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Study On The Characteristics And Driving Forces Of Urban Human-land Allometric Growth In Central China

Posted on:2024-09-18Degree:MasterType:Thesis
Country:ChinaCandidate:M Q XuFull Text:PDF
GTID:2557307106953569Subject:Geography
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With the continuous promotion of the urbanization process,the scale of urban land expands accordingly,and the conflict between urban population and land becomes more and more obvious,the study of the relationship between urban expansion and population growth can make urban land more scientific and rational,to avoid the chaotic and disorderly,unbalanced and insufficient development of the city in the process of development due to the problems of land,and can give the relevant departments a reference to analyze the future trend of urban development and formulate urban planning.It is also important in regulating the economic structure and transforming the economic development mode.In this paper,the coefficients of the growth rate of people and land from 2000 to 2020 were calculated for 87 cities in six central provinces of China based on the model of the growth rate of people and land,and the coordination of people and land in the study area was analyzed accordingly.Comparing the current situation of land expansion and population growth of 87 cities in six central provinces in different periods,it can be seen that during the 20 years from 2000 to 2020,the coordination degree of people-land in 87 cities in six central provinces is generally dominated by significant population growth,among which the first 10 years are dominated by a contraction of people-land,while the second 10 years are dominated by significant population growth,which is a more obvious change in terms of period.In terms of the number of cities,the number of cities with basic human-land harmony and significant land expansion increased in the second decade compared to the first decade,but overall,there were few cities with basic human-land harmony and significant land expansion in both the first and second decades.The number of cities with significant population growth increased in the second decade compared to the first decade,but overall the number of cities was moderate.In addition,the distribution of all types of cities in terms of spatial location is more variable.Secondly,the spatial correlation of the relationship between the anisotropic growth coefficients of 87 cities in the six central provinces from 2000 to 2020 is analyzed.87 cities in the six central provinces from 2000 to 2010 show a weak spatial autocorrelation,and the cities belonging to the same type of anisotropic growth are distributed in a weak aggregation pattern;while the anisotropic growth coefficients of 87 cities in the six central provinces from 2010 to 2020 show a spatial The cities in this period explore their own urban population and land development paths,so the synergy effect among cities is not strong,and each city develops more according to its own actual situation.From the overall perspective of 2000-2020,the anisotropic growth coefficients of 87 cities in six central provinces show a positive spatial correlation,and the correlation is greater than that of 2000-2010,and the cities are concentrated in spatial distribution,and the cities that fall into the same category of anisotropic growth type are distributed in an aggregated trend.On this basis,multiple linear regression model,geographically weighted regression model,spatial lag model and spatial error models are established to investigate the driving factors influencing the anisotropic growth coefficient and the direction and intensity of each driving factor,and the results of each model are compared and analyzed.By comparing the regression coefficients of each influencing factor in each city,it can be concluded that the influence of each factor on the growth coefficient of anisotropy varies in different cities of different sizes and degrees of influence.Among them,GDP,patch density(PD),and Shannon diversity index(SHDI)all have significant effects on the anisotropic growth coefficient in several models mentioned above.Finally,according to the analysis of the results of the six provinces in the central urban development of the corresponding countermeasures and recommendations.
Keywords/Search Tags:Man-land relationship, Allometric growth, Multiple linear regression, Spatial lag model, Spatial Error Model, Geographically weighted regression
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