Characterizing community-wide housing attributes using georeferenced street-level photography.

Abstract

New methods are needed to efficiently characterize built environment attributes and residential behaviors to improve exposure assessment in epidemiologic research, given limitations of available databases and approaches. Window opening and presence of air conditioning (AC) units predict indoor air quality and thermal comfort, but data are not widely available. In this study, we tested the utility of a GIS-based tool for rapidly assessing open windows and window/wall air conditioning units in the city of Chelsea, Massachusetts using georeferenced street-level photographs and crowdsourced online surveys. We characterized open windows and window/wall AC units for 969 parcels in the winter and 1 213 parcels in the summer, requiring approximately 40 person-hours per season. In the winter, 21% of parcels surveyed had a window or wall AC unit and 19% had an open window. In the summer, 69% had a window or wall AC unit and 53% had an open window. We demonstrated an efficient method for rapidly characterizing open windows and window/wall AC units across an entire city. This tool can help characterize exposures for epidemiological research, engage community members, and inform local land use planning and decision-making.