Quantifying the aggregation patterns of urban population, economic activities, and land use are essential for understanding compact development, but little is known about the difference among the distribution characte...Quantifying the aggregation patterns of urban population, economic activities, and land use are essential for understanding compact development, but little is known about the difference among the distribution characteristics and how the built environment influences urban aggre-gation. In this study, five elements are collected in Wuhan, China, namely population density, floor area ratio, business POIs, road network and built-up area as the representative of urban population, economic activities and land use. An inverse S-shape function is employed to fit the elements’ macro distribution. An aggregation degree index is proposed to measure the aggregation level of urban elements. The kernel density estimation is used to identify the aggregation patterns. The spatial regression model is used to identify the built environment factors influencing the spatial distribution of urban elements. Results indicates that all urban elements decay outward from the city center in an inverse S-shape manner. The business Pointof- Interest (POI) density and population density are highly aggregated;floor area ratio and road density are moderately aggregated, whereas the built-up density is poorly aggregated. Three types of spatial aggregation patterns are identified: a point-shaped pattern, an axial pattern and a planar pattern. The spatial regression modeling shows that the built environment is associated with the distribution of the urban population, economic activities and land use. Destination accessibility factors, transit accessibility factors and land use diversity factors shape the distribution of the business POI density, floor area ratio and road density. Design factors are positively associated with population density, floor area ratio and built-up density. Future planning should consider the varying spatial concentration of urban population, economic activities and land use as well as their relationships with built environment attributes. Results of this study will provide a systematic understanding of aggregation of urban land use, popula-tion, and economic activities in megacities as well as some suggestions for planning and compact development.展开更多
The primary object of this paper is to examine the spatial-temporal pattern evolution of manufacturing geographical agglomeration of the old industrial base.Industrial spatial agglomeration index and concentration rat...The primary object of this paper is to examine the spatial-temporal pattern evolution of manufacturing geographical agglomeration of the old industrial base.Industrial spatial agglomeration index and concentration ratio are used in this paper.Multiple linear regression models are also applied to try to explore the internal driving mechanisms on manufacturing geographical agglomeration.The results show that:1) the manufacturing agglomeration degree of Jilin Province is increasing gradually.The spatial polarization structure is visible;and the central region is the agglomeration area,in addition,the manufacturing industries of Changchun Proper present a trend of dispersion;2) the structure of manufacturing industries has changed,and the concentration ratio of labor-intensive manufacturing industry is declining,while the proportions of technology-intensive and capital-intensive manufacturing industry are relatively rising;3) marketing level,location accessibility,labor resources,capital,science and technology innovation capability,scale economy and the level of globalization affect manufacturing agglomeration with different degree.There are significant differences of the effects about employment,technology,the quality of residents and the export-oriented market on the industrial concentration ratio;4) in the future,the impact of policy and institution,export-oriented market and quality of resident on manufacturing geographical agglomeration pattern will be more profound.展开更多
基金The research was funded by the National Natural Science Foundation of China(grant number 41971368).
文摘Quantifying the aggregation patterns of urban population, economic activities, and land use are essential for understanding compact development, but little is known about the difference among the distribution characteristics and how the built environment influences urban aggre-gation. In this study, five elements are collected in Wuhan, China, namely population density, floor area ratio, business POIs, road network and built-up area as the representative of urban population, economic activities and land use. An inverse S-shape function is employed to fit the elements’ macro distribution. An aggregation degree index is proposed to measure the aggregation level of urban elements. The kernel density estimation is used to identify the aggregation patterns. The spatial regression model is used to identify the built environment factors influencing the spatial distribution of urban elements. Results indicates that all urban elements decay outward from the city center in an inverse S-shape manner. The business Pointof- Interest (POI) density and population density are highly aggregated;floor area ratio and road density are moderately aggregated, whereas the built-up density is poorly aggregated. Three types of spatial aggregation patterns are identified: a point-shaped pattern, an axial pattern and a planar pattern. The spatial regression modeling shows that the built environment is associated with the distribution of the urban population, economic activities and land use. Destination accessibility factors, transit accessibility factors and land use diversity factors shape the distribution of the business POI density, floor area ratio and road density. Design factors are positively associated with population density, floor area ratio and built-up density. Future planning should consider the varying spatial concentration of urban population, economic activities and land use as well as their relationships with built environment attributes. Results of this study will provide a systematic understanding of aggregation of urban land use, popula-tion, and economic activities in megacities as well as some suggestions for planning and compact development.
基金Under the auspices of National Natural Science Foundation of China(No.41371135)Science and Technology Guide Plan Soft Science Project of Jilin Province(No.20120635)
文摘The primary object of this paper is to examine the spatial-temporal pattern evolution of manufacturing geographical agglomeration of the old industrial base.Industrial spatial agglomeration index and concentration ratio are used in this paper.Multiple linear regression models are also applied to try to explore the internal driving mechanisms on manufacturing geographical agglomeration.The results show that:1) the manufacturing agglomeration degree of Jilin Province is increasing gradually.The spatial polarization structure is visible;and the central region is the agglomeration area,in addition,the manufacturing industries of Changchun Proper present a trend of dispersion;2) the structure of manufacturing industries has changed,and the concentration ratio of labor-intensive manufacturing industry is declining,while the proportions of technology-intensive and capital-intensive manufacturing industry are relatively rising;3) marketing level,location accessibility,labor resources,capital,science and technology innovation capability,scale economy and the level of globalization affect manufacturing agglomeration with different degree.There are significant differences of the effects about employment,technology,the quality of residents and the export-oriented market on the industrial concentration ratio;4) in the future,the impact of policy and institution,export-oriented market and quality of resident on manufacturing geographical agglomeration pattern will be more profound.