Multi-dimensional Characteristics and Pattern Recognition of Urban Form:A Case Study of Natural Cities in China,the United States and Europe
Objectives:Analyzing urban form patterns and their differentiation from a multi-dimensional and large-scale perspective is the basis for studies of urban patterns,processes and effects,but the subject re-mains a great challenge.Methods:We construct a multi-dimensional characterization system of urban form by integrating urban physical space and social space perspectives,which include indices on land use,building distribution,transport network,population distribution and urban function distribution.We further propose a pattern identification method based on principal component analysis and clustering algorithm.Results:Taking 2 475 natural cities in China,the United States,and Europe as examples,we identify six major urban morphological patterns which include high-density(HD),high-aggregation with low-density(HALD),low-aggregation with low-density(LALD),multi-center with high-concentration(MCHC),multi-center with high-mixed(MCHM)and multi-center with low-mixed(MCLM).Chinese cities are mostly HD cities and MCHC cities,and the distribution of patterns has a significant difference between northwest and south-east areas.In the United States,there are mostly HALD cities,LALD cities and MCLM cities,while showing difference between east and west areas.The cities in Europe are mostly MCHM cities with a few other types of cities along the western and southern coastlines.Conclusions:Multi-dimensional charac-terization can classify cities into categories in a comprehensive,refined and reasonable way,and urban form patterns can provide support for cross-regional urban comparison studies,urban pattern and process ef-fects,and urban simulation.
urban formurban classificationtransnational city comparisoncluster analysis
NETL
NSTL
万方数据
