RAPID: Examining public spatial behavior during the COVID-19 outbreak

2019冠状病毒病大流行改变了我们日常公共生活的每时每一刻。一些社区已经开始限制大部分人口的移动、活动、身体互动和社会化。采取这些行动是必要的，目的是减少人与人之间的接触，作为减轻病毒潜在传播的广泛努力的一部分。在人口密集的大都市地区，保持社会距离的措施产生了紧迫感，这些地区是新冠肺炎病例的很大一部分。该项目将启动一项快速努力，以获取疫情期间街景生活的高分辨率数据，目标是随着公共空间行为的变化而产生快速反应的见解。这将通过捕捉和编码沉浸式的、第一人称的、地理定位的视频日记来实现，这些视频日记记录了大都市居民每天的街景活动，随着生活的变化，以适应新的社交距离和宵禁令。这些数据将通过当地社区伙伴关系广泛传播。此外，该项目还将资助四名STEM相关领域的研究生。这项研究捕捉了新形式的空间行为是如何出现的，同时测试了现有的空间行为理论在特殊情况下是如何成立的。核心创新是关注日常街景场景中的个体体现，通过公共场所的肢体语言揭示潜在和公开的空间行为。这将通过一组招募的志愿者在大流行期间进行日常活动时的第一人称视频片段来完成。这些数据将被手工和机器编码，以探索空间行为的模式，这些模式可以表明个人、建筑环境和社会行为现象之间的关系。紧急关系将被微调，在事后使用一系列基于工作室的实验，部署动作捕捉，系统地和经验地追踪非语言交流（如手势和习惯）和空间行为的高分辨率时空细节之间的路径，在一个受控的环境中，利用收集的视频数据作为基础事实。为了促进数据的广泛使用并促进进一步的研究，将使用高分辨率时空地理信息系统（GIS）和虚拟地理环境对来自实地和工作室实验的数据进行整理。这些资源将公开提供，并与当地合作伙伴共享，这将对保障公众健康和福祉产生影响。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。

The COVID-19 pandemic has altered the moment-to-moment activities of our daily public lives. Some communities have initiated restrictions on the movement, activities, physical interaction, and socialization of large sections of the population. These actions have been borne of necessity, in a bid to reduce human contact as part of widespread efforts to mitigate the potential spread of the virus. Social distancing measures have taken on a sense of urgency in population-dense metropolitan areas, which host a large portion of the COVID-19 cases. This project will launch a rapid effort to acquire high-resolution data regarding life on streetscapes during the pandemic, with the goal of producing quick-response insight as changes in public spatial behavior unfold. This will be done by capturing and coding immersive, first-person, geolocated video- diaries of metropolitan residents going about their daily streetscape activity, as life shifts to adapt to new social distancing and curfew orders. The data will be disseminated broadly through local community partnerships. Additionally, the project will fund four graduate students in diverse STEM related fields.This research captures how new forms of spatial behavior emerge, while testing how existing theories of spatial behavior hold under extraordinary circumstances. The central innovation is to focus on individual embodiment in day-to-day streetscape scenes, as revealed in latent and overt spatial behavior through body language in public places. This will be accomplished through first-person video footage of everyday streetscape scenes from a group of recruited volunteers as they go about daily activities during a pandemic. The data will be hand and machine coded to explore patterns of spatial behavior that can indicate relationships between individuals, the built environment, and socio-behavioral phenomena. Emergent relationships will be fine-tuned, using a series of studio-based experiments after the fact, deploying motion capture to methodically and empirically trace-out pathways between non-verbal communication such as gestures and mannerisms, and high-resolution space-time details of spatial behavior, in a controlled setting that utilizes the collected video data as ground truth. To promote broader use of the data and to foster additional research, data will be collated—from both the field and from the studio experiments—using high-resolution space-time Geographic Information Systems (GIS) and virtual geographical environments. These resources will be made publicly available and shared with local partners, with implications for safeguarding public health and wellbeing.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.