Over the last decade, street-view type images have been used across disciplines to generate and understand various place-based metrics. However efforts to collect this data were often meant to support investigator-driven research without regard to the utility of the data for other researchers. To address this, we describe our methods for collecting and publishing longitudinal data of this type in the wake of the COVID-19 pandemic and discuss some of the challenges we encountered along the way. Our process included designing a route taking into account both broad area canvassing and community capitals transects. We also implemented procedures for uploading and publishing data from each survey. Our methods successfully generated the kind of longitudinal data that can be beneficial to a variety of research disciplines. However, there were some challenges with data collection consistency and the sheer magnitude of data produced. Overall, our approach demonstrates the feasibility of generating longitudinal street-view data in the wake of a disaster event. Based on our experience, we provide recommendations for future researchers attempting to create a similar data set.

翻译：过去十年来，街景类图像已被跨学科用于生成和理解各类基于场所的指标。然而，以往的数据采集工作往往服务于研究者主导的特定研究，并未考虑数据对其他研究者的可用性。为此，我们介绍了在新冠疫情期间采集并发布此类纵向数据的方法，并探讨了过程中遇到的若干挑战。我们的流程包括：综合考虑大范围普查与社区资本样带设计路线，同时实施了每次调查数据的上传与发布规程。该方法成功生成了有益于多学科研究的纵向数据，但数据采集的一致性以及生成数据的海量规模仍构成挑战。总体而言，我们的方法证明了在灾害事件后生成纵向街景数据的可行性。基于实践经验，我们为未来尝试构建类似数据集的研究者提供了建议。