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基于24个空间单元的统计数据和实地调查资料,运用BP神经网络模型和ESDA方法,在GIS技术支持下,定量评价吉林省中部粮食主产区城乡关联度,并分析各县域城乡关联状态与空间差异。研究结果表明:(1)区域城乡综合关联Moran’s I指数仅为-0.1205,表明各县域城乡关联呈分散状态;经济、社会和基本建设非均衡发展是制约城乡协调发展的关键因素。(2)区域城乡关联的区域差异明显,地级市辖区城乡关联性显著高于各县(县级市);经济、社会和基本建设关联性分别呈现“圈层”、“十字型”和“块状”的空间结构。(3)区域城乡关联表现出较弱的集聚趋势。空间差异较小的县域主要沿哈大线呈带状分布,空间差异较大的县主要分布在5个地级市辖区和东南部低山丘陵区;经济、社会和基本建设关联性分别表现为弱扩散、强极化和强扩散状态。
Based on the statistical data and field survey data of 24 spatial units, the BP neural network model and ESDA method were used to quantitatively evaluate the correlation degree between urban and rural areas in the main grain-producing areas in central Jilin Province with the support of GIS technology. difference. The results show that: (1) The Moran's I index of regional integrated urban-rural correlation is only -0.1205, indicating that the correlation between urban and rural areas in each county is decentralized; the unbalanced development of economy, society and infrastructure is the key factor restricting the coordinated development of urban and rural areas. (2) The regional differences between urban and rural areas in the region are obvious, and the correlation between urban and rural areas in prefecture-level cities is significantly higher than that in all counties (county-level cities); the correlations of economy, society and infrastructure show “circle”, “ ”And “ block ”space structure. (3) The relationship between urban and rural areas in the region shows a weak tendency of agglomeration. The counties with smaller spatial differences are mainly zonal distributed along the Ha-Da Line and the counties with large spatial differences are mainly distributed in five prefecture-level cities and hilly areas in the southeast. The correlations of economy, society and infrastructure are respectively Weak diffusion, strong polarization and strong diffusion state.