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The Influence Mechanism of Urban Spatial Structure on Urban Vitality Based on Geographic Big Data: A Case Study in Downtown Shanghai
How can we construct the multidimensional evaluation framework of urban vitality from the perspective of urban spatial structure? Under the current intensity of land development, does the population density in the downtown area of Shanghai have the potential to be improved? Can a subdistrict be an appropriate spatial scale for evaluating urban vitality in central Shanghai? First, based on multisource geospatial big data, a comprehensive theoretical framework of the influence mechanism of urban spatial structure on urban vitality was constructed from the three dimensions of population, land use, and traffic, and 11 indicators were selected to form an evaluation index system. Second, the influence mechanism of urban spatial structure on urban vitality was analyzed from the six aspects of economic vitality, cultural vitality, quality of life, social governance, air quality, and nocturnal vitality, using binary spatial correlation analysis and a regression model based on eigenvector space filtering (ESF). The results show the following: (1) According to the combined impact analysis, the job–housing balance degree, floor area ratio, open space ratio, and road network density are positively correlated with urban vitality, while population density, land use mix degree, average block area, rail transit station density, and rail transit station accessibility are negatively correlated with urban vitality. (2) The correlation between population density and the urban comprehensive vitality index is related to the floor area ratio. Under the current land development intensity, the population density of the central urban area of Shanghai has approached the theoretical “ceiling”. (3) Different spatial scales have different effects on urban vitality. Finally, some policy suggestions are proposed to optimize the urban spatial structure and enhance urban vitality.
The Influence Mechanism of Urban Spatial Structure on Urban Vitality Based on Geographic Big Data: A Case Study in Downtown Shanghai
How can we construct the multidimensional evaluation framework of urban vitality from the perspective of urban spatial structure? Under the current intensity of land development, does the population density in the downtown area of Shanghai have the potential to be improved? Can a subdistrict be an appropriate spatial scale for evaluating urban vitality in central Shanghai? First, based on multisource geospatial big data, a comprehensive theoretical framework of the influence mechanism of urban spatial structure on urban vitality was constructed from the three dimensions of population, land use, and traffic, and 11 indicators were selected to form an evaluation index system. Second, the influence mechanism of urban spatial structure on urban vitality was analyzed from the six aspects of economic vitality, cultural vitality, quality of life, social governance, air quality, and nocturnal vitality, using binary spatial correlation analysis and a regression model based on eigenvector space filtering (ESF). The results show the following: (1) According to the combined impact analysis, the job–housing balance degree, floor area ratio, open space ratio, and road network density are positively correlated with urban vitality, while population density, land use mix degree, average block area, rail transit station density, and rail transit station accessibility are negatively correlated with urban vitality. (2) The correlation between population density and the urban comprehensive vitality index is related to the floor area ratio. Under the current land development intensity, the population density of the central urban area of Shanghai has approached the theoretical “ceiling”. (3) Different spatial scales have different effects on urban vitality. Finally, some policy suggestions are proposed to optimize the urban spatial structure and enhance urban vitality.
The Influence Mechanism of Urban Spatial Structure on Urban Vitality Based on Geographic Big Data: A Case Study in Downtown Shanghai
Danxuan Liu (author) / Yishao Shi (author)
2022
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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