Identification of the urban functional regions considering the potential context of interest points

doi:10.11947/j.AGCS.2020.20190315

Abstract

Abstract: The exploration of urban functional structure plays an important role in understanding urban and urban planning. POI(point of interest) data, as a representative of urban facilities, is widely used to extract urban functional areas. In the past, most of the researches on urban functional areas only considered POI statistical information. However, they ignored the abundant spatial distribution characteristics of POI, which are closely related to regional functions. Therefore, we firstly use spatial co-location pattern mining to mine the potential context of POI, extract the spatial distribution information of POI, construct regional feature vectors, and carries out the regional clustering through the clustering algorithm. Then we use the POI class ratio and residents’ travel characteristics to identify the clustering results. We experimented our method on the core urban functional areas of Beijing, the results, which were verified with Baidu Map and residents’ travel characteristics, showed that they can identify urban functional areas with obvious characteristics, such as mature entertainment business areas, science and education cultural areas, residential areas, etc. We also proved the superiority of our method compared with the LDA method based on POI semantic information and the Word2Vec method considering the linear spatial relationship of POI.

Key words: urban functional area identification, contextual relationship, point of interest, spatial co-location mode, Beijing

CLC Number:

P208

CHEN Zhanlong, ZHOU Lulin, YU Wenhao, WU Liang, XIE Zhong. Identification of the urban functional regions considering the potential context of interest points[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(7): 907-920.

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