Environmental inequities in terms of different types of urban greenery in Hartford, Connecticut

• Environmental disparity was investigated in terms of different types of urban greenery in Hartford, Connecticut.
• Low-income people are living in areas with less street greenery and Hispanics people live in neighborhoods with less backyard greenery in Hartford, CT.
• There is no disparity in terms of proximity to urban parks among different racial/ethnic groups.
• Google Street View was utilized to map the spatial distribution of street greenery with consideration of the time information.

Urban greenery has long been recognized as an important component of urban ecosystem and provides many benefits to urban residents. However, different types of urban greenery provide different kinds of natural experiences to people. In this study, green metrics calculated based on multisource spatial datasets were used to quantify the spatial distribution of different types of urban greenery in Hartford, Connecticut. Geo-tagged Google Street View images, which capture the profile view of cityscape, were used to quantify street greenery by considering the time information. Land cover map and urban parks map were used to measure residential yard greenery and proximity to urban parks, respectively. We analyzed the associations of the calculated green metrics with socio-economic variables derived from census data. Statistical results show that: (1) people with higher income tend to live in neighborhoods with more street greenery; (2) census block groups with a higher proportion of owner-occupied units tend to have more yard vegetation and yard tree/shrub coverage; (3) Hispanics tend to live in block groups that have less yard vegetation but African Americans mostly live in block groups with more yard greenery; and (4) there are no significant environmental disparities among racial/ethnic groups in terms of proximity to urban parks. In general, this study provides an insight into the environments of urban residents in terms of urban greenery, and a valuable reference data for urban planning.