SPATIO-TEMPORAL STUDY OF THE DETERMINANTS OF RESIDENTIAL SATISFACTION IN NEW YORK CITY DURING COVID-19 USING CROWDSOURCED DATA
- Department of Civil and Urban Engineering, Tandon School of Engineering, New York University. Brooklyn, NY 11201, USA
Keywords: Noise, Crime, NYC311, NYPD 911, COVID-19, Change Dynamics, Residential Satisfaction
Abstract. Residential satisfaction, an indicator of the quality of life, can be conceptualized with the objective and subjective evaluation of the physical and ecological characteristics of dwellings and neighbourhoods. The majority of the New Yorkers remained indoors during the COVID-19 pandemic, increasing the importance of the residential environment and satisfaction like never before. Noise and safety are two major determinants of residential satisfaction that changed much during the pandemic lockdown. We used citizen-generated non-emergency (NYC311) and emergency (NYPD911) complaint data to investigate the spatial and temporal change dynamics of complaints related to noise and safety. In the noise domain, we focused on NYC311 complaints associated with the noise from neighbours, streets, and illegal fireworks. In the safety domain, we examined the change of both physical and economic safety. For physical safety, we used the NYPD 911 data related to burglary and vehicle larceny, where for economic safety, we used NYC311 complaints correspond to price gouging. We spatially aggregated the complaints at the census tract level (total = 2123) and performed Welsch’s t-test to identify the change dynamics of the satisfaction during the pandemic for different socioeconomic factors. We found the overall residential satisfaction decreased during the pandemic with extreme noise exposure and inadequate safety. The study also found the economic and racial disparity in residential satisfaction during the pandemic, as with statistical significance, the complaints regarding noise, physical and financial safety generated from the Black, Latinx, and impoverished communities were significantly higher than White, Asian and affluent communities.