Tree canopy change and neighborhood stability: A comparative analysis of Washington, D.C. and Baltimore, MD

- We evaluated the association between income change and tree canopy.
- We built spatial regression models to predict tree canopy.
- Income change reveals different associations with tree canopy in cities.
- Distribution of trees involves complex interactions of socio-ecological systems.

Trees provide important health, ecosystem, and aesthetic services in urban areas, but they are unevenly distributed. Some neighborhoods have abundant tree canopy and others nearly none. We analyzed how neighborhood characteristics and changes in income over time related to the distribution of urban tree canopy in Washington, D.C. and Baltimore, MD. We used stepwise multiple regression analysis to identify strong predictors of UTC, from variables found in neighborhoods with different patterns of wealth-stability over time. We then built spatial lag models to predict variation in UTC cover, using the results of a Principal Component Analysis of the socioeconomic, demographic, and housing characteristics of the two cities. We found that: (1) stable-wealthy neighborhoods were more likely to have more, and more consistent, tree canopy cover than other neighborhood types; (2) decreases and increases in income were negatively associated with UTC in Washington, D.C. but not Baltimore, where income stability in both wealthy and impoverished neighborhoods was a significant predictor of UTC; and (3) the association of high socioeconomic status with UTC coverage varied between the two cities.