地理学报 ›› 2011, Vol. 66 ›› Issue (12): 1597-1606.doi: 10.11821/xb201112002

• 理论与方法研究 • 上一篇    下一篇

空间自相关的可塑性面积单元问题效应

陈江平, 张瑶, 余远剑   

  1. 武汉大学遥感信息工程学院, 武汉 430079
  • 收稿日期:2011-04-07 修回日期:2011-08-17 出版日期:2011-12-20 发布日期:2012-01-19
  • 作者简介:陈江平(1975- ), 女, 湖北洪湖人, 博士, 副教授.研究方向为空间分析, 数据挖掘等.E-mail: chenjp_lisa@163.com
  • 基金资助:

    国家自然科学基金青年科学资金项目(40801152);教育部留学科研基金项目(213153249)

Effect of MAUP in Spatial Autocorrelation

CHEN Jiangping, ZHANG Yao, YU Yuanjian   

  1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
  • Received:2011-04-07 Revised:2011-08-17 Online:2011-12-20 Published:2012-01-19
  • Supported by:

    National Natural Science Foundation of China--Youth Science Fund Project, No.40801152;Scholarship Research Fund Project, Ministry of Education, No.213153249

摘要: 可塑性面积单元问题(modifiable areal unit problem,MAUP) 效应是对空间数据分析结果产生不确定性影响的主要原因之一,在空间自相关分析中也不例外.本文分别利用网格模拟数据和中国人均GDP实例数据为数据源,以全局Moran's I 系数来探究空间自相关统计中的MAUP效应,分析结果表明,变量的空间自相关程度依赖于空间的粒度大小与单元的划分方法,但空间单元的变化与自相关性并不存在某种函数关系.因此,在进行空间自相关研究时必须选择合适的地理单元的粒度大小和分区.最后本文给出一种基于地统计内插方法来降低MAUP对空间自相关分析影响.

关键词: MAUP, 空间自相关, 空间分析, 粒度, 区划

Abstract: This research investigated the role of modifiable area unit problem (MAUP) in the spatial autocorrelation on data of per capita GDP of China and grid simulated data. The global Moran's I coefficient was used to explore the MAUP effect of spatial autocorrelation statistics. The results showed that the degree of spatial autocorrelation of variables depends on the size of spatial particles and zone designing methods. However, there is no determined function relationship between the change of spatial units and the autocorrelation. So, how to choose the appropriate size of geographical unit particles and zone designing are very important in the research of spatial autocorrelation. Finally, the study presented an approach based on geostatistical interpolation to decrease MAUP effect in spatial autocorrelation analysis.

Key words: modifiable areal unit problem, spatial autocorrelation, spatial analysis, particle, zonation