以Google Earth为平台，基于GDP、人口与场地效应的全球大震损失评估模型
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摘要
随着人类文明的进步,世界财富的积累,人口城市化进程不断加快,全球经济持续发展,破坏性地震所造成的社会灾害损失随之越来越严重。科技的发展,技术的进步,也能让人们能在地震发生后比以往更快的速度到达灾区进行救援,及时有效地救援才能尽量减少社会财产的损失和挽救更多的生命。通常在大地震发生后,灾区的通信会中断,此时作为地震工作者和研究人员,如果我们尽快的估计灾区的震情分布、地震破坏性的分布(烈度)、以及损失分布情况,就能为救援人员提供信息参考和决策依据。本论文主要研究以Google Earth为展示平台,考虑场地放大效应对地震动的影响与修正,并利用GDP等宏观经济指标作为震害评估的全球大震损失评估模型。主要从下几个方面展开研究:
1.Internet的高速发展,使得Web-GIS逐步替代了传统的GIS系统,而“数字地球”概念的提出则更丰富和促进Web-GIS的发展。Google Earth的迅速崛起,并慢慢的渗透进人们的日常生活。基于XML语法的KML脚本语言和丰富的Web-API接口以及高分辨率的地理和地形构造信息方便了科研工作人员的使用,丰富的各类社会信息图层、高分辨率的卫星影像、人性化简单易操作的友好界面使得Google Earth成为了一个向大众展示和传播信息的优秀平台,也成为一个更客观方便的决策平台。
2.地震动参数的分布是进行震害和损失估计的基础。如何在地震后快速给出灾区的地表运动情况,并跟据得到的地震动进行地震损失的估计是本文的重点研究内容。影响地震动的参数很多,本章着重研究快速地震动的计算及场地效应对地震动的影响分布,并根据地震动分布和Vs30分布对地震动进行场地效应的校正。本文根据David Wald等人提出的方法,利用地形倾斜度求浅层剪切波Vs30的分布,进而根据地震动参数和数值求得场地放大因子。
3.陈颙院士等提出了利用GDP等宏观经济指标进行震害预测的方法,为进行地震的社会灾害损失评估提供了可行的途径。传统的地震灾害损失研究通常采用分类清单方法,即通过对研究区内建筑设施建立分类数据库,并收集详尽的资料进行分析。但面对现代社会的迅速发展,严峻的社会灾害损失所要求的地震快速应急响应和救灾决策,传统的方法在收集并及时更新资料方面都存在着明显的局限性。本文在进一步论证此方法可行性的基础上,继承了此思路和方法作损失的评估。
本文以简单的震源参数和地震动记录为输入条件,建立模型,在GoogleEarth平台中输出地震动参数的分布和以GDP为指标的地震损失分布结果。根据此模型,我们以2008年M8.0级汶川地震和2007年的M8.0级秘鲁地震作为实际应用的例子,检验此模型的可行性及分析存在的问题。
Along with the worldwide accelerating process of urbanization and the accumulation of wealth in the world,With the progress of human civilization,the loss caused by destructive earthquake increases remarkably.The development of science and technology also help People to reach the disaster area faster than ever before to rescue,and timely and effective manner will rescue the loss of social assets less and save more lives.The communication of the disaster areas will usually be interrupted after a strong earthquake,therefore we must distribute the earthquake ground motions,intensity map and the estimated loss map as a scientist of Seismology,to provide information for the earthquake emergency response and risk management.We try to set up a model for estimating the earthquake loss base on site correction and macroeconomic indicator-GDP on Google Earth platform.The main aspects we researched are following:
1.Web-GIS gradually replace traditional GIS with the high development of Internet,and then Google Earth is used in people's daily lives for it's many advantages.KML is based on XML syntax and API of web make Google Earth convenient for Seismologist.Also,Google Earth has rich information lays,high resolution satellite topographic images and is a suitable GIS platform to broadcast earthquake information.
2.Earthquake ground motions are the basement of emergency response and loss estimation.It's very important to distribute ground motions as soon as possible after an earthquake,but we need do site correction with the ground motions.David Wald et al.derived first-order site condition maps directly from topographic data,the slope-based method provides a simple approach to uniform site condition mapping.
3.Prof.Chen Yong et al.proposed an approach to address exposure bypass the problem of the conventional method by employing a macroscopic indicator to represent the social wealth directly.It provided a simplified method to estimate economic loss of social disaster impacts of earthquakes for most parts of the world.This approach is simple and easy to apply
We input the simple earthquake source parameters,such as magnitude, epicenter,depth and faults,then the model calculate and broadcast the ground motions and loss estimation in Google Earth.Wenchuan M8.0 earthquake(2008) and Peru M8.0 earthquake(2007) are two applications of this model.
1.Internet的高速发展,使得Web-GIS逐步替代了传统的GIS系统,而“数字地球”概念的提出则更丰富和促进Web-GIS的发展。Google Earth的迅速崛起,并慢慢的渗透进人们的日常生活。基于XML语法的KML脚本语言和丰富的Web-API接口以及高分辨率的地理和地形构造信息方便了科研工作人员的使用,丰富的各类社会信息图层、高分辨率的卫星影像、人性化简单易操作的友好界面使得Google Earth成为了一个向大众展示和传播信息的优秀平台,也成为一个更客观方便的决策平台。
2.地震动参数的分布是进行震害和损失估计的基础。如何在地震后快速给出灾区的地表运动情况,并跟据得到的地震动进行地震损失的估计是本文的重点研究内容。影响地震动的参数很多,本章着重研究快速地震动的计算及场地效应对地震动的影响分布,并根据地震动分布和Vs30分布对地震动进行场地效应的校正。本文根据David Wald等人提出的方法,利用地形倾斜度求浅层剪切波Vs30的分布,进而根据地震动参数和数值求得场地放大因子。
3.陈颙院士等提出了利用GDP等宏观经济指标进行震害预测的方法,为进行地震的社会灾害损失评估提供了可行的途径。传统的地震灾害损失研究通常采用分类清单方法,即通过对研究区内建筑设施建立分类数据库,并收集详尽的资料进行分析。但面对现代社会的迅速发展,严峻的社会灾害损失所要求的地震快速应急响应和救灾决策,传统的方法在收集并及时更新资料方面都存在着明显的局限性。本文在进一步论证此方法可行性的基础上,继承了此思路和方法作损失的评估。
本文以简单的震源参数和地震动记录为输入条件,建立模型,在GoogleEarth平台中输出地震动参数的分布和以GDP为指标的地震损失分布结果。根据此模型,我们以2008年M8.0级汶川地震和2007年的M8.0级秘鲁地震作为实际应用的例子,检验此模型的可行性及分析存在的问题。
Along with the worldwide accelerating process of urbanization and the accumulation of wealth in the world,With the progress of human civilization,the loss caused by destructive earthquake increases remarkably.The development of science and technology also help People to reach the disaster area faster than ever before to rescue,and timely and effective manner will rescue the loss of social assets less and save more lives.The communication of the disaster areas will usually be interrupted after a strong earthquake,therefore we must distribute the earthquake ground motions,intensity map and the estimated loss map as a scientist of Seismology,to provide information for the earthquake emergency response and risk management.We try to set up a model for estimating the earthquake loss base on site correction and macroeconomic indicator-GDP on Google Earth platform.The main aspects we researched are following:
1.Web-GIS gradually replace traditional GIS with the high development of Internet,and then Google Earth is used in people's daily lives for it's many advantages.KML is based on XML syntax and API of web make Google Earth convenient for Seismologist.Also,Google Earth has rich information lays,high resolution satellite topographic images and is a suitable GIS platform to broadcast earthquake information.
2.Earthquake ground motions are the basement of emergency response and loss estimation.It's very important to distribute ground motions as soon as possible after an earthquake,but we need do site correction with the ground motions.David Wald et al.derived first-order site condition maps directly from topographic data,the slope-based method provides a simple approach to uniform site condition mapping.
3.Prof.Chen Yong et al.proposed an approach to address exposure bypass the problem of the conventional method by employing a macroscopic indicator to represent the social wealth directly.It provided a simplified method to estimate economic loss of social disaster impacts of earthquakes for most parts of the world.This approach is simple and easy to apply
We input the simple earthquake source parameters,such as magnitude, epicenter,depth and faults,then the model calculate and broadcast the ground motions and loss estimation in Google Earth.Wenchuan M8.0 earthquake(2008) and Peru M8.0 earthquake(2007) are two applications of this model.
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