A fast approach to regional earthquake hazard evaluation based on population statistical data

来源 :Acta Seismologica Sinica(English Edition) | 被引量 : 0次 | 上传用户:rxw257
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In the prediction process of large-scale earthquake damage occurred in urban and rural regions,new models and approaches,which are different from traditional ones,should be adopted to rapidly predict earthquake damage. This article utilizes sampled population and buildings data that is easily available from the statistical database to conduct vulnerability analysis of buildings on the basis of earthquake damage of existing urban buildings in an analogical way,so as to provide a relation model between population data and disaster losses. In virtue of this model,the average vulnerability matrix of buildings of different structures in Fujian Province is established,the matrix adjustment coefficient of different decades is developed in accordance with the economic conditions,and the rapid evaluation system is set up as well. The result shows: this evaluation model,based on the population statistical data has merits as small investment,automatic data prediction,regular updates,as well as the advantage of easy accessibility. In the prediction process of large-scale earthquake occurred occurred in urban and rural regions, new models and approaches, which are different from traditional ones, should be adopted quickly predict earthquake damage. This article includes sampled population and buildings data that is readily available from the statistical database to conduct vulnerability analysis of buildings on the basis of earthquake damage of existing urban buildings in an analogical way, so as to provide a relation model between population data and disaster losses. buildings of different structures in Fujian Province is established, the matrix adjustment coefficient of different decades is developed in accordance with the economic conditions, and the rapid evaluation system is set up as well. The result shows: this evaluation model, based on the population statistical data has merits as small investment, automatic data prediction, regular updates, as well as th e advantage of easy accessibility.
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