Big Data and Emergency Management: Concepts, Methodologies, and Applications
Big Data and Emergency Management: Concepts, Methodologies, and Applications
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DOI：
10.1109/tbdata.2020.2972871
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发表时间：
2020-02
影响因子：
7.2
通讯作者：
Xuan Song;H. Zhang;R. Akerkar;Huawei Huang;Song Guo;L. Zhong;Yusheng Ji;A. Opdahl;Hemant Purohit-He
中科院分区：
文献类型：
--
作者：
Xuan Song;H. Zhang;R. Akerkar;Huawei Huang;Song Guo;L. Zhong;Yusheng Ji;A. Opdahl;Hemant Purohit-He
近几十年来，自然灾害和其他突发事件的频率、强度和影响显著增加，迫使世界各国政府将应急响应和灾害管理作为国家优先事项。超大和复杂的数据集--通常称为大数据--的增长，以及信息和通信技术和计算的各种进步，现在支持对自然灾害和紧急事件的人道主义救济、后勤协调、全面灾害管理和长期恢复采取更有效的办法。利用大数据和技术进步进行应急管理在研究界引起了相当大的关注。然而，大数据和应急管理(BDEM)的理想融合需要协调努力，以调整和定义跨学科术语和方法。到目前为止，这一新兴研究领域的关键概念和技术还没有以足够广泛和多学科的方式得到一致的讨论。在本文中，一个国际团队概述了BDEM领域，重点介绍了一个总体框架，并从几个角度讨论了关键挑战。我们介绍和总结了典型的技术和应用，分为六大类：遥感、弹性通信网络、移动通信网络、人员流动和城市感知、社会网络分析和知识图谱。最后，我们概述了未来研究的几个方向。
Recent decades have seen a significant increase in the frequency, intensity, and impact of natural disasters and other emergencies, forcing the governments around the world to make emergency response and disaster management national priorities. The growth of extremely large and complex datasets—commonly referred to as big data—and various advances in information and communications technology and computing now support more effective approaches to humanitarian relief, logistical coordination, overall disaster management, and long-term recovery in connection with natural disasters and emergency events. Leveraging big data and technological advances for emergency management has attracted considerable attention in the research community. However, the desired merging of big data and emergency management (BDEM) requires coordinated efforts to align and define interdisciplinary terminologies and methodologies. To date, the key concepts and technologies in this emerging research area have not been coherently discussed in a sufficiently broad and multidisciplinary manner. In this article, an international team presents an overview of the BDEM domain, highlighting a general framework and discussing key challenges from several perspectives. We introduce and summarize typical technologies and applications, organized into the six broad categories of remote sensing, resilient communication networks, mobile communication networks, human mobility and urban sensing, social network analysis, and knowledge graphs. Finally, we outline several directions of future research.