RAPID: Rural Loss Estimates of Hurricane Florence Enabled by Citizen Scientists

这个快速反应研究(RAPID)项目考察了普通公民科学家在一场影响农村地区的飓风后能否有效地收集易腐烂的研究级损害数据的方法。这项研究以2018年的飓风佛罗伦萨为测试案例。该项目独特地利用农村地区的记者网络，积极招募当地公民科学家，利用多种渠道记录破坏情况。该项目直接加强了对佛罗伦萨农村破坏的了解，并将影响这些经常被边缘化和被忽视的社区的立即恢复。此外，本研究还通过地面实况勘察数据验证了农村环境中公民生产的损坏数据与工程师收集的损坏数据的有效性。因此，这项科学研究贡献支持了NSF的使命，即促进科学进步和增进我们的国家福利，这些利益将为规划改善美国社区的复原力，特别是飓风和洪水的复原力提供信息。如果利用公民科学家尚未开发的潜力，收集关于受佛罗伦萨影响的贫困农村农业地区各级飓风破坏的大量真实世界视觉和文字数据，证明是收集损害数据的成功方法，这可以改变工程师预测和研究这些事件影响的方式。此外，该项目开发的快速激活记者和公民科学家网络的新方法也可应用于其他自然灾害(如海啸、地震、风暴病等)。超出拟议工作范围的工程工作，可能涉及类似的偏远和农村社区。通过让公众参与科学，这项工作使农村公民能够了解飓风的影响，并承担起他们对这一研究领域的贡献。从这项研究中获得的结果和数据将通过DesignSafe网络基础设施提供的交互式和可访问的工具迅速传播给公众和研究社区。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This Rapid Response Research (RAPID) project examines the ways in which everyday citizen scientists might be able to effectively collect perishable research-grade damage data following a hurricane that affects rural locales. This research uses Hurricane Florence in 2018 as a test case. The project uniquely leverages networks of journalists in rural areas to actively recruit local citizen scientists to document damage using multiple channels. This project directly enhances the understanding of rural damage from Florence and will impact the immediate recovery of these often marginalized and neglected communities. Furthermore, this research measures and tests the efficacy of citizen-produced versus engineer-collected damage data in rural contexts, validated by ground truth reconnaissance data. This scientific research contribution thus supports NSF's mission to promote the progress of science and to advance our national welfare with benefits that will inform planning to improve the resilience of United States communities, in particular to hurricanes and flooding. If harnessing the untapped potential of citizen scientists to collect large volumes of real-world visual and textual data regarding all levels of hurricane damage in poorer rural agricultural areas affected by Florence proves to be a successful method of collecting damage data, this can transform the ways in which engineers can predict effects from and study these events. Moreover, the new methodologies for rapid activation of journalist and citizen scientist networks developed in this project can be applied to other natural hazards (e.g., tsunamis, earthquakes, wind storms, etc.) engineering efforts beyond the scope of the proposed work that might involve similar remote and rural communities. By engaging the public in participatory science, this work empowers rural citizens to learn about the effects of hurricanes and take ownership of their contributions to this field of research. Findings and data obtained from this study will be rapidly disseminated to the public and research community through interactive and accessible tools available via the DesignSafe cyberinfrastructure..This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.