A GIS Equity Analysis of San Francisco Slow Streets

Abstract

San Francisco's Slow Streets program was first established on a temporary basis during the COVID-19 pandemic in 2020 and has since been made permanent. Slow Streets are meant to reduce and slow down vehicle traffic in order to prioritize pedestrians and bicyclists. The original purpose of Slow Streets during the pandemic was to promote social distancing to keep sidewalks and public transportation from overcrowding. Due to the emergency nature of the program's early implementation, the public had minimal opportunity to provide input. This raises important equity questions about where Slow Streets were located and who benefited from them. This thesis conducts a GIS analysis using publicly available census data to examine how equitably Slow Streets were distributed during two time periods: the initial network of Slow Streets in 2020 and the network of permanent Slow Streets in 2023. This study finds that the distribution of Slow Streets in San Francisco became less equitable in terms of race and income between the early stages in 2020 and the permanent network in 2023. In term of age, fewer seniors benefitted from Slow Streets in 2023 compared to 2020, with a smaller change for children. Future additions to the Slow Streets program can target neighborhoods without current access in order to make the program more equitable. The results of this analysis can be used to evaluate the success of Slow Streets, measure how equitably the benefits were distributed, and understand how the program can potentially be improved.