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

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 Gr...

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Detalles Bibliográficos
Autores principales: Schwarz, Kirsten, Fragkias, Michail, Boone, Christopher G., Zhou, Weiqi, McHale, Melissa, Grove, J. Morgan, O’Neil-Dunne, Jarlath, McFadden, Joseph P., Buckley, Geoffrey L., Childers, Dan, Ogden, Laura, Pincetl, Stephanie, Pataki, Diane, Whitmer, Ali, Cadenasso, Mary L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382324/
https://www.ncbi.nlm.nih.gov/pubmed/25830303
http://dx.doi.org/10.1371/journal.pone.0122051
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author Schwarz, Kirsten
Fragkias, Michail
Boone, Christopher G.
Zhou, Weiqi
McHale, Melissa
Grove, J. Morgan
O’Neil-Dunne, Jarlath
McFadden, Joseph P.
Buckley, Geoffrey L.
Childers, Dan
Ogden, Laura
Pincetl, Stephanie
Pataki, Diane
Whitmer, Ali
Cadenasso, Mary L.
author_facet Schwarz, Kirsten
Fragkias, Michail
Boone, Christopher G.
Zhou, Weiqi
McHale, Melissa
Grove, J. Morgan
O’Neil-Dunne, Jarlath
McFadden, Joseph P.
Buckley, Geoffrey L.
Childers, Dan
Ogden, Laura
Pincetl, Stephanie
Pataki, Diane
Whitmer, Ali
Cadenasso, Mary L.
author_sort Schwarz, Kirsten
collection PubMed
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. 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.
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spelling pubmed-43823242015-04-09 Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice Schwarz, Kirsten Fragkias, Michail Boone, Christopher G. Zhou, Weiqi McHale, Melissa Grove, J. Morgan O’Neil-Dunne, Jarlath McFadden, Joseph P. Buckley, Geoffrey L. Childers, Dan Ogden, Laura Pincetl, Stephanie Pataki, Diane Whitmer, Ali Cadenasso, Mary L. PLoS One Research Article 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. Public Library of Science 2015-04-01 /pmc/articles/PMC4382324/ /pubmed/25830303 http://dx.doi.org/10.1371/journal.pone.0122051 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Research Article
Schwarz, Kirsten
Fragkias, Michail
Boone, Christopher G.
Zhou, Weiqi
McHale, Melissa
Grove, J. Morgan
O’Neil-Dunne, Jarlath
McFadden, Joseph P.
Buckley, Geoffrey L.
Childers, Dan
Ogden, Laura
Pincetl, Stephanie
Pataki, Diane
Whitmer, Ali
Cadenasso, Mary L.
Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice
title Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice
title_full Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice
title_fullStr Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice
title_full_unstemmed Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice
title_short Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice
title_sort trees grow on money: urban tree canopy cover and environmental justice
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382324/
https://www.ncbi.nlm.nih.gov/pubmed/25830303
http://dx.doi.org/10.1371/journal.pone.0122051
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