectively; (4) areas showing most significant increases in production include southern Shaanxi, central and eastern Hubei, northern Hunan, central Anhui and eastern Jiangsu.

Diverse conservation efforts have been expanding around the globe, even under the stress of increasing agricultural production. A striking example is the supply-chain agreements put upon the Amazon forest which had reduced deforestation by 80% from the early 2000s (27,772 km²) to 2015 (6207 km²). However, evaluation of these conservation efforts usually focused on the impacts within the Amazon biome only, while the effects that spill over to other areas (e.g., displacement of environmental pressure from one area to another) were rarely considered. Ignoring spillover effects may lead to biased or even wrong conclusions about the effectiveness of these conservation efforts because the hidden cost outside the target area of conservation may offset the achievement within it. It is thus important to assess the spillover effects of these supply-chain agreements. In this study, we used the two supply-chain agreements (i.e., Soy Moratorium and zero-deforestation beef agreement) implemented in the Amazon biome as examples and evaluated their spillover effects to the Cerrado. To achieve a holistic evaluation of the spillover effects, we adopted the telecoupling framework in our analysis. The application of the telecoupling framework includes the interactions between distant systems and extends the analytical boundaries beyond the signatory areas, which fill the gap of previous studies. Our results indicate that the supply-chain agreements have significantly reduced deforestation by half compared to projections within the sending system (i.e., Pará State in the Amazon, which exports soybeans and other agricultural products), but at the cost of increasing deforestation in the spillover system (i.e., a 6.6 time increase in Tocantins State of the Cerrado, where deforestation was affected by interactions between the Amazon and other places). Our study emphasizes that spillover effects should be considered in the evaluation and planning of conservation efforts, for which the telecoupling framework works as a useful tool to do that systematically.

This paper analyzes the role of the National Natural Science Foundation of China (NSFC) in advancing human geography in China by focusing on five key research areas: land use, urban systems and urban agglomeration, economic globalization, climate change and social and cultural geographies. All NSFC-funded human geography programs related to these five topics from 1986 to 2017 comprise the sample for analysis, and the research topics, content, teams, and peer-reviewed journal publications supported by these programs are investigated. Specifically, this paper analyzes the NSFC’s promotion of the expansion of research topics in response to national developmental needs and the shifting frontiers of human geography research internationally, its enhancement of interdisciplinary research, and its contributions to the assembly of specialized research teams. The paper also reports important progress in Chinese human geography over the past 30 years through the institutional lens of the NSFC, revealing major characteristics and trends in the discipline. The paper concludes by calling for further collaboration between the research community and the NSFC for the development of a locally suitable and globally influential Chinese human geography.

The rapid progress of China’s industrialization has been manifested in space as the formation and evolution of a series of industrial bases. Employing data from the years 1985, 2001 and 2010, this paper carries out differentiation, screening, and categorization of industrial bases in China. It then analyses the evolutional characteristics of these industrial bases and explores different paths of growth according to their scale or types, and summarizes the general pattern for their formation and evolution. The results of this study indicate that China’s industrial bases as a whole have gone through three spatial stages since the founding of the PRC in 1949: decentralized development before reform and opening up in 1978, gradual concentration in eastern coastal regions during the early period of reform and opening up, and balanced and diversified development since the beginning of the 21st century. By 2010, China had a total of 251 industrial bases and had thereby established the overall spatial map of its industrialization. As industrial bases expand in scale, their industrial structures develop from homogenization to diversification, and then again from diversification to competitive optimization. Leading industries in the vast majority of industrial bases constantly evolve along the track of light industries, basic materials industries, and advanced manufacturing industries. Meanwhile, the key factors in their evolution and development transition from traditional factors of production like resources and labor to new ones like capital and information, but there are significant differences in terms of influencing factors and growth paths between large, medium, and small bases. Small industrial bases primarily rely on natural resources to maintain development through a single leading industry, medium industrial bases gradually become more comprehensive in their industrial compositions, and large industrial bases evolve in the direction of a combination of basic materials industries and equipment manufacturing industries.

Numerous domestic scholars have argued that a remote location is the major factor preventing the transformation and sustainable development of resource-exhausted cities. Research to date, however, has not presented relevant evidence to support this hypothesis or explained how to identify the concept of ‘remoteness’. Resource-exhausted cities designated by the State Council of China were examined in this study alongside the provincial capital cities that contain such entities and three regional central cities that are closely connected to this phenomenon: Beijing, Shanghai, and Guangzhou. Spatial and temporal distances are used to calculate and evaluate the location remoteness degrees (LRDs) of resource-exhausted cities, in terms of both resource types and regions. The results indicate that resource-exhausted cities are indeed remote from the overall samples. Based on spatial distances, the LRDs are α₁ = 1.36 (i.e., distance to provincial capital city) and β₁ = 1.14 (i.e., distance to regional central city), but when based on temporal distances, α₂ = 2.02 (i.e., distance to provincial capital city) and β₂ = 1.44 (i.e., distance to regional central city). Clear differences are found in the LRDs between different regions and resource types, with those in western China and forest industrial cities the most obviously remote. Finally, the numbers of very remote resource-exhausted cities based on spatial and temporal distances (i.e., α > 1.5 ∩ β > 1.5) are 14 and 19, respectively, encompassing 17.9% and 24.4% of the total sampled. Similarly, 25 and 30 not remote resource-exhausted cities based on spatial and temporal distances (i.e., α ≤1.0 ∩ β ≤ 1.0) encompass 32.1% and 38.5% of the total, respectively. This study provided supporting information for the future development and policy making for resource-exhausted cities given different LRDs.

The Chinese urban system is currently experiencing a fundamental shift, as it moves from a size-based hierarchy to a network-based system. Contemporary studies of city networks have tended to focus on economic interactions without paying sufficient attention to the issue of knowledge flow. Using data on co-authored papers obtained from China Academic Journal Network Publishing Database (CAJNPD) during 2014-2016, this study explores several features of the scientific collaboration network between Chinese mainland cities. The study concludes that: (1) the spatial organization of scientific cooperation amongst Chinese cities is shifting from a jurisdiction-based hierarchical system to a networked system; and (2) several highly intra-connected city regions were found to exist in the network of knowledge, and such regions had more average internal linkages (14.21) than external linkages (8.69), and higher average internal linkage degrees (14.43) than external linkage degrees (10.43); and (3) differences existed in terms of inter-region connectivity between the Western, Eastern, and Central China regional networks (the average INCD of the three regional networks were 109.65, 95.81, and 71.88). We suggest that China should engage in the development of regional and sub-regional scientific centers to achieve the goal of building an innovative country. Whilst findings reveal a high degree of concentration in those networks - a characteristic which reflects the hierarchical nature of China’s urban economic structure - the actual spatial distribution of city networks of knowledge flow was found to be different from that of city networks based on economic outputs or population.

Poverty has been a focus of Chinese government for a long time. It is therefore of great significance to investigate both the mechanisms and spatial patterns of regional impoverishment in order to adequately target Chinese anti-poverty goals. Based on the human-environment relationship and multidimensional poverty theory, this study initially develops a three-dimensional model encompassing human, society, and environmental factors to investigate the mechanisms of rural impoverishment as well as to construct an indicator system to evaluate the comprehensive poverty level (CPL) in rural areas. A back propagation neural network model was then applied to measure CPL, and standard deviation classification was used to identify counties that still require national policy-support (CRNPSs) subsequent to 2020. The results of this study suggest that CPL values conform to a decreasing trend from the southeast coast towards the inland northwest of China. Data also show that 716 CRNPSs will be present after 2020, mainly distributed in high-arid areas of the Tibetan Plateau, the transitional zones of the three-gradient terrain, as well as karst areas of southwest China. Furthermore, CRNPSs can be divided into four types, that is, key aiding counties restricted by multidimensional factors, aiding counties restricted by human development ability, aiding counties restricted by both natural resource endowment and socioeconomic development level, and aiding counties restricted by both human development ability and socioeconomic development level. We therefore propose that China should develop and adopt scientific and targeted strategies to relieve the relative poverty that still exist subsequent to 2020.

The logistics clusters are the result of concentration, scale and specialization of logistics activities, and their quantitative measurement and development evaluation provide an important foundation for improving the land use efficiency and achieving economies of scale. Taking 289 cities at prefecture-level and above as research objects, this paper collected macro-statistical data of transport, postal and warehousing industry during 2000-2014, business registration data of more than 290 thousand logistics enterprises, and 170 thousand logistics points of interest (POI). With the integration of multi-index and multi-source data, the evolution process and spatial pattern of logistics clusters in China were explored with the methods of Location Quotient (LQ), Horizontal Cluster Location Quotient (HCLQ), Logistics Employment Density (LED) and modified Logistics Establishments’ Participation (LEP). The development levels, types and modes of different logistics clusters were quantified. Several important findings are derived from the study. (1) The logistics clusters are mainly located on the east side of the Hu Huanyong Line, and the accumulative pattern evolves from group to block structure, featuring wide coverage and high concentration. The evolution of logistics clusters has two stages of rapid convergence and stable change, resulting in gradual increase in the development level and efficiency of logistics clusters and in emergence of spillover effect. (2) 21 mature logistics clusters are distributed in the core and sub-cities of the main metropolitan areas of 16 provincial-level administrative divisions, conforming to the government logistics and transport planning. 43 emerging logistics clusters are distributed in 21 provincial administrative divisions, and different types of cities have huge disparities which highlight the differentiation of the market behaviors and government planning among them. (3) The logistics clusters present differentiated development modes with the change of scales. In urban agglomerations scale, the nested “center-periphery” structures with “main nucleus-secondary cores-general nodes” are clarified. The polar nuclear development, networked and balanced development, single core and multipoint, multi-core multipoint hub-spoke development patterns are formed in different provincial administrative divisions.

The interprovincial terrestrial physical geographical entities are the key areas of regional integrated management. In this paper, we analyzed the spatial patterns of the interprovincial terrestrial physical geographical names (ITPGN) from three aspects: numerical features, spatial variance and spatial agglomeration. The influencing factors of the distribution of ITPGN and the implications for the regional management were further discussed. GIS technology was used to visualize the distribution of ITPGN, analyze the spatial agglomeration and the influencing factors of ITPGN. A total of 11,325 ITPGN, including 4243 water ITPGN and 7082 terrain ITPGN, were extracted from the database of “China’s Second National Survey of Geographical Names (2014-2018)”, and the mountain geographical names were the largest type in ITPGN. Hunan Province had the largest number of the names in China, and Shanghai had the smallest number of the names. The spatial variance of the terrain ITPGN was larger than that of the water ITPGN, and the ITPGN showed a significant agglomeration phenomenon in the southern part of China. In addition, the relative elevation and the population had an impact on the distribution of the ITPGN. The largest number of the geographical names occurred in the regions where the relative elevation was between 1000-2000 meters, and where the population was between 40-50 million. Based on the analysis, it was suggested that the government should take the ITPGN as management units, optimize management strategies based on the characteristics of different types of ITPGN, strengthen the naming of unnamed interprovincial terrestrial physical geographical entities and balance the interests in the controversial ITPGN. This study demonstrated that GIS and spatial analysis techniques were useful for the research of ITPGN and the results could provide targeted management suggestions to realize coordinated development in the interprovincial regions.