Managing Urban Forests for Distributive, Procedural, and Recognition Justice

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Description
City governments have an opportunity to address historic environmental injustices through the management of their urban forests. When applying environmental justice to the management of urban trees, the common approach is to plant new trees in areas with high proportions

City governments have an opportunity to address historic environmental injustices through the management of their urban forests. When applying environmental justice to the management of urban trees, the common approach is to plant new trees in areas with high proportions of underserved residents and low tree canopy. This is the approach taken by many programs, such as the MillionTrees programs in Los Angeles and New York City. However, these initiatives do not always result in just outcomes and, in some cases, exacerbate existing inequities. This suggests the need for a model of urban tree canopy (UTC) justice that encapsulates distributive, procedural, and recognition justice. In this thesis, I suggest such a model of UTC justice that incorporates ecosystem services and disservices to understand resident satisfaction with neighborhood trees. I then apply the model to the case of the Phoenix, Arizona metropolitan area by assessing local UTC plans for mentions of environmental justice. Finally, I use multiple regression analysis to identify the relationship between neighborhood tree canopy percentage and resident satisfaction with neighborhood trees. Results indicate that tree canopy is a statistically insignificant determinant of resident satisfaction in 23 of 30 models. This supports my model of UTC justice in that it suggests that there is a confounding variable between UTC provisioning and resident satisfaction. This thesis culminates in recommendations for city governments, including the use of longitudinal socioecological surveys to evaluate the need for and success of UTC plans for environmental justice.
Date Created
2024
Agent

Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice

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Description

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data.

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman’s correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns.

Date Created
2015-04-01
Agent