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  • 软件名称:基于历史相似案例空间推演的地震伤亡人口评估方法研究
  • 软件大小: 0.00 B
  • 软件评级: ★★★★★★
  • 开 发 商: 曾婷婷, 宫阿都, 陈艳玲, 杨雨晴
  • 软件来源: 《地球信息科学学报》
  • 解压密码:www.gissky.net

资源简介

摘要:

地震是对人类生存构成最大威胁的自然灾害之一,往往导致巨大的损失。本研究选取中国2000—2013年震级为4.0级以上且有人员伤亡的地震灾害统计数据作为历史案例,以基于历史案例的灾情加权综合评估模型(Assessment Method of Natural Disaster Based on Similarly Historical Cases,SHC)为基础,考虑历史案例与当前灾害的空间相关程度,获得改进的基于历史相似案例空间推演的地震伤亡人口评估(Assessment Method of Earthquake Casualties Based on Spatial Reasoning of Similarly Historical Cases,SRSHC);并选取2010年青海玉树地震、2013年四川芦山地震及2014年云南鲁甸地震作为验证案例,进行精度验证。结果表明:① 对于3个验证案例,SRSHC模型的最佳评估精度均在95%以上,表明该方法在地震伤亡人口评估方面具有一定的可行性及适用性;② SRSHC模型相较于SHC模型,参评案例的个数少且精度更高,以2010年四川芦山地震为例,当参评案例个数为3个时,SRSHC模型评估结果达到最佳(97.92%);而SHC模型参评案例个数需6个达到评估结果最佳(35.49%),这表明历史案例与当前灾害发生地区的空间相关程度对评估结果有较大影响;③ 灾情评估的精度与参评案例的个数有关,当参评案例在2个以上时,模型评估的精度随着参评案例个数的增加呈平稳下降趋势;当参评案例的个数为3~4个时,SRSHC模型的评估精度最佳。基于历史案例的灾情评估方法成本低、效率高、时效性强,且方法简单、约束条件较少、容易实现, 在灾情评估方面具有一定的实用价值。

关键词: 灾情评估, 快速评估, 空间推演, 历史相似案例, 地震, 伤亡人口, SRSHC模型, 空间相关程度

Abstract:

Earthquake is one of the most serious natural disasters for our human existence, and often causes huge losses. Disaster assessment based on similar historical cases is useful for disaster analysis and quick policy making when detailed real disaster data are not available. Based on the framework of the Assessment Method of Natural Disaster Based on Similarly Historical Cases (SHC model), this paper constructs the Spatial Reasoning of Similarly Historical Cases (SRSHC) model for earthquake casualty assessment, which considers the spatial relevance of historical cases to current disasters. We select earthquake magnitude, focal depth, and time of earthquake to describe the characteristics of an earthquake and use a similarity assessment model based on Manhattan distance to evaluate its similarity to historical cases. Besides, this paper introduces the distance of earthquake fault to quantify the spatial correlation between historical cases and current disaster. In this study, earthquake disasters with a magnitude of 4.0 or above in China from 2000 to 2013 are selected as historical cases. Three representative cases are chosen for accuracy verification, including the Yushu earthquake in Qinghai in 2010, the Lushan earthquake in Sichuan in 2013, and the Ludian earthquake in Yunnan in 2014. Results show that: (1) For the three verification cases, the accuracy of the SRSHC model is all above 95%, indicating that the model has certain feasibility and applicability in assessment of earthquake casualty; (2) Compared with the SHC model, the SRSHC model requires fewer participating cases but higher accuracy. For example, for the Yushu earthquake, when the number of participating cases is three, the accuracy of the SRSHC model reaches highest (97.92%). While the SHC model requires six participating cases to reach the highest accuracy (35.49%). It reveals that the spatial correlation between historical cases and the current disaster has a great impact on the evaluation of results; and (3) The accuracy of the disaster assessment model is related to the number of participating cases. When there are more than two participating cases, the accuracy of the model assessment decreases with increasing number of participating cases. When the number of participating cases is three or four, the accuracy of the SRSHC model is the highest. In conclusion, the advantages of the method developed this study are low cost, high efficiency, timely effectiveness, its simplicity, less constraint, and easy to implement, which has certain practical value and prospects in disaster assessment.

Key words: disaster assessment, rapid assessment, spatial reasoning, similar historical cases, earthquake, casualties, SRSHC model, spatial correlation

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