基于互联网信息快速估计汶川地震有感范围
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摘要
通过搜索和分析互联网上有关汶川地震的信息得出,汶川地震后3h为有感信息密集发布时段,信息总量为4 515条。分析信息的发布时间、地域和有感强度分布特征,对信息按照无感、有感和强有感进行分类,提取分布于199个地区的2 289条有感信息作为数据源进行有感范围的空间插值拟合处理。空间插值选用反距离权插值、径向基函数插值和克里格插值3种方法,通过对不同插值结果的比较分析发现,克里格插值方法在一定的插值模型和参数下对有感范围的拟合效果与汶川地震实际影响范围基本吻合,尤其是强有感范围基本反映了地震灾区范围。该项研究为震后快速获取地震有感范围提供了有效途径,同时也为地震灾害速判提供了动态修正依据,为地震应急提供第一时间的灾情信息。
Based on the felt information from the Internet after the earthquake,this paper studied the methods of earthquake damage information acquisition and analysis. We carried out the research based on 4515 pieces of felt information after the Wenchuan earthquake acquired from the Internet.After the analysis on the publishing time,location and intensity of the feeling of the earthquake in the felt information,we found that the release of felt information was concentrated within the 3 hours after the Wenchuan earthquake happened. And we initially identified 2 289 felt data released in the subsequent three hours after Wenchuan earthquake,which distributed in 199 areas,as the data sources for spatial interpolation. In order to do spatial interpolation for these datasets,we classified the datasets into three categories,which are "unawareness","felt " and "strongly felt ",and assigned the value of 0,1 and 2 to "unawareness","felt"and "strongly felt"respectively. Before doing the spatial interpolation for the datasets,we preprocessed the datasets distributed in 193 different areas to remove the redundant and abnormal value data and to finally extract 193 felt data distributed in different areas. At the same time,this paper did exploratory analysis for the datasets,by which we knew the law of the datasets and determined the parameters and model for the spatial interpolation. After a series of analysis,this paper adopted IDW,RBF and Kriging methods to interpolate the felt datasets,and get the results of the felt range of Wenchuan earthquake. Then,the paper compared the results from different spatial interpolation ways by interpolation accuracy and the goodness of fit with the actual earthquake disaster. After the comparison,we found that the result of Kriging method,with a certain interpolation model and parameters,was consistent with actual disaster distribution of the Wenchuan earthquake to a certain extent,especially for the fitting with the strongly felt area( Ⅵ degrees). This study provides an effective way for us to know quickly the earthquake felt range and correct for the disaster information of the earthquake. And it will play an important role in making scientific and rational decisions during the earthquake emergency.
Based on the felt information from the Internet after the earthquake,this paper studied the methods of earthquake damage information acquisition and analysis. We carried out the research based on 4515 pieces of felt information after the Wenchuan earthquake acquired from the Internet.After the analysis on the publishing time,location and intensity of the feeling of the earthquake in the felt information,we found that the release of felt information was concentrated within the 3 hours after the Wenchuan earthquake happened. And we initially identified 2 289 felt data released in the subsequent three hours after Wenchuan earthquake,which distributed in 199 areas,as the data sources for spatial interpolation. In order to do spatial interpolation for these datasets,we classified the datasets into three categories,which are "unawareness","felt " and "strongly felt ",and assigned the value of 0,1 and 2 to "unawareness","felt"and "strongly felt"respectively. Before doing the spatial interpolation for the datasets,we preprocessed the datasets distributed in 193 different areas to remove the redundant and abnormal value data and to finally extract 193 felt data distributed in different areas. At the same time,this paper did exploratory analysis for the datasets,by which we knew the law of the datasets and determined the parameters and model for the spatial interpolation. After a series of analysis,this paper adopted IDW,RBF and Kriging methods to interpolate the felt datasets,and get the results of the felt range of Wenchuan earthquake. Then,the paper compared the results from different spatial interpolation ways by interpolation accuracy and the goodness of fit with the actual earthquake disaster. After the comparison,we found that the result of Kriging method,with a certain interpolation model and parameters,was consistent with actual disaster distribution of the Wenchuan earthquake to a certain extent,especially for the fitting with the strongly felt area( Ⅵ degrees). This study provides an effective way for us to know quickly the earthquake felt range and correct for the disaster information of the earthquake. And it will play an important role in making scientific and rational decisions during the earthquake emergency.
引文
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李璐,姜小三,孙永远.2011.基于地统计学的降雨侵蚀力插值方法研究:以江苏省为例[J].生态与农村环境学报,27(1):88—92.LI Lu,JIANG Xiao-san,SUN Yong-yuan.2011.Geostatistics-based spatial interpolation method for study of rainfallerosivity:A case study of Jiangsu[J].Journal of Ecology and Rural Environment,27(1):88—92(in Chinese).
刘爱利,王培法,丁园圆.2012.地统计学概论[M].北京:科学出版社.LIU Ai-li,WANG Pei-fa,DING Yuan-yuan.2012.Introduction of Geostatistics[M].Science Press,Beijing(inChinese).
帅向华,侯建盛,刘钦.2009.基于地震现场离散点灾情报告的灾害空间分析模拟研究[J].地震地质,31(2):321—333.doi:10.3969/j.issn.0253-4967.2009.02.013.SHUAI Xiang-hua,HOU Jian-sheng,LIU Qin.2009.Analysis and simulation of spatial distribution of disaster basedon disaster reports from discrete dots at earthquake site[J].Seismology and Geology,31(2):321—333(inChinese).
帅向华,胡素平,刘钦,等.2013.地震灾情网络媒体获取与处理模型[J].自然灾害学报,22(3):178—184.SHUAI Xiang-hua,HU Su-ping,LIU Qin,et al.2013.Internet media-based acquisition and processing model ofearthquake disaster situation[J].Journal of Natural Disasters,22(3):178—184.
汤国安,杨昕.2006.Arc GIS地理信息系统空间分析实验教程[M].北京:科学出版社.TANG Guo-an,YANG Xin.2006.Experimental Course of Arc GIS for GIS Spatial Analysis[M].Science Press,Beijing(in Chinese).
王艳妮,谢金梅,郭祥.2008.Arc GIS中的地统计克里格插值法及其应用[J].软件导刊,7(12):36—38.WANG Yan-ni,GUO Jin-mei,GUO Xiang.2008.Application of geostatistical interpolation method in Arc GIS[J].Software Guide,7(12):36—38(in Chinese).
于晓艳,马劲松,朱敬芳,等.2011.基于地统计学的江西省年降水量插值研究[J].测绘科学,36(4):83—85.YU Xiao-yan,MA Jin-song,ZHU Jing-fang,et al.2011.Application of annual precipitation interpolation of Jiangxibased on geostatistics method[J].Science of Surveying and Mapping,36(4):83—85(in Chinese).
张仁铎.2005.空问变异理论及应用[M].北京:科学出版社.ZHANG Ren-duo.2005.Theory and Application of Spatial Variability[M].Science Press,Beijing(in Chinese).
郑向向.2012.基于SMS和GIS的地震灾情信息获取与处理研究[D]:[学位论文].北京:中国地震局地震预测研究所.ZHENG Xiang-xiang.2012.Research of earthquake disaster information acquisition and processing based on SMS andGIS[D].Dissertation.Institute of Earthquake Science,China Earthquake Administration,Beijing(in Chinese).
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