| Since the middle of 1990 s, along with the rapid development of urbanization, the contradiction between speed and quality of urbanization has caused wide public concern because of the phenomenon of ignoring the population urbanization in the blind pursuit of the scale urbanization. The human-based ideology has to be embedded into each link in the processes of urbanization. On the basis of this, it is particularly important at the present stage of urbanization to integrate the urbanization development of cities and towns into an interactional and coordinated whole. Counties can be regarded as the connection of urban areas and rural areas, namely, an important node in urban system. So the county’s population urbanization is the indispensable component in the system of urbanization.Shanxi Province is an important resource-based region in our country. The research group on the strategy of urbanization development within Shanxi Province put forward that “the county is the key link to promote the development of regional urbanization, so we should facilitate and guide actively the agglomeration of the quality factors and preponderant resource to counties. Thus, the economic growth pole at the county’s level will form gradually.” Therefore, based on the study of spatial patterns and influencing factors of 96 counties’ population urbanization in Shanxi Province, this paper provides new ideas and theoretical support for the differentiation Strategy of population urbanization.Based on existing literature and relevance theory, this thesis analyzes the urban system’s structure in Shanxi by fractal approach. Then exploratory spatial data analysis(ESDA) is used to study the temporal and spatial evolution patterns of population urbanization of 96 counties in Shanxi Province from 2000 to 2010 and reveal the characteristics and heterogeneity on population urbanization across county areas. Furthermore, adopting global regression analysis(ordinary least squares, spatial lag model and spatial error model) and local regression analysis(geographically weighted regression model) analysis factors affecting the pattern evolution of population urbanization. Finally, some suggestions are provided on basis of the features of different regions.The results show that:(1) Urban system’s structure of Shanxi Province tends to be more complete gradually. The number of medium-sized cities has increased, and county-level cities have become a strong power to develop and complete the urban system of Shanxi.(2) The county’s population urbanization in Shanxi presents an obvious trend of agglomeration development. The population urbanization of northern and central regions show a agglomeration pattern of high values, but the cluster range has narrowed. At the same time, the high level agglomeration areas have a trend moving to central areas gradually. Conversely,the edge regions of Shanxi Province show a low level agglomeration, suggesting that the appeal to floating population is not strong. The radiation effect of municipal districts on surrounding county area is so insufficient that it is difficult to drive the long-term development of entire region.(3) Spatial autocorrelation of county’s population urbanization pattern in Shanxi province exists, so the result of spatial econometrics model in which spatial factors are considered is more appropriately to meet the need of practical application than ordinary least squares, and outcomes of spatial lag model has more significant goodness-of-fit than spatial error model. Compared to global regression analysis, geographically weighted regression model(GWR) reveals the existence of spatial heterogeneity of regression coefficients. The results of SLM and GWR indicate that Per Capita GDP, the per capita disposable income of urban residents, the secondary industry and tertiary industry’s value-added, total retail sales of consumer goods in urban areas to all counties come into positive effect; the first industry’s value-added, Rural per capita net income and Theil index is negative effect. In addition, GWR is a variable coefficient regression analysis method,so the regression coefficients of each county are not identical. Coefficient of fixed assets investments, Coal sales and Traffic conditions index can be positive or negative in GWR. But in SLM, coal sales have a positive impact on county’s population urbanization, and the correlation between fixed assets investment, traffic condition index and county’s population urbanization in Shanxi Province is not significant. |
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