RAPID: Discovering Crises Within Crises - Real-Time Detection, Tracking and Visualization of Emergent Crises in Hurricanes

RAPID：发现危机中的危机 - 飓风中紧急危机的实时检测、跟踪和可视化

• 批准号: 1760645
• 负责人: John Taylor
• 金额: $ 18.77万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1760645&HistoricalAwards=false
• 关键词: RAPID; Discovering; Crises; Within; Real

Hurricanes are a devastating natural disaster. Forecasters at the NOAA Climate Prediction Center have predicted an above-normal hurricane season this year. This prediction is already proving accurate as evidenced by the two massive and devastating recent hurricanes: Hurricane Harvey and Hurricane Irma. It is urgent and time critical to develop, refine and test systems that can improve the ability of first responders and emergency management agencies to identify emergent crises before, during and after hurricanes. The research objective of this Rapid Response Research (RAPID) is to develop a crisis detection, tracking and visualization system. Social media data collected before, during and after Hurricane Harvey and Hurricane Irma will be used to develop and retrospectively validate the system. The results of this research will improve the detection, tracking and visualization of emergent crises in hurricanes and other large scale natural disasters in the future by enabling the pinpointing of extreme crisis areas in the midst of an overall emerging crisis. This will be accomplished without prior definition of crisis topics to enable the detection of unexpected crises that are clustered in space and time, potentially leading to more lives saved. It will further provide first responder and emergency management agencies with a new understanding of the role spatially-referenced social media can play in increasing the effectiveness of disaster response efforts. The research findings and the detection, tracking and visualization system will be disseminated in presentations to emergency responders in coastal urban areas to demonstrate the system and encourage its implementation in future tropical cyclone seasons.

飓风是一场毁灭性的自然灾害。 NOAA气候预测中心的预报员预测今年的飓风季节超过了。这两个巨大而毁灭性的飓风已经证明了这一预测是准确的：哈维飓风和飓风艾尔玛。 开发，完善和测试系统的紧急时间和时间至关重要，可以提高急救人员和紧急管理机构在飓风前，期间和之后确定紧急危机的能力。 这项快速响应研究（快速）的研究目标是开发危机检测，跟踪和可视化系统。 在哈维飓风和飓风Irma飓风之前和之后收集的社交媒体数据将用于开发和追溯验证该系统。 这项研究的结果将改善未来飓风和其他大规模自然灾害新兴危机的检测，跟踪和可视化，通过在整个新兴危机中实现极端危机地区的准确指标。 这将在没有事先定义危机主题的情况下实现，以便能够发现在时空聚集的意外危机，并有可能导致更多的生命挽救。 它将进一步为急救人员和应急管理机构提供对空间引用的社交媒体角色的新了解，可以在提高灾难响应工作的有效性方面发挥作用。研究发现以及检测，跟踪和可视化系统将在向沿海城市地区的紧急响应者的演讲中传播，以证明该系统并鼓励其在未来的热带气旋季节中实施。

项目成果

The Sound of Silence: Exploring How Decreases in Tweets Contribute to Local Crisis Identification

• 发表时间: 2018
• 作者: R. Samuels;J. Taylor;Neda Mohammadi

Measuring the Impact of Transportation Diversity on Disaster Resilience in Urban Communities: Case Study of Hurricane Harvey in Houston, TX

衡量交通多样性对城市社区抗灾能力的影响：德克萨斯州休斯顿飓风哈维的案例研究

• DOI: 10.1061/9780784482445.071
• 发表时间: 2019
• 期刊: Proceedings of the ASCE International Conference on Computing in Civil Engineering
• 作者: Wang, Yan;Rahimi-Golkhandan, Armin;Chen, Changjie;Taylor, John E.;Garvin, Michael J.
• 通讯作者: Garvin, Michael J.

The Promise of Smart and Resilient Cities

智慧和韧性城市的前景

• 发表时间: 2018
• 期刊: The Bridge
• 作者: DesRoches, R.;Taylor, J.
• 通讯作者: Taylor, J.

Applied Methodology for Identifying Hurricane-Induced Social Media Signal Changes in Vulnerable Populations

识别飓风引起的弱势群体社交媒体信号变化的应用方法

• DOI: 10.1061/9780784482445.067
• 发表时间: 2019
• 期刊: Proceedings of the ASCE International Conference on Computing in Civil Engineering
• 作者: Samuels, Rachel;Taylor, John E.
• 通讯作者: Taylor, John E.

Coupling sentiment and human mobility in natural disasters: a Twitter-based study of the 2014 South Napa Earthquake

• DOI: 10.1007/s11069-018-3231-1
• 发表时间: 2018-06-01
• 期刊: NATURAL HAZARDS
• 影响因子: 3.7
• 作者: Wang, Yan;Taylor, John E.
• 通讯作者: Taylor, John E.