摘要
采用专门研究不确定性变化规律的蒙特卡罗 (MonteCarlo)模拟法结合GIS ,研究北京地区非典时空变化的基本特征。北京非典时间变化的影响度指数结果表明 ,海淀区(10 6 6 6 6 7)、朝阳区 (6 6 92 31)、东城区 (5 974 36 )、西城区 (4 1794 9)和通州区 (3 6 410 3)等 5个地区占北京地区非典影响率的 72 8% ,其中海淀区就占了 2 5 % ,远郊区县的影响几乎为零。非典整体频数 /次数特征曲线表现出明显的偏正态分布 ,因此前期及时对公众预警并切断传染途径是预防体系的首要环节。非典空间分布表现出明显的圈层结构 ,并且具有西北—东南走向 。
This paper improves a technique by using Monte Carlo simulation approach integrated with GIS to study the spatial-temporal uncertainty of SARS in Beijing. The output relative indexes from the sensitive analysis show that five districts, Haidian with the value of 10.66667, Chaoyang with the value of 6.69231, Dongcheng with the value of 5.97436, Xicheng with the value of 4.17949 and Tongzhou with the value of 3.64103, together contributed 72.8% of the total frequency distribution in the case of Beijing’s SARS. However, Haidian District alone presented almost 25% of the total frequency distribution. The frequency distribution of SARS’s series was a typical lognormal distribution. These facts indicated that the early-stage timely warning of SARS and the blocking transmission of infection for the public are of the first importance. The spatial distributions of SARS's effects significantly presented different shapes of circles. However, the shapes of the circles were most likely a kind of ellipse that had long axis extending from the northwest to the southeast in Beijing. It is suggested that the preventive system of SARS can be served as several circles from the center to the fringe when new outbreaks of SARS occur.
出处
《地理研究》
CSCD
北大核心
2004年第6期815-824,共10页
Geographical Research
基金
国家自然科学基金资助项目 (4 0 1710 2 9
4 0 4 710 5 8)
南京大学科研基金资助项目 (0 2 0 90 0 4 10 3)
关键词
北京地区
非典
时空变化规律
蒙特卡罗模拟法
Beijing area
SARS
spatial-temporal distribution
Monte Carlo simulation
