RAPID: The COVID-19 Pandemic Seattle, Washington Street View Campaign

华盛顿州西雅图是美国第一个受到2019冠状病毒病（COVID-19）大流行严重影响的城市。自疫情爆发以来，州和地方政府制定了政策和指导方针（即非药物干预措施）来阻止疾病的传播，包括在全州范围内实施就地避难令。这项快速反应研究拨款（Rapid）将在西雅图广泛的横截面上进行为期12个月的纵向（重复）街景调查，以收集有关疫情对社区影响的数据。调查运动将在本次大流行期间和之后产生城市区域的高分辨率地面记录。该数据集将提供以下方面的基本见解：(1)灾害对商业运营、交通网络和其他社区资产的影响；(2)就地安置后的恢复速度和质量，以及基于社区社会经济特征的地方差异；(3)灾害后放松就地安置政策对社区的影响。除了数据收集之外，该项目还将通过建立可用于指导未来破坏性事件的数据收集活动的采样协议，推进事件后移动成像的科学应用。所有项目数据将在nsf支持的自然灾害工程研究基础设施（NHERI）数据仓库（https://www.Designsafe-ci.org）中公开提供给研究和实践社区。街景调查将使用美国国家科学基金会支持的NHERI RAPID设施的车载移动成像系统进行，该系统位于华盛顿大学。将采用两种数据收集策略：(1)调查，这是一种获取数据的总括方法，可用于回答各种多学科研究问题；(2)在社区首都样带（社会、文化、建筑、经济和公共卫生）进行调查，这是一种基于资本复原力理论的方法，旨在促进在广泛的社区和灾害中进行复制的能力。该项目还将开发和实施一系列开源程序，自动处理数据，从图像中快速提取时间敏感的见解。处理后的数据集将作为校准和验证城市模拟和恢复模型以及许多新兴的基于人工智能的模型的基准。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Seattle, Washington is the first city in the United States to be severely impacted by the coronavirus disease 2019 (COVID-19) pandemic. Since the outbreak, state and local governments have enacted policies and guidelines (i.e., nonpharmaceutical interventions) to stem the spread of the disease, including a statewide shelter-in-place order. This Grant for Rapid Response Research (RAPID) will conduct longitudinal (repeat) street view surveys for 12 months across a broad cross-section of Seattle to collect data on the community impact of the pandemic. The survey campaign will produce a high-resolution, ground-based record of the urban region both during and after this pandemic. The data set will provide fundamental insights on (1) disaster impacts on business operations, transportation networks, and other community assets, (2) the rate and quality of recovery following shelter-in-place, and how this varies locally based on a community's socioeconomic characteristics, and (3) the impact of shelter-in-place policy relaxation on communities following this disaster. In addition to the data collection, this project will advance the scientific application of post-event mobile imaging by establishing sampling protocols that may be used to guide data collection campaigns for future disruptive events. All project data will be made openly available to research and practice communities in the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI) Date Depot (https://www.Designsafe-ci.org). The street view surveys will be conducted using the NSF-supported NHERI RAPID facility's vehicle-mounted mobile imaging system, located at the University of Washington. Two data collection strategies will be adopted: (1) canvassing, an umbrella approach to acquire data that may be used to answer diverse multidisciplinary research questions, and (2) surveying across community capitals transects (social, cultural, built, economic, and public health), an approach grounded in capital-based resilience theory to promote the capacity for replication across a wide range of communities and hazards. The project will also develop and implement a series of open-source routines that automatically process the data to rapidly extract time-sensitive insights from the imagery. The processed data set will serve as a benchmark for calibrating and validating urban simulation and recovery models and many of the emerging artificial intelligence-based models.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.