Urban Functional Area Identification Method Based on Mobile Big Data

doi:10.16182/j.issn1004731x.joss.19-FZ0272

Abstract

Abstract: With the rapid development of urbanization, the function of urban land is constantly evolving. It is of great significance to identify urban functional areas in real time and accurately. In recent years, accompanied by the popularity of smart phones and the rapid development of the Internet, mobile phones have become sensors of human activities. In this paper, a method of urban functional area identification based on time series mobile phone data mining and POI semantics analysis is proposed. The time series feature of remaining mobile phone positioning is extracted facing block scale. And a FCM clustering algorithm based on this feature is constructed. Combining the point density distribution of POI in different regions, the functional attributes of clustering results are analyzed and explained. The experimental results show that the method basically realizes the identification of urban functional area.

Key words: mobile big data, functional area identification, POI, residual mobile positioning, FCM clustering algorithm

CLC Number:

TP391.9

Xiao Di, Zhang Xiaoyong, Hu Yang. Urban Functional Area Identification Method Based on Mobile Big Data[J]. Journal of System Simulation, 2019, 31(11): 2281-2288.

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