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Addressing the issue of the healthy and coordinated development of the population and economic factors in rural areas will not only help consolidate and expand the achievements of poverty alleviation, but will also lay a foundation for comprehensive rural revitalization. In this paper, the spatial coupling relationship between the population and economic factors in rural areas in the Qinling-Daba Mountains, China, is explored to provide a reference for rural revitalization and regional sustainable development in poverty areas. Sixty-eight county units in rural areas in the Qinling-Daba Mountains, as well as the population and economic factors in rural areas, are used to study the spatial coupling relationship between population and economy, as well as the driving mechanism, in rural areas in the Qinling-Daba Mountains from 2010 to 2020. The results show that a population contraction phenomenon occurred in the rural areas in the Qinling-Daba Mountains, and the spatial agglomeration trends of the population and economic factors were consistent. The agglomeration was mainly located in the suburban areas of the municipal area, and the agglomeration degree was significantly higher in these areas than in other areas. In terms of the spatial distribution, the economic development level of the rural areas in the northeastern part of the Qinling-Daba Mountains was generally higher than that in the central and western parts, and the unbalanced trends of the population and economic spatial differentiation in the eastern and western regions were significant. The spatial coupling relationship between the population and economy changed from coordinated development to economic advancement. This was mainly due to the mutual restriction and joint actions of the industrial structure, capital situation, natural environment, policies, and institutional regulations, among which the industrial structure and capital status had significant effects. [ABSTRACT FROM AUTHOR]

It is very important to understand the ecological and socio-economic factors in population distribution and their changes over time for the compilation of regional development planning and the guidance of rational population flow. Using surface-based population data for China from 1990 to 2015, the national distribution and dynamics of the human population by elevation are quantified based on 1-km cell-size gridded distribution datasets and 1-km cell-size DEM (digital elevation model). A geographical detector model is used to quantitatively analyze the dominant role of natural geographical factors, such as topography and climate, on the spatial distribution of population. Results show that: 1) the population size and density decrease rapidly with elevation below 1000 m above the sea level, and the gap in population density between low-altitude areas and high-altitude areas increases with time because of the continuous growth of population density in low-altitude areas; 2) the distribution of the population can be divided into five steps according to integrated population density (IPD), in proportions of 43: 35: 21: 1: 0, and that these proportions have remained stable over the last 25 yr; 3) the basic pattern of population spatial distribution is determined by natural geographical environment factors, such as topography, climate, geomorphology, and their interactions; and 4) the development of society and the economy are the driving forces for the dynamic change in the population distribution during the study period, with the distribution pattern and dynamics of population by altitude in China providing a comprehensive reflection of various geographical elements on different spatial scales. [ABSTRACT FROM AUTHOR]

The spatial distribution of urban population can reflect significantly urban functions and development status. Shenyang, as a typical old industrial city in China, has experienced considerable changes in spatial distribution of population in the process of urban transformation, resulting in the change of urban spatial structure. Based on the subdistrict data of Chinese national population censuses in 1982, 1990 and 2000, this study simulates the evolution pattern of spatial distribution of urban population in Shenyang City. Using statistical method and exploratory spatial data analysis (ESDA), we found that the population distribution, on the whole, has presented a balanced and decentralized trend since the 1980s, which characterizes with Chinese suburbanization. Furthermore, based on the investigation of the pattern of population distribution, it is concluded that the negative exponential model fitted the distribution best, and population concentration in the inner suburb kept increasing gradually, meanwhile, the spatial structure of population distribution has presented a polycentric feature since the 1980s. The parameters of the model show that population in the urban core concentrate significantly all the time. The increase of population in the inner suburb influences the population distribution pattern more and more importantly, but the concentration intensity of population cores in inner suburb is still low. [ABSTRACT FROM AUTHOR]

Character of population distribution is one of the focuses studied by urban geography. Using the fifth national census data as basic data and using areal interpolation method, this paper analyzes character of urban population distribution of Shenyang City, Northeast China, in terms of three aspects of statistical character, spatial auto-correlation and spatial structure. Furthermore, this research analyzes the factors affecting the population distribution of the city. The main conclusions include: 1) There is an obvious structure character of population distribution in the grid with a grain of 300m, which is appropriate scale when researching population distribution in Shenyang City. 2) Urban population distribution has the character of assembling while population density distribution takes on variability in Shenyang City. 3) Population density distribution shows spatial auto-correlation within 7.36km. Spatial heterogeneity of population density is low. 4) Urban center, population distribution barycenter and population density maximum points separate each other. Population density distribution has multi-cores character. 5) Layout of governments, primary schools, middle schools, colleges, hospitals and marketplaces affects population distribution directly. With the increase of distance to these factors, population density decreases as logarithm. [ABSTRACT FROM AUTHOR]

Population density in Guangzhou City is characterized by a main single center and considerable differences throughout the 8 districts and 112 neighborhoods and towns. Historically, population density in Guangzhou City rose sharply, and population distribution was mainly influenced by the attraction of the port. After the founding of the People’s Republic of China (PRC), a series of large-sized factories were built in suburban areas, which drew in a large amount of population from the areas outside of Guangzhou. A small part of this population lived in the suburban areas while most resided within the city centre. As the natural increase rate of population was very high, the population density of both the city centre and suburban areas rose, the former rose at higher rates. Since reform and the opening up to the outside world, Chinese economy has grown quickly, the total population of Guangzhou has also increased quickly. Meanwhile, changes in population density within the city is becoming more and more obvious. Population density in the city centre is falling and in city periphery is rising. From the analysis of the population density model, it is found that population distribution of Guangzhou is in the process of transition from an early stage to a mature stage. Population decline within the centre city of Guangzhou City, which reflects a prosperous economy of the city, is significantly different from the recession of in the western countries. [ABSTRACT FROM AUTHOR]