基于互联网大数据的区域多层次空间结构分析研究

doi:10.3724/SP.J.1047.2016.00719

Abstract

Abstract:

With the development of Information and Communication Technology (ICT), big data is now becoming an important tool to carry on researches in many fields. In the domain of human geography, big data technology has gained more and more attention, and there are extensive studies carried out which could be categorized into three groups of research hotspots: the residential behavioral spatial pattern, the urban space and the regional structure. But few researches have explored the regional hierarchical spatial structure systematically based on the big data, and the relevant researches are primarily based on the survey data, which has a bottleneck towards the volume and the detailed micro-data acquisition. This study combined the internet big data mined from internet with the GDP and the spatial traffic network data, etc. to identify the regional spatial structure. The gathered data was categorized into three categories: the point data, the line data and the polygon data. They are used to specify the urban overall capacity and the intensity of interactions between city pairs and the serving area respectively. Based on the obtained data, an algorithm was developed to identify the hierarchical regional structure. This method was applied to the Beijing-Tianjin-Hebei region. And a hierarchical regional structure was demonstrated by a multi-way tree created with this algorithm. The established multi-way tree identifies a regional urban ranking system in detail and can be of great help to decision makers in delineating the regional spatial policies. The results shows that Beijing which has the highest overall capacity becomes the core city (root node) and has the largest serving area, but the matured secondary cities around Beijing are still expected to share Beijing's serving functions, and there is a development inequality existing between the north and south part of this region. This study provides a good reference to researches in the domain of human geography with the application of big data.

Key words: big data, inter-city relation, centrality, hierarchical regional structure, Beijing-Tianjin-Hebei region

NIU Fangqu,LIU Weidong. Identifying the Hierarchical Regional Spatial Structure Using Internet Big Data[J].Journal of Geo-information Science, 2016, 18(6): 719-726.DOI:10.3724/SP.J.1047.2016.00719

Figures/Tables 8

Fig.1

Fig.2

Tab.1

Weights of the evaluation indices for city′s overall capacity

评价指标	权重 $w ′ j$
互联网大数据	0.432
POI	0.230
GDP	0.338

Tab.1

Fig.3

Tab.2

Weights of the evaluation indices for city′s socio-economic contacts

评价指标	权重 $w ′ j$
文本大数据	0.273
公路运力	0.353
铁路运力	0.357
交通可达性	0.016

Tab.2

Fig.4

Fig.5

Fig.6

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Identifying the Hierarchical Regional Spatial Structure Using Internet Big Data

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