Research on Geospatial Association of the Urban Agglomeration around the South China Sea Based on Marine Traffic Flow

Abstract

Studying the geospatial association within the urban agglomeration around the South China Sea can provide a basis for understanding the internal development of the China-Association of Southeast Asian Nations (ASEAN) Free Trade Area (CAFTA) and provide ideas for promoting economic and trade cooperation among cities in the region. The purpose of this paper was to reflect the characteristics of the urban agglomeration association network based on big traffic data. Based on trajectory data mining and complex network analysis methods, the automatic identification system (AIS) data was used to construct the traffic flow association network of the urban agglomeration around the South China Sea and then analysis and evaluation were carried out in three aspects: Spatial distribution characteristics of marine traffic flow, analysis of spatial hierarchy and internal difference analysis of the urban agglomeration. The results show the following: (1) The distribution of marine traffic flow within the urban agglomeration around the South China Sea is characterized by polarization and localization and shows a specific power-law distribution; (2) there is a close relationship within the urban agglomeration and the core urban and the marginal urban agglomerations were apparent; (3) subgroup division of urban agglomeration around the South China Sea shows an evident geographic agglomeration phenomenon and there were significant differences between the level of economic development among subgroups; and (4) relative to static factors such as population size and economic aggregate, dynamic flow of information and capital traffic flow plays a more important role in the spatial correlation between cities. Strengthening the links among the three layers of core-intermediate-edge cities through trade and investment means enhancing cooperation among cities within the urban agglomeration and ultimately promoting sustainable regional development.