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《城市交通》杂志
双语出版
20200402-Urban Vitality Zone and Central District Identification Based on Big Data_ A Case Study in Guangzhou City
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SONG Cheng, CHEN Jiachao, LI Caixia, AI Guantao
Guangzhou Transport Planning Research Institute, Guangzhou 510030, Guangdong Province, China

Abstract: The urban vitality zone and the central district can offer important basic information to understand and research the city, which can also serve as the premise of making urban management and control polices. It is difficult to define the boundary of an urban vitality zone and a central district accurately depending on traditional survey data, which is usually the qualitative analysis. The emergence of big data provides conditions for boundary identification of urban functional areas. Based on cellular signaling, Internet location data, Point of Interest (POI) and other multi-source data, this paper develops two static indicators (comprehensive population density and POI density) as well as two dynamic indicators (urban center accessibility and point density of business and leisure activities) so as to comprehensively identify the urban vitality zone and central district boundaries. The combination of dynamic and static indicators overcomes the limitations of boundary identification with single index or only static indexes. Taking Guangzhou as an example, the paper demonstrates the practicability of the method and concludes that the scope of Guangzhou’s vitality zone and central district is equivalent to that of world-class international cities.

Keywords: cellular signaling data; POI; vitality zone; central district; boundary identification; kernel density; Guangzhou