Studying population flow patterns is essential for comprehending regional population changes and economic and social development trends. Using data from the sixth and seventh national population censuses to classify China's interprovincial population flows into four types: rural-urban, rural-rural, urban-urban, and urban-rural, this paper analyzes the spatial characteristics of population flow networks and their influencing factors using a spatial autoregressive negative binomial model. The results show that: The proportion of rural-urban and urban-urban population flows has increased, while the proportion of rural-rural population flows has decreased. Rural-rural and rural-urban population flows tend to move from west to east, while urban-urban and urban-rural population flows are diverse and bi-directional. China's population center is shifting from a single city (province) to an urban agglomeration. While economic factors play a significant role in rural-urban and rural-rural population flows, the factors influencing urban-rural and urban-urban population flows are complex and diverse. The degree of influence of economic factors on these flows is weakening.

Population agglomeration is the foundation of urbanization. However, lots of migrants in China returned to their hometowns. Housing prices and house ownerships are two crucial factors in determining whether floating population would return. Although a vast body of literatures have analyzed various factors in return migration as well as the effect of housing prices on migration and settlement intention, few studies have focused on return behaviors. Employing China Household Finance Survey, we examine the effect of housing prices and house ownerships on the return behavior of floating population. Results from IVProbit model show that (1) the increase in housing prices crowds out floating population to return; (2) owning houses in their host cities reduces the chance of return for the homeowners and weakens the crowdingout effect of high housing prices; (3) the effects of housing prices and house ownerships on return decision are varying among the locations and the scales of the host city. Our findings have important policy implications for advancing urbanization strategies.

Population urbanization and urban-rural income gap affect each other. Based on prefecture-level data of urbanization rate and urban-rural income ratio in mainland China, we examine this mutual impact by conducting three econometric models, including ordinary multiple linear regression (OLS), simultaneous equation model (SEM) and spatial simultaneous equation model (SSEM). We suggest that spatial simultaneous equation model (SSEM) should be used because of the simultaneity and spatial autocorrelation between urbanization rate and urban-rural income gap. The regression results show that the urbanrural income ratio decreases when the local and surrounding areas are more urbanized. And high urban-rural income ratios in surrounding areas inhibit the urbanization process in the local area. Moreover, economic development and the promotion of human capital contribute to higher urbanization level and lower urban-rural income ratio. Based on these results, policy implications are discussed on how to narrow the urban-rural income gap at the broad spatial level and to increase human capital through educational development.

Based on the 2000 and 2010 census data of Beijing-Tianjin-Hebei megacity regionthis paper uses the ESDA method to analyze the spatial pattern of urbanization rates as well as its changes at county level By applying Spatial Error Model and GWR method both global and local driving forces of urbanization are investigated in this region The main results are as follows The urbanization rate of Beijing-Tianjin-Hebei megacity region at county level manifests a significant pattern of spatial aggregation which is gradually strengthened The increase of urbanization rate shows a pattern of convergence and areas where the urbanization rate is high have positive impact on the nearby areas where the urbanization rate is low For areas where the urbanization rate is increased the distribution of high value of rural contribution share is similar to that of areas which are in low urbanization rate Economic level industrial structure medical and education level and terrain condition have significant effects on the urbanization level of Beijing-Tianjin-Hebei megacity region Each driving force has a unique distribution of incidence pattern for different areas．

Since China’ s reform and opening up，connections between the regions in China are getting increasingly closer，with more and more frequent population migration．The reason why people migrate from one region to another is because of the attraction of the inflow area．This paper uses the 6th national population census data and the attractiveness measurement indicator RIA to calculate the attraction index for China’ s 31 provinces．The result shows that the east coastal zone，which represented by Guangdong，Zhejiang，Shanghai， Jiangsu and Beijing，has the largest attraction for migrants．On the other hand，the far west region，defined as restricted development region，which represented by Gansu，Qinghai，Ningxia and Tibet，has the least attrac- tion for migrants．Policy implications are discussed regarding industrial upgrading，population control，environ- mental protection，and targeted poverty alleviation．

Based on the data of 2000 and 2010 population censuses in China，this paper investigates the spatial patterns of Chinese population mobility using spatial analysis methods．Visualized analysis and spatial autocorrelation analysis are conducted for intra- and inter-provincial population in-migration respectively at province，city and county levels．Results show that there is a significant trend of geographical concentration for inter-provincial migration from eastern coastal region to middle and western regions in China．Hotspots analysis verifies three nationwide agglomeration centers: Pearl River Delta，Yangtze River Delta and Beijing- Tianjin-Hebei Metropolitan Area．On these bases，this paper quantitatively identifies city attractiveness factors that respectively have impacts on intra－ and inter－provincial population in-migration at the city level，using ordinary multivariate regression and spatial regression models．Development of tertiary industry and local wage level both affect the choice of migration destinations for intra- provincial and inter- provincial floating population; local social public resources have significant impact on intra- provincial migration; high employment rate and high urbanization rate are“pulling”factors for inter-provincial migration．Policy implications are discussed．

This is a case study in which data are collected from Bijie in Guizhou Province and geographically weighted regression is performed,with comparison with OLS,to explore the influence of economic,social and natural factors on population density.Results demonstrate that economic and social factors have larger impact on population distribution than natural factors.Altitude does not influence population distribution significantly while slope does.There is negative correlation between population distribution and economic strength,urbanization level,transportation and terrain conditions.Medical conditions have positive influence on population distribution.Therefore in the future Bijie should enhance city and town construction,strengthen the ecological immigration and protect natural resource and environments to optimize population distribution.

Based on economic,social and environmental panel data of eight counties in Bijie Prefecture between 1987 to 2007,this article explored the impact of resource environment,economic level and social development on changes of population distribution.The findings are multifaceted.First,the population quantity and density in these eight counties have increased steadily with a similar growth pattern and trend,although the pace of growth varies,suggesting regional disparities.Second,the effect of natural environment on population redistribution has been weakened over time to a lesser extent,which indicates that natural factors have an ingrained impact on the changes of population distribution.Third,the effect of economic and social development,particularly GDP per capita and the quality of medical care,on the changes of population density has been strengthened.Finally,each county in Bijie Prefecture exhibits obviously distinctive characteristics in terms of the dynamic trend of population density,although they share same impact of resources environment,the social and economic development.

Based on ArcGIS as analytical tools and the 2000 census data,this research is carried out in county units. The result indicates that among principal function areas,key development zones have the highest population size while optimized key development zones the highest population density. Compared with limited development zones of lowest population quality,optimized development zones show highest population quality. As for age structure,optimized development zones reveal highest proportion of labor population. Further analysis demostrates that population migration does not follow the planning of principal function Areas. Current technical and cultural development may still not meet the requirement of principal function Areas planning. A large number of labors assemble in optimized development zones,which deviates from principal function Areas planning. In order to achieve regional population equilibrium,proper population and industrial policy should be implemented in different principal function Areas with consideration of regional advantadges. In addition,population policy should coordinate with other public policy.