地球科学进展 ›› 2005, Vol. 20 ›› Issue (3): 282 -291. doi: 10.11867/j.issn.1001-8166.2005.03.0282

学术论文 上一篇    下一篇

中国SARS疫情的探索性空间数据分析
范新生,应龙根   
  1. 华东师范大学地理信息科学教育部重点实验室,上海 200062
  • 收稿日期:2004-02-25 修回日期:2004-07-12 出版日期:2005-03-25
  • 通讯作者: 范新生 E-mail:fanxs80@163.com
  • 基金资助:

    国家自然科学基金项目“中国地区经济增长空间分析”(编号:40271033 );教育部科学技术研究重点项目“GIS空间数据现代分析”(编号:03074)资助.

AN EXPLORATORY SPATIAL DATA ANALYSIS OF SARS EPIDEMIC IN CHINA

FAN Xinsheng; YING Longgen   

  1. Key Laboratory of GIScience, Ministry of Education, ECNU, Shanghai 200062, China
  • Received:2004-02-25 Revised:2004-07-12 Online:2005-03-25 Published:2005-03-25

运用空间统计学手段对中国省级SARS疫情的空间分布格局做了探索性的空间数据分析(exploratory spatial data analysis)。MoranI统计分析表明SARS疫情的分布具有很强的空间自相关,Moran Scatterplot进一步揭示了这一空间关系的地域差异及其各区位SARS疫情分布对总体趋势的偏移,Gi*统计则确定了疫情分布的空间集聚模式及其随时空转移轨迹。分析表明中国省级SARS疫情的发展并非一个相互独立的过程,而是存在着统计学意义上可测度的空间关系,且这种关系在空间相邻时最为显著。

Based on recently developed methods of exploratory spatial data analysis, this paper analyzes the SARS epidemic in China from a spatial perspective. Our results show strong evidence of spatial autocorrelation in the levels of reported SARS cases. A global measure of spatial autocorrelation with Moran's I reveals the dominant pattern of spatial processes being positive, which suggests that provinces with high (low) reported SARS cases tend to be spatially clustered in nature. A local spatial autocorrelation analysis using Moran scatterplot provides a visual impression on the local regimes of spatial dependence as well as the pockets of local non-stationarity with respect to the global spatial process. A further spatial clustering analysis using the local Gi* statistic detects the spatial center of SARS epidemic development and its spatial shifting trajectory. All this strongly suggests that, while regions may be growing or declining in reported SARS cases, they do not do so independently but rather tend to display dynamics similar to their contiguity neighbors.

中图分类号: 

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