This study used machine learning models to classify the type of vegetation (i.e., tree, low-lying vegetation, grass) from street view images and investigated the associations between street green space and socioeconomic (SES) factors, in Los Angeles County, California. We found that high resolution street view imagery coupled with deep learning approach can accurately and efficiently measure eye-level street green space and distinguish vegetation types. In Los Angeles County, disadvantaged communities had substantively less street green space. Governments and urban planners need to consider the type and visibility of street green space from pedestrian’s perspective.
Sun Y, Wang X, Zhu J, Chen L, Jia Y, Lawrence JM, Jiang L, Xie X, Wu J. 2021. Using machine learning to examine street green space and their associations with socioeconomic factors in Los Angeles County. Science of the Total Environment: 87. https://doi.org/10.1016/j.scitotenv.2021.147653.