基于多源数据的武汉市多中心空间结构识别

doi:10.18306/dlkxjz.2019.11.003

Abstract

Abstract:

Examining the spatial agglomeration level and hierarchy differences of various urban elements and the distribution of diverse functional centers is significant for guiding the development and regulating the plans of the polycentric spatial structure of cities. City center is represented by various urban elements. It is difficult to fully identify and recognize the urban spatial structure by using a single data source. Thus, combining different types of data to deeply understand the status of urban internal development is necessary. This study used points of interest (POI), nighttime light, and road network data and adopted the local contour tree algorithm to identify the polycentric spatial structure in Wuhan City. The results show that: 1) The overall agglomeration level of various urban elements in the three towns of Wuhan is not balanced—the agglomeration level is higher in Hankou and Wuchang, and lower in Hanyang. 2) The development of the core area of Wuhan City is relatively mature. In the process of outward expansion, various urban elements tend to aggregate in local areas to form an urban center. 3) Considering the zonal development of Wuhan City, the functional distribution model of business-housing-industry corresponding to the ring roads of the city center was gradually established. The inner ring and the second ring regions have formed stable business service centers. Representative residential centers appeared in the multifunctional clusters near the second ring road. Similarly, Zhuankou and Wugang outside the third ring road led the development of industries, and are typical industrial centers.

Key words: polycentric spatial structure, POI, nighttime light, road network, local contour tree algorithm, Wuhan City

MAO Shuaiyong, JIAO Limin, XU Gang, LI Zehui. Identification of the polycentric spatial structure in Wuhan City based on multisource data[J].PROGRESS IN GEOGRAPHY, 2019, 38(11): 1675-1683.

Figures/Tables 6

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Identification of the polycentric spatial structure in Wuhan City based on multisource data

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