基于GIS的社会统计数据空间化处理方法  

METHOD OF PIXELIZING SOCIAL STATISTICAL DATA BASED ON THE GIS

作　　者：闫庆武[1] 卞正富[1] 

机构地区：[1]中国矿业大学环境与测绘学院

出　　处：《云南地理环境研究》2007年第2期92-97,共6页Yunnan Geographic Environment Research

基　　金：全国优秀博士论文基金资助(200044).

摘　　要：社会统计数据的空间化是当前地理科学和社会科学共同研究的热点问题之一,根据社会统计数据的特点可以将其分为和值(extensive)变量型统计数据和均值(intensive)变量型统计数据两种类型。分析了这两类社会统计数据在区域拆分与合并时的特点,并尝试将网格单元面积权重内插(GCAWI)法引入社会统计数据的空间化的工作中,提出了确定网格单元大小的原则和采用图像平滑技术改进空间化结果的方法。以徐州市人均GDP数据(均值变量型统计数据)空间化为研究实例,采用网格单元面积权重内插法实现了徐州市人均GDP数据的空间化,而且运用图像平滑技术得到了比较满意的结果。Pixelizing social statistical data is an important problem which is studied in both geography and sociology. By its characteristic, social statistical data can be divided into two kinds, extensive statistical data and intensive statistical data. How to compute of these two kinds data when region divided or merged is studied. A method name as grid cells＇ areal weighted interpolation （GCAWI） is introduced to the work of pixelizing social statistical data. The principles of determining grid cells＇ size are pointed out. A method of neighborhood averages is tried to improve the result of pixelizing. Pixelizing per GDP data with the method of GCAWI in Xuzhou is taken as an example. With the methods of GCAWI and neighborhood averages satisfactory result is obtained.

关 键 词：区域统计数据 空间化 面积权重内插法 图像平滑 GIS 

分 类 号：X87[环境科学与工程—环境工程]