Population Distribution In China Research Articles

China's provincial optimum population sizes under SSP‐RCP scenarios

AbstractClimate change poses new challenges to achieving a balanced population distribution. Predicting the impact of development patterns using climate change scenarios can offer more precise insights into environmental and social risks. By adopting the possibility–satisfiability (P–S) model, this study investigates the optimum population sizes for the 31 provincial districts of China by 2035 and 2050 under seven shared socioeconomic pathway‐representative concentration pathway (SSP‐RCP) scenarios. Results indicate that under SSP2‐4.5 scenario, which maintains current development patterns, the optimum human population (OHP) ranges from 985 million to 717 million in 2035 and from 902 million to 623 million by 2050 at different P–S values, respectively. The SSP1‐1.9 and SSP1‐2.6 scenarios offer promising prospects by carrying the largest optimum population size. Therefore, China's future development depends on choosing a sustainable path that prioritizes the growth of the OHP. The optimum population sizes of provinces under unbalanced development routes SSP4‐3.4 and SSP4‐6.0 scenarios are mainly limited by economic development, while those of the regional competition route SSP3‐7.0 scenario are limited by both economic and climatic pressures. Under the fossil fuel route SSP5‐8.5 scenario, climate deterioration imposes severe constraints on optimum population size. The optimum population scales of the eastern coastal area with high urbanization levels and the northwest area with harsh environments are subject to natural conditions. In addition, the central and western regions encounter population size limitations due to insufficient economic development. Notably, China's population distribution remains concentrated in the east and sparse in the west, flanking the Hu Huanyong Line (Hu Line), with minimal expected changes in the future. By studying the spatial distribution of the optimum population under different SSP‐RCP scenarios, this study provides theoretical support for government decision‐making in the context of future climate change.

Using POI and multisource satellite datasets for mainland China's population spatialization and spatiotemporal changes based on regional heterogeneity

Geospatial big data and remote sensing data are widely used in population spatialization studies. However, the relationship between them and population distribution has regional heterogeneity in different geographic contexts. It is necessary to improve data processing methods and spatialization models in areas with large geographical differences. We used land cover data to extract human activity, nighttime light and point-of-interest (POI) data to represent human activity intensity, and considered differences in geographical context to divide mainland China into northern, southern and western regions. We constructed random forest models to generate gridded population distribution datasets with a resolution of 500 m, and quantitatively evaluated the importance of auxiliary data in different geographical contexts. The street-level accuracy assessment showed that our population dataset is more accurate than WorldPop, with a higher R2 and smaller deviation. The improved datasets provided broad potential for exploring the spatial-temporal changes in grid-level population distribution in China from 2010 to 2020. The results indicated that the population density and settlement area have increased, and the overall pattern of population distribution has remained highly stable, but there are significant differences in population change patterns among cities with different urbanization processes. The importance of the ancillary data to the models varied significantly, with POI contributing the most to the southern region and the least to the western region. Moreover, POI had relatively less influence on model improvement in undeveloped areas. Our study could provide a reference for predicting social and economic spatialized data in different geographical context areas using POI and multisource satellite data.

Agglomeration and Radiation: Central Cities and China's Spatial Economy

Abstract This paper summarizes stylized facts of three dimensions of population agglomeration and the radiation effects of central cities relating to the evolutionary laws of China's population distribution. We test with decennial census data from 2000 to 2020 to identify determinants of population agglomeration and radiation effects. The results show that the distance to the major ports, central cities, and city centers of central cities determines China's population concentration. Moreover, central cities have apparent radiation effects. The closer to the central cities or the larger the population and economic scale of the central cities, the more the population is concentrated in peripheral cities or counties.

Characteristics of Soil Moisture Variation in Agroforestry in Karst Region

The special above-ground and underground dual structure in the karst area makes the capacity of surface water storage in this area poor. In water-limited ecosystems, soil moisture is the key to the survival of plants. Influenced by rainfall and soil texture, soil moisture variation characteristics of different vegetation types are different in slope land. Many researchers use rainfall simulation experiments to study the influence of soil water movement processes under rainfall patterns, but there are few studies under natural conditions. In this paper, wood trees, peach trees, flue-cured tobacco, and grassland were planted at the buffer zone boundary of Shibing, a World Heritage site, along different elevations in the depression of the research site. Peach trees and flue-cured tobacco were the main cash crops in the area. The soil layers of 0–0.15 m, 0.15–0.30 m, 0.30–0.45 m, 0.45–0.60 m, and 0.60–0.75 m were taken as research objects. Rainfall and soil moisture were monitored every ten minutes to study the variation of soil moisture of vegetation types under different rainfall patterns. Through the analysis of soil physicochemical properties and vegetation types, it was found that soil moisture changes were different in different land types. In general, shallow soil moisture (0~0.30 m) was more active in the wet season (CV > 10%) but tended to be stable in the dry season. The rainy season rainfall had the greatest influence on soil moisture change. The response level of soil moisture to rainfall of all vegetation types was grassland > peach trees > flue-cured tobacco. These results can provide ecological and economic suggestions for karst areas with large population distribution in China, so as to reduce the impact of rock desertification on this area.

Monitoring and Analysis of Population Distribution in China from 2000 to 2020 Based on Remote Sensing Data

Accurately and precisely grasping the spatial distribution and changing trends of China’s regional population is of great significance in new urbanization, economic development, public health, disaster assessment, and ecological environmental protection. To monitor and evaluate the long-term spatiotemporal characteristics of the population distribution in China, a population monitoring estimation model was proposed. Based on remote sensing data such as nighttime light (NTL) images, land use data, and data from the fifth, sixth, and seventh censuses of China, the population spatiotemporal distribution in China from 2000 to 2020 was analyzed with a random forest algorithm. This study obtained spatial distribution maps of population density at a 1 km x 1 km resolution in 2000, 2010, and 2020. The results revealed the trend of the spatiotemporal pattern of population change from 2000 to 2020. It shows that: the accuracy assessment using the 2020 census population of townships/streets as a reference shows an R2 of 0.67 and a mean relative error (MRE) of 0.44. The spatial pattern of the population in 2000 and 2010 is generally unchanged. In 2020, population agglomeration is evident in the east, with a slight increase in the proportion of the population in the west. The patterns of population agglomeration and urbanization also change over time. The population spatiotemporal distribution obtained in this study can provide a scientific reference for urban sustainable development and promote the rational allocation of urban resources.

Climate change and city size: the role of temperature difference in the spatial distribution of China's population.

This paper examines the relationship between climate change and the spatial distribution of population in China. We establish a two-way fixed effects model to investigate the role of temperature difference in the spatial distribution of China's population. We find that the annual variation of temperature has an impact on city size in both large and small cities, and that city size tends to shrink as the temperature difference increases. Meanwhile, we also find that the population in the cities located south of Qinling-Huaihe Line and Aihui-Tengchong Line (Hu's Line) is more sensitive to temperature effects, and that the temperature difference has a significant negative effect on city size. Similarly, the same results are found for prefecture-level cities with low administrative levels. Considering the endogeneity between temperature change and city size, we adopt an instrumental variable using latitude to perform a more robust empirical analysis, the results of a series of robustness tests support these conclusions.

Urban population distribution in China: Evidence from internet population

Based on mobile internet user data, we construct an “Internet population” measure and reexamine spatial population distribution in China. The location based service (LBS) data of mobile internet uses is able to capture the accurate location of users' residence and solve the underestimation problem of missing migrants. We have three main findings. First, contrary to previous studies based on traditional population statistics, city size distribution of Internet population fits well into Zipf's law with a R2 of 90.7%. Second, the Internet population indicator is superior to traditional population statistics in explaining inelastic household consumption such as water consumption, electricity consumption, and garbage disposal. It suggests that the “Internet population” is a better proxy of actual city population. Third, the traditional population statistics systematically overestimate population in small cities and underestimate population in large cities. It indicates that the public resource distortions will continue to exist or even worsen off in China if the allocation process relies greatly on traditional population statistics. Although no measures are perfect, our new population measure provides important incremental information for future discussion.

Classification of land surface slope spectrum and its relationship with population distribution in China at county scale

Classification of land surface slope spectrum and its relationship with population distribution in China at county scale

Lipid control in adult Chinese patients with type 2 diabetes: a retrospective analysis of time trends and geographic regional differences.

Lipid control in adult Chinese patients with type 2 diabetes: a retrospective analysis of time trends and geographic regional differences.

Spatiotemporal patterns and influencing factors of human migration networks in China during COVID-19

The social lockdowns and strict control measures initiated to combat the COVID-19 pandemic have had an impact on human migration. In this study, big data was used to analyze spatial patterns of population migration in 369 Chinese cities during the COVID-19 outbreak and to identify determinants of population migration. We found that the overall migration intensity decreased by 39.87% compared to the same period in 2019 prior to the COVID-19 outbreak. COVID-19 severely affected human migration. The public holidays and weekends have impacted human migration from the perspective of time scale. The spatial pattern of China's population distribution presents a diamond structure that is dense in the east and sparse in the west, which is bounded by the Hu line and the cities such as Beijing, Shanghai, Guangzhou and Chengdu as nodes to connect. There is a strong consistency between the population distribution center and the level of urban development. The urban human migration network is centered on provincial capitals or municipalities at the regional scale, showing a prominent "center-periphery" structure. COVID-19 dispersed the forces of human migration in time and changed the direction of human migration in space. But it did not change the pattern of national migration. The most critical factors influencing mass migration are income levels and traditional culture. This study reveals the impacts of major public health emergencies on conventional migration patterns and provides a scientific theoretical reference for COVID-19 prevention and control.

Mapping Multi-Temporal Population Distribution in China from 1985 to 2010 Using Landsat Images via Deep Learning

Fine knowledge of the spatiotemporal distribution of the population is fundamental in a wide range of fields, including resource management, disaster response, public health, and urban planning. The United Nations’ Sustainable Development Goals also require the accurate and timely assessment of where people live to formulate, implement, and monitor sustainable development policies. However, due to the lack of appropriate auxiliary datasets and effective methodological frameworks, there are rarely continuous multi-temporal gridded population data over a long historical period to aid in our understanding of the spatiotemporal evolution of the population. In this study, we developed a framework integrating a ResNet-N deep learning architecture, considering neighborhood effects with a vast number of Landsat-5 images from Google Earth Engine for population mapping, to overcome both the data and methodology obstacles associated with rapid multi-temporal population mapping over a long historical period at a large scale. Using this proposed framework in China, we mapped fine-scale multi-temporal gridded population data (1 km × 1 km) of China for the 1985–2010 period with a 5-year interval. The produced multi-temporal population data were validated with available census data and achieved comparable performance. By analyzing the multi-temporal population grids, we revealed the spatiotemporal evolution of population distribution from 1985 to 2010 in China with the characteristic of concentration of the population in big cities and the contraction of small- and medium-sized cities. The framework proposed in this study demonstrates the feasibility of mapping multi-temporal gridded population distribution at a large scale over a long period in a timely and low-cost manner, which is particularly useful in low-income and data-poor areas.

Population mapping in China with Tencent social user and remote sensing data

Real-time population data are vital for urban planning and resource management for sustainable development. To complement satellite-based population estimation methods, geospatial social media data provide additional opportunities to estimate the distribution of population with high levels of efficacy and accuracy. Thus, this study attempts to assess the performance of various sensing data to disaggregate population data in China; the tested data include Tencent location-based service (LBS) data (about 0.8 billion users), satellite-derived land use/cover data, and nightlight imagery data. With the use of census data for validation, the experimental results show that Tencent LBS data are much better than satellite-derived land use/cover data and nightlight satellite data for mapping the population distribution. The overall mapping accuracy at the city level using Tencent LBS data was 88.9%, whereas the accuracy using land use/cover data was 87.1% and that using nightlight satellite data was 85.5%. The experimental results also indicate that LBS data and remote sensing data could both be well integrated to map the population distribution in China. Thus, a population spatialization model was further developed using all of the tested indicators; this model allowed the overall population estimation accuracy at the city level to reach 90.4%. This model could help determine the population distribution on various spatial scales quickly and efficiently, and the developed tool and the provided population estimates may be vital for the sustainable development of cities and regions for which population data are lacking.

Spatiotemporal characteristics and determinants of internal migrant population distribution in China from the perspective of urban agglomerations.

Urban agglomerations are fundamental regional units of development and attract large-scale migrant population. Previous studies have only focused on migrant population distribution in major urban agglomerations. Therefore, this study analysed the spatiotemporal characteristics of migrant population distribution in China during 2000–2010 at city level from the perspective of urban agglomerations. The results indicate that urban agglomerations were accumulation areas of migrant population. Numerous people have migrated into 19 urban agglomerations, which has enlarged regional differences in migrant population distribution. The interprovincial migrant population dominated within urban agglomerations, whereas the intraprovincial migrant population dominated outside urban agglomerations. In the future, intraprovincial migration will become the dominant migration mode. The evolution of migrant population distribution pattern in urban agglomerations agrees with classic theories of unbalanced regional development. The determinants of migration in different regions were compared. Results revealed that economic and government driving forces jointly influenced migration; however, economic forces exceeded government forces. Economic forces were more influential within urban agglomerations, whereas government forces played more important roles outside urban agglomerations. Increased income and job opportunities were the core attractions of urban agglomerations. Moreover, with an increase in the urban agglomeration development level, the influence of economic forces increased, whereas that of government forces decreased. The findings provide a deeper understanding of migrant population distribution in China, which will benefit population management across various regions.

Evolving population distribution in China's border regions: Spatial differences, driving forces and policy implications.

The security and socioeconomic development of China’s border areas are of great significance to the nation and the wider world. Using census, statistical, digital elevation model (DEM) and network data, this paper employs visual analysis to capture population distribution patterns in China’s 131 border counties from 1982 to 2010. Multiple stepwise regression is carried out to identify the influencing factors of population dynamics in border regions. The main findings include: China’s most heavily populated border areas are primarily in the northeast, northwest, and the Guangxi-Yunnan region, while rapid growth of population is found in western Inner Mongolia, southwest Xinjiang, northwest Tibet, and southern Yunnan. Given the increasingly market-oriented migration mechanism, the national reclamation policy has been no longer effective in population attraction in the new century. Education has significantly lowered and will continuously lower the fertility rate in remote border areas. The factors influencing population growth show a remarkable regional heterogeneity along China’s long border.

Fitting Chinese cities’ population distributions using remote sensing satellite data

Remote sensing satellite data from 2012 to 2013 are used to fit the Chinese cities’ population distributions over the same period in order to verify the population distribution in China from a relatively objective perspective. Most scholars have used nighttime light data and vegetation indexes to fit the population distribution, but the fitting effect has not been satisfactory. In this paper, processed Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light data, net primary productivity of vegetation (NPP), and average slope data were used to fit the population distribution from the three dimensions of economic growth, ecological environment, and topographic factors, respectively. The fitting effect was significantly improved compared with other studies (R2 values of 0.9244 and 0.9253 in 2012 and 2013, respectively). Therefore, this method provides a practical and effective way to fit the population distribution for remote cities or areas lacking census data. Furthermore, there is important practical significance for the government to formulate its population policies rationally, optimize the spatial distribution of population, and improve the ecological quality of the city.

The distribution of Chinese minority populations and its change based on the study of the Hu Huanyong line

The “Hu Line” and its demographic implications have attracted world-wide attention since the line was developed 80 years. Using GIS, this paper conducts a statistical analysis and systematic investigation on the stability and spatial of China’s minority population growth on both sides of “Hu Line” by constructing the spatial database of China’s census data from 1953 to 2010 and initiating a new method for identifying the spatial patterns of population growth. Major findings are as follows: (1) Spatial distribution of the minority population in China is not balanced, showing a significant spatial clustering; (2) The minority population is widely distributed across China, spreading to East China and all over the country; (3) The distribution pattern of China’s minority population is characterized by extraordinary stability, with the ratio of south-east half to north-west half standing roughly at 75:25 from 1953 to 2010. We can thus say that the “Hu Line” is also a mutant line of China’s minority population.

Regional Features and National Differences in Population Distribution in China’s Border Regions (2000–2015)

China is of great geostrategic significance not only in the Asia-Pacific region, but also in the wider world. The population distribution in China’s border regions is of significance for the development of China and neighboring countries. Based on the LandScan Population Distribution Database, this study used GIS spatial analysis and statistics to investigate national trends in the population distribution of China’s border regions. The study areas were the buffer zones within specified Euclidean distances from the land borders of China. The results showed that: (1) Although the population agglomeration index and population size inside China’s border areas have increased, the population density inside China’s border areas is still far below China’s average population density; (2) Over the last 15 years, the population of China’s northwestern border has been sparse, with small increases in the population agglomeration index and population size. China’s northeastern and southwestern border regions have several average population density areas, but the northeastern regions have seen a substantial reduction in population size since 2000. Based on our analysis, we propose that the Chinese government introduce supporting policies for the development of border regions to maintain the population size. At the same time, considering the varied living suitability of the natural environment along the northeastern, northwestern, and southwestern borders, “moderate agglomeration” and “moderate evacuation” population development strategies should be implemented in specified areas. Tilt policy should also be implemented in areas of rapid population decline.

PHP129 - Analysis on the Regional Distribution of Telemedicine in China

Analyze the regional distribution of telemedicine in diferent districts. According to the directories of National Health Committee telemedicine center network hospitals , collecting the hospital ownership in different regions.And analyzing the circumstances of telemedicine from the view of population distribution in China. there are 1220 hospitals in the directories, which from 28 provinces ,it can be divided into three parts. 1.there are 13 region from the west of China, contained 760 medical units, accounting for 62.30%, Among the 760 hospitals, tertiary hospitals accounted for 11.84%,secondary hospitals accounted for 35.28%, community hospital accounted for 3.28%, unrated hospital accounted for 49.60%. And there are 471 hospitals in the poorest areas among 760 medical units, 8.5% are tertiary hospitals, secondary hospitals accounted for 22% ,community hospital accounted for 2.55%, unrated hospital accounted for 66.88% . 2. there are 6 provinces from the central and northeast old industrial regions regions,contained 135 hospitals and institutions, accounted for 11.06%.Among the 135 hospitals, tertiary hospitals accounted for 17.78% , secondary hospitals accounted for 40.74%, community hospital accounted for 20.74% ,unrated hospital accounted for 20.74%.3. there are 9 provinces from the economically developed regions,contained 327 hospitals and institutions,accounting for 26.8%.Among the 327 hospitals ,the ertiary hospitals accounted for 14.68% , secondary hospitals accounted for 45.87%, community hospital accounted for 4.28%, unrated hospital accounted for 35.17%. 1.Most of hospitals of the telemedicine are distributed in the west of China which are vast sparsely populated, and many of them are in the poorest and most extensive areas of west. 2.some of them are in the central and northeast old industrial areas ,3 .Less of them are distributed in economically developed regions. so, we predict telemedicine will have a better development in China.

Prevalence of chronic kidney disease and its association with metabolic diseases: a cross-sectional survey in Zhejiang province, Eastern China

BackgroundThe prevalence of chronic kidney disease (CKD) and metabolic diseases has increased at different rates in different regions in China. The aim of our study was to estimate the prevalence of CKD and to analyze associated risk factors of CKD in Zhejiang province, Eastern China.MethodsA cross-sectional survey of 11,013 adults was conducted from September 2009 to June 2012 in Zhejiang Province, located in Eastern China. CKD was defined as having an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 or the presence of albuminuria. Medical history, physical examination and laboratory data were used to diagnose metabolic diseases. Age- and sex-standardized prevalence was calculated using the data on the population distribution in China in 2010. We examined risk factors associated with decreased renal function and albuminuria using multivariate logistic regression.ResultsA total of 10,384 adults (94.3%) completed the screening. The standardized prevalence of reduced renal function (eGFR < 60 mL/min/1.73 m2) was 1.83% (95% CI 1.52–2.13) and that of albuminuria was 8.65% (95% CI 7.98–9.31). The overall prevalence of CKD was 9.88% (95% CI 9.18–10.59). The prevalence of reduced renal function was greater in the eastern rural areas in Zhejiang province. Multivariate logistic regression revealed that metabolic diseases such as diabetes, obesity, hypertension, and hyperuricemia were independent risk factors of CKD. Patients with metabolic diseases had a significantly (P < 0.001) higher prevalence of CKD than those without such diseases.ConclusionsCKD has become a severe public health problem in Zhejiang Province, and metabolic diseases may increase the risk of CKD in Zhejiang population.

中国城市人口分布的幂次现象

幂次法则是一个普遍存在于自然科学和社会科学中的现象，在城市中也不例外。尽管对于形成这种现象的幕后机制仍在试图理解之中，但城市中的幂次现象仍然有其重要的意义。这一现象是客观规律在城市人口分布整体特征中的自发涌现，不仅可以作为自上而下构建理论的依据，而且可以作为自下而上进行城市复杂系统模拟的基础，尤其可做为我国政府制定城乡均衡发展政策的参考。本文通过大量城市人口数据统计，发现我国城市人口分布的R2值很大，说明我国城市人口分布符合幂次法则。而且q值在1附近，说明符合位序–规模法则。从1999年到2009年的演化过程来看，我国城市人口分布的幂次现象日趋加强，斜率q最近几年远离−1，说明城市趋于不均衡发展。 Power law is a common phenomenon in natural and social sciences, including cities. Though many attempts have been made to understand the underlying mechanisms of the power law phenomenon, it means a lot to cities. This phenomenon is a manifestation of an emerging, objective law in urban population distribution, which can serve as a basis not only for theory construction from the top down, but also for simulations on urban complex systems from the bottom up, in particular as a reference for urban and regional policy making in China. Through mass urban population statistics, we found in the present paper that the R2 values for the urban population distribution in China were high, indicating that distribution fulfills the requirement of the power law distribution. In addition, the q values scattered around unity, fulfilling the requirement of the rank-size rule. Starting from 1999 through 2009, the evolution toward the power law of the urban population distribution in China intensified, with the slope of q moving further away from −1, indicating imbalanced development of cities.