Spatial patterns, driving forces, and urbanization effects of China&apos;s   internal migration: County-level analysis based on the 2000 and 2010   censuses

doi:10.1007/s11442-015-1165-z

CORC > 北京大学 > 城市与环境学院

	Spatial patterns, driving forces, and urbanization effects of China's internal migration: County-level analysis based on the 2000 and 2010 censuses
	Liu Tao ; Qi Yuanjing ; Cao Guangzhong ; Liu Hui
刊名	journal of geographical sciences
	2015
关键词	floating population migration urbanization urban system megacity region census China RURAL-URBAN MIGRATION INTERPROVINCIAL MIGRATION REGIONAL-DEVELOPMENT DECISIONS GEOGRAPHY
DOI	10.1007/s11442-015-1165-z
英文摘要	China has witnessed unprecedented urbanization over the past decades. The rapid expansion of urban population has been dominantly contributed by the floating population from rural areas, of which the spatiotemporal patterns, driving forces, and multidimensional effects are scrutinized and evaluated in this study by using the latest national censuses conducted in 2000 and 2010. Analysis based on the county-level data comes to conclusions as follows. The spatial pattern of floating population has remained stable over the first decade of the new century. The top 1% cities with the largest floating population received 45.5% of all migrants in China. As the rapid development of mega-city regions, the coastal concentration areas of floating population tended to geographically united as a whole, whereas the spatial distribution of migrants within each region varied significantly. The migrant concentration area in the Yangtze River Delta was the largest and its expansion was also the most salient. However, the floating population has growingly moved into provincial capitals and other big cities in the inland regions and its gravity center has moved northward for around 110 km during the study period. The spatial pattern of floating population has been formed jointly by the state and market forces in transitional China and the impacts of state forces have been surpassed by those of market forces in the country as a whole. The attractiveness of coastal cities and counties to the floating population comes mainly from the nonagricultural employment opportunities and public services, reflecting that long-distance and long-term migrants have moved coastward not only to gain employment but also to enjoy city life. By contrast, in the central and western regions, places with a higher economic development level and at a higher administrative level are more attractive to floating populations, demonstrating that the state remains to play an important role in allocating economic resources and promoting regional development in inland China. As the main body of new urban residents, the floating population has contributed substantially to the elevation of the urbanization levels of migrant-sending and -receiving places, by 20.0% and 49.5% respectively. Compared with extensively investigated interprovincial migrants, intra-provincial migrants have higher intention and ability to permanently live in cities and thus might become the main force of China's urbanization in the coming decades. The internal migration has also reshaped China's urban system in terms of its hierarchical organization and spatial structure.; Geography, Physical; SCI(E); 中国科技核心期刊(ISTIC); 中国科学引文数据库(CSCD); 0; 2; 236-256; 25
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/206225]
专题	城市与环境学院
推荐引用方式 GB/T 7714	Liu Tao,Qi Yuanjing,Cao Guangzhong,et al. Spatial patterns, driving forces, and urbanization effects of China's internal migration: County-level analysis based on the 2000 and 2010 censuses[J]. journal of geographical sciences,2015.
APA	Liu Tao,Qi Yuanjing,Cao Guangzhong,&Liu Hui.(2015).Spatial patterns, driving forces, and urbanization effects of China's internal migration: County-level analysis based on the 2000 and 2010 censuses.journal of geographical sciences.
MLA	Liu Tao,et al."Spatial patterns, driving forces, and urbanization effects of China's internal migration: County-level analysis based on the 2000 and 2010 censuses".journal of geographical sciences (2015).