共查询到19条相似文献，搜索用时 328 毫秒
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通过分析地震应急救援工作中对灾情信息的需求,提出了“地震应急灾情”的概念,设计了基于12322平台的江苏省地震应急灾情速报系统。本文详细介绍了该系统的设计框架、基本功能和应用效果。系统主要包括短信和微信两大模块,短信模块主要面向非地震系统人员,通过手机短信形式向社会灾情速报员发送灾情邀请短信,灾情速报员只需简单回复灾情代码“1”—“4”即可。微信模块主要面向地震系统工作人员,通过微信企业号“苏震12322”自动推送地震信息并完成灾情收集工作。经过近1年的试运行,系统能够在震后迅速完成灾情信息的收发与数据处理工作,并以“天地图”为地理底图实时直观地展示已上报的灾情信息。 相似文献
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文中重点研究了基于地震现场能够获取的离散的地震灾情点信息进行灾情的总体分析和模拟。依靠灾情速报人员或相关人员上报的地震现场灾情点信息,运用泰森多边形和GIS空间分析方法对离散点进行面插值分析和边界修正处理,形成适合计算离散灾情采样点的模型和算法,并借助GIS技术和WebService技术实现该模型和算法,建立相应的试验系统。该模型和系统能够随着灾情收集点的变化进行动态的分析模拟,从而能够在一定程度上及时快速地反映并确定地震灾情的基本分布情况,为地震救灾指挥提供相对确切的灾情分布信息。文中以汶川地震部分数据为例进行分析,结果基本与实际灾情吻合。选取的数据为73条有效短信,这些短信是从截至5月12日24:00收到的600余条灾情上报数据短信中分析提取出来的 相似文献
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为及时获取多源异构灾情信息,以多源灾情管理系统的架构和功能模块为研究对象,针对单体系统存在灵活性差、性能低、资源消耗不均衡等问题,提出基于微服务架构设计,在分布式环境下利用Spring Cloud框架,通过业务划分,设计独立模块的微服务,同时加入熔断器、消息队列等组件,缓存处理数据。运用地理信息系统实现灾情数据实时获取、灾情编码入库、地震灾情速报产品实时发布以及灾后应急管理。实验结果表明,采用多层微服务架构,系统扩展性增强,并发性能得到提高,提升了灾情数据管理效率。 相似文献
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从地震速报质量看江苏地震速报系统的进步 总被引：1，自引：0，他引：1
通过对１９８６年以来逐年地震速报质量分析比较,回顾了江苏地震速报系统的进步,并得到两点认识：１．地震观测系统建设的进步是提高地震速报水平的基础,２．加强地震速报队伍的建设是提高地震速报水平的保障。 相似文献
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随着我国经济的飞速发展,高速公路建设越来越多,地震监测设施和观测环境因其建设被危害的现象越来越严重。地震监测设施和观测环境保护行政执法的目的是保证地震监测设施完好、排除地震监测设施正常效能范围内的干扰源,保障地震监测预报工作质量。这类行政执法实际上是跨学科的,不仅要熟悉防震减灾法律法规,还需要了解测震、电磁、地壳形变和地下流体观测的地震专业知识。本文列举甘肃省办理过的3起典型案件,剖析该类案件行政执法各阶段的工作重点,提出高速公路建设危害地震监测设施和观测环境行政执法中存在法律依据缺位、执法主动性不够、执法效率低下、相关宣传不够的现实问题,通过分析、论证,给出有效建议。 相似文献
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本文综合评述了国际灾害搜索救援工作的起源、发展现状和管理理念,以及在联合国框架下实施国际灾害应急救援的相关组织和机构的职能及其在国际灾害紧急救援行动中的重要作用。还介绍了我国地震灾害应急救援事业的发展和当今应急指挥体制。详细阐述了云南省地震局在推进地震应急管理工作方面从经验型向规范化、制度化、法制化迈进的历程和经验。并就今后进一步搞好云南的地震灾害危险性管理工作提出一些建议。 相似文献
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在进行大规模城乡震害预测工作中,需要使用与传统预测方式不同的新模型及新方法,以便实现震害快速预测及结果共享。利用人口普查数据等基础数据库,根据人口数据及灾害损失的关系模型,基于WebGIS技术,采用三层体系网络架构(由后台数据库、应用服务器(地图服务器)+Web服务器、客户端组成),利用VB+ArcObject服务器组件开发技术,通过动态链接库技术实现了在Ar-cIMS下的地图动态更新、动态预测及动态发布功能,实现了具有B/S结构的震害预测管理信息系统。该系统具有投入少、数据自动预测、定期更新且易于获取等优点,实现了地震震害信息共享 相似文献
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1837年甘肃岷县北6级地震考证与发震构造分析 总被引：8，自引：0，他引：8
通过对1837年甘肃岷县北6级地震的历史资料考证、 发震构造的综合研究表明:在1837年地震中遭破坏最为严重的地区位于今岷县堡子乡武旗及临潭县陈旗一带(当时的洮州厅以东约15 km)。 由此确定1837年甘肃岷县地震极震区位于甘肃岷县-临潭-卓尼三县交界, 极震区烈度为Ⅷ度, 震中位于北纬34.7°, 东经103.9°, 误差在10 km以内。 该地区构造位于东昆仑断裂带和西秦岭北缘断裂带的应变传递和构造转换的中间过渡区, 其中临潭-宕昌断裂带活动特性差异明显, 只有部分地段表现出全新世活动特征, 地震极震区一带分布有不同程度的滑坡和基岩崩塌等。 综合分析认为, 临潭-宕昌断裂带的岷县-宕昌段的前缘分支断裂是甘肃岷县1837年6级地震的发震构造。 相似文献
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From the events of catastrophic natural disasters that have occurred in recent years, it can be found that social media platforms are increasingly becoming the most important and most convenient way for the general public to timely release and obtain information on disasters. The information obtained from such platforms contains a large amount of information in the form of texts, pictures, etc. that record the current situation of the disaster. And it also has characteristics of high efficiency and high spatial distribution to serve the rapid emergency after the earthquake. In this paper, we firstly make a statistical analysis of 32 689 pieces of historical disaster data acquired from 5 earthquakes with obvious characteristics, such as post-earthquake disaster events, user's expression habits and so on, and adopts cross-validation method. Then information classification system which includes seven first-level categories and more than 50 second-level categories is constructed. The information classification system and evaluation system of crisis degree for post-earthquake emergency response are constructed both using cross-validation method. The former is referred to the thought of existing classification basis and the experience knowledge of several emergency experts. Based on the five indicators of subject word, action word, degree word, time and position measurement, an evaluation system of critically with four levels of severity, moderate intensity, mildness and others was constructed. Considering the sparse features of self-media information and the large difference in the number of training sets, a naive Bayes model for information classification is trained based on the classification system and evaluation system. Its accuracy rate is 73.6%. At the same time, the classification method of feature fusion of machine learning model and semantic calculation model is used to evaluate the criticality of the disaster information. The accuracy rate of the evaluation model is 89.2%, higher than 85.2% of the semantic computing model and 77% of the naive Bayesian model. The evaluation model has combined the advantages of semantic computing method which can evaluate all index features with machine learning method which has high classification efficiency and accuracy. The thresholds for classification between mild and moderate intensity, moderate intensity and severe intensity were 15.2 and 27.39. The model realized in this paper can crawl, classify and evaluate the disaster information in the media in real time after an earthquake, and realizes mining of a small amount of critical and important information from the massive self-media information, thus, to assist in earthquake intensity rapid reporting and accurate rescue. Finally, taking the Jiuzhaigou earthquake on August 8, 2017 as an example, 17 432 pieces of data were crawled in real time within 48 hours after the earthquake. At the same time, based on ArcGIS, the mining information is visualized in time and space, and the availability of the data is evaluated from two perspectives of earthquake intensity quick reporting and accurate rescue after the earthquake. The disaster information of Jiuzhaigou County in the earthquake area is obviously more than that of the non-earthquake area in terms of quantity and emergency degree. The results show that the self-media information with high spatial distribution can effectively find the severer disaster grade area after the earthquake, shorten the time of earthquake intensity prediction, effectively classify and extract information, provide real-time information for precise rescue, and improve the efficiency of emergency response after the earthquake. 相似文献
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