- Paul Torrens (Principal Investigator) – Professor of Urban Informatics at CUSP
With a trove of data already in hand about how people move about on New York City streetscapes, Professor Paul Torrens’ research team was a natural to perform a compare-and-contrast study after COVID-19 hit. The NSF agreed, funding the project that could quickly inform decisions on curfews and social distancing in dense urban areas. After all, citizens’ actual reactions to each other can indicate just how strict regulations should be and potentially even help communities to forecast how the citizenry will respond once shelter-in-place rules are lifted.
This research captures how new forms of spatial behavior emerge while testing how existing theories of spatial behavior hold under extraordinary circumstances. Emergent relationships will be fine-tuned, using a series of studio-based experiments after the fact, deploying motion capture to trace pathways between non-verbal communication such as gestures and mannerisms, and high-resolution space-time details of spatial behavior. The resources will be made publicly available and shared with local partners, with implications for safeguarding public health and well-being.
Torrens is a professor in the Computer Science and Engineering Department and CUSP.
Project Abstract
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.