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以浙江省69个县域行政单元为研究对象,根据城乡关联内涵及特点,构建综合评价指标体系,运用主成分分析法和探索性空间数据分析方法,定量测度浙江省2001~2011年县域城乡关联性,并分析城乡关联时空演变特征及空间关联状态。研究表明:(1)各县域城乡关联综合得分均出现不同程度的增长,表明区域城乡经济社会统筹得到优化;(2)城乡关联空间存在差异,东部沿海平原县域城乡关联性普遍高于西部低山丘陵县域,地级市辖区城乡关联性明显高于各县(县级市);(3)城乡关联表现出较强的空间集聚特性,城乡关联较强的县域主要分布于长三角环杭州湾地区,城乡关联较弱的县域则集中分布于浙西南低山丘陵区域。在此基础上,提出经济水平发展、交通设施改善、要素联系强化、政策制度优化等4因素为浙江省城乡关联演变的主要动力机制。
Taking the administrative units in 69 counties of Zhejiang Province as the research object and according to the connotation and characteristics of the correlation between urban and rural areas, this paper constructs a comprehensive evaluation index system and uses principal component analysis and exploratory spatial data analysis methods to quantitatively measure the correlation between urban and rural areas in Zhejiang Province from 2001 to 2011 , And analyzes the temporal and spatial evolution of urban-rural correlation and spatial correlation. The results show that: (1) The comprehensive scores of the correlation between urban and rural areas in all counties have increased to some extent, indicating that the economic and social overall planning of urban and rural areas in the region has been optimized; (2) There are differences in the spatial correlation between urban and rural areas; the correlation between urban and rural areas in eastern coastal plains is generally higher than that in western low mountains The correlation between urban and rural areas in hilly county and prefecture-level municipal districts is significantly higher than that in all counties (county-level cities); (3) The urban-rural correlation shows strong spatial agglomeration characteristics, and the counties with strong urban-rural connection are mainly distributed in the Hangzhou Bay area , The counties with weak urban-rural connection are concentrated in the hilly area of southwest Zhejiang. On this basis, the author puts forward four main driving forces for the evolution of urban-rural linkages in Zhejiang Province: economic development, improvement of transport facilities, strengthening of factors and policy system optimization.