基于多尺度的中部地區(qū)經(jīng)濟(jì)發(fā)展空間相關(guān)性分析
[Abstract]:The spatial relevance of economic development, as well as economic differences, has attracted more and more attention from all walks of life. Both at home and abroad, great achievements have been made in the research of spatial correlation methods and the innovation and application of spatial autocorrelation analysis methods in China. In the research of spatial correlation at home and abroad, the spatial scale is mostly focused on the analysis of the single spatial scale, and for the spatial weight matrix, a single weight matrix is often chosen, generally the adjacent spatial weight matrix is the majority. In this paper, taking the central region as the research object, we select the city scale and the county level, and select the adjacency matrix and the distance matrix to analyze the spatial correlation of the economic development in the central region. In this paper, the global spatial correlation analysis and local spatial correlation analysis of the double scale and double spatial weight matrices are carried out on the per capita GDP data of the central region from 1990 to 2010. The results of the analysis show that the development of the city scale economy based on the adjacency matrix and the distance matrix shows the trend of global positive correlation, global negative correlation and global positive correlation. The change of global Moran exponent based on distance matrix is greater than that of global Moran index based on adjacent matrix in the city scale, but there is a spatial positive correlation between the adjacent matrix and the development of county scale economy based on distance matrix. And the development of county scale economy based on distance matrix is highly positive correlation; From the point of view of local correlation, the local G index hot spots based on adjacency matrix and distance matrix are scattered and less, but for county scale, whether adjacent matrix or distance matrix, the local G index hot spots are scattered and less, and for county-level scale, whether adjacent matrix or distance matrix, Hot spots are concentrated and mainly distributed around provincial capitals. The local G exponent based on distance matrix is not sensitive to the cold point distribution, while the local G exponent based on the adjoining matrix reflects the distribution of the cold point region at the junction of the provinces and parts of Hunan Province and Jiangxi Province.
【學(xué)位授予單位】:南昌大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2013
【分類號(hào)】:F129.9
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