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Integration of Social Media and Unmanned Aerial Vehicles (UAVs) for Rapid Damage Assessment in Hurricane Matthew

机译：集成社交媒体和无人机以快速评估马修飓风

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Recent studies stress the critical role of rapid damage assessment in crisis management to reduce losses in natural disasters. Timely damage-related data collection by traditional empirical inquiry methods (e.g., interview and survey questionnaire) is particularly difficult after natural disasters such as hurricanes and floods. Remote sensing technologies including satellite and unmanned aerial vehicles (UAVs) were popularly employed in previous research in support of damage data collection. Compared with orbit limitation and high operating costs of satellites, UAVs demonstrated its advantages in low operating costs, high operational flexibility, and high spatial resolution of imagery. However, using UAVs alone in data collection for major disasters such as Hurricane Matthew is particularly difficult because the affected area was so extensive. On the other side, previous studies indicate that social media (e.g., Twitter) was widely used as a crowdsourcing platform for citizens' communication and information sharing during natural disasters. Furthermore, citizens can also communicate information updates related to damage (e.g., burned area of wildfire) in natural disasters. Hence, social media presented its potential in providing timely information to support damage assessment. To conduct a rapid damage assessment, this paper proposed the framework of integration of Twitter and UAVs for damage data collection for Hurricane Matthew in Florida. Firstly, this study used real-time Twitter data to prioritize the affected counties requiring the deployment of UAVs. Secondly, we proposed the employment of UAVs in imagery and video data collection in these affected areas at the city and region level. Lastly, processing techniques for image and video were applied for rapid damage assessment, which can be further geographically represented to support crisis management.
机译：最近的研究强调了快速损害评估在减少危机中减少自然灾害损失中的关键作用。在飓风和洪水等自然灾害发生后，通过传统的经验查询方法（例如访谈和调查问卷）及时收集与损害相关的数据尤其困难。包括卫星和无人飞行器（UAV）在内的遥感技术已广泛用于以前的研究中，以支持破坏数据的收集。与轨道限制和卫星的高运营成本相比，无人机展示出其低运营成本，高运营灵活性和高图像空间分辨率的优势。但是，由于受灾地区如此之大，仅使用无人机来收集诸如马修飓风这样的重大灾难的数据就特别困难。另一方面，先前的研究表明，社交媒体（例如Twitter）被广泛用作自然灾害期间公民交流和信息共享的众包平台。此外，公民还可以传达与自然灾害中的破坏（例如，野火烧毁的区域）有关的信息更新。因此，社交媒体展现了其提供及时信息以支持损害评估的潜力。为了进行快速的损害评估，本文提出了整合Twitter和无人机的框架，以收集佛罗里达州马修飓风的损害数据。首先，这项研究使用实时Twitter数据对需要部署无人机的受灾县进行优先排序。其次，我们建议在城市和地区级别的这些受影响地区使用无人机进行图像和视频数据的收集。最后，将图像和视频的处理技术用于快速损害评估，可以在地理上进一步表示这些特征以支持危机管理。

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