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Early Flood Detection for Rapid Humanitarian Response: Harnessing Near Real-Time Satellite and Twitter Signals

机译:早期洪水检测,可快速做出人道主义响应:利用近实时卫星和Twitter信号

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Humanitarian organizations have a crucial role in response and relief efforts after floods. The effectiveness of disaster response is contingent on accurate and timely information regarding the location, timing and impacts of the event. Here we show how two near-real-time data sources, satellite observations of water coverage and flood-related social media activity from Twitter, can be used to support rapid disaster response, using case-studies in the Philippines and Pakistan. For these countries we analyze information from disaster response organizations, the Global Flood Detection System (GFDS) satellite flood signal, and flood-related Twitter activity analysis. The results demonstrate that these sources of near-real-time information can be used to gain a quicker understanding of the location, the timing, as well as the causes and impacts of floods. In terms of location, we produce daily impact maps based on both satellite information and social media, which can dynamically and rapidly outline the affected area during a disaster. In terms of timing, the results show that GFDS and/or Twitter signals flagging ongoing or upcoming flooding are regularly available one to several days before the event was reported to humanitarian organizations. In terms of event understanding, we show that both GFDS and social media can be used to detect and understand unexpected or controversial flood events, for example due to the sudden opening of hydropower dams or the breaching of flood protection. The performance of the GFDS and Twitter data for early detection and location mapping is mixed, depending on specific hydrological circumstances (GFDS) and social media penetration (Twitter). Further research is needed to improve the interpretation of the GFDS signal in different situations, and to improve the pre-processing of social media data for operational use.
机译:人道主义组织在洪灾后的响应和救援工作中起着至关重要的作用。灾难响应的有效性取决于有关事件的位置,时间和影响的准确及时的信息。在这里,我们通过菲律宾和巴基斯坦的案例研究,展示了如何使用两个近实时数据源(卫星观测的水覆盖范围和Twitter的洪水相关社交媒体活动)来支持快速灾难响应。对于这些国家,我们分析了来自灾难响应组织,全球洪水检测系统(GFDS)卫星洪水信号以及与洪水相关的Twitter活动分析的信息。结果表明,这些近乎实时的信息源可用于更快速地了解洪水的位置,时间以及洪水的成因和影响。在位置方面,我们基于卫星信息和社交媒体制作每日影响图,可以在灾难期间动态,快速地勾勒出受影响的区域。就时间安排而言,结果表明,在向人道主义组织报告该事件之前的一到几天,GFDS和/或Twitter信号标记正在进行或即将发生的洪水。在事件理解方面,我们表明,GFDS和社交媒体都可以用于检测和理解意外或有争议的洪水事件,例如,由于水力发电大坝的突然开放或防洪保护的破坏。 GFDS和Twitter数据用于早期检测和位置映射的性能是混合的,具体取决于特定的水文情况(GFDS)和社交媒体渗透(Twitter)。需要进一步研究以改进在不同情况下对GFDS信号的解释,并改善社交媒体数据的预处理以供操作使用。

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