人口空间分布的异质性测量

Heterogeneity measurement of population distribution

基于数据异质性测量理论,提出了人口空间分布异质性测量的方法,即人口空间分布的相对异质性指数(GPD)。接着以江苏省为研究区域,采用GPD指标对江苏省2005年的人口空间分布的异质性进行了测度。结果表明:基于地级市行政单元的人口空间分布的异质性较小,而基于县级行政单元的人口空间分布的异质性较大;人口空间分布异质性大的地区主要分布在苏南地区,而异质性小的地区主要分布在江苏东北部。采用Moran散点图和Local Moran's I统计量对江苏省县级单元的人口密度分布的局域空间自相关进行分析,结果显示:人口空间分布的异质性与人口密度空间分布的聚集性特征密切相关,异质性大的地区一般出现在人口密度"低-高"或"高-低"聚集的地区,异质性小的地区一般出现在"低-低"或"高-高"聚集的地区。

Heterogeneity is an important characteristic of geographical system, which is receiving more and more attention because of its determining role in geographical pattern and process. Based on the theory of data heterogeneity measurement, the paper put forward a Gini index of population distribution （GPD）, which can be used to measure the heterogeneity of population distribution. Taking advantage of a GIS data set of county-level admin- istrative regions census data in 2005 in Jiangsu, this research uses the GPD index to analyze the heterogeneity of population distribution in Jiangsu. By computing the GPD index of Jiangsu in 2005 at county and city levels, the conclusions can be drawn as follows. Heterogeneity of population distribution at city level is small, while that at county level is big. Heterogeneity of population distribution in southern Jiangsu is bigger than that in northeastern Jiangsu. Moran scatter plot and local Moran＇s I are employed to study local spatial autocorrelation of population density distribution in Jiangsu based at county level. The results indicate that the heterogeneity of population distribution in low-high and high-low spots is big, while that in high-high and low-low spots is small. The above results are consistent with the actual conditions, indicating that the GPD index is effective.