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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...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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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. |
format | Online Article Text |
id | pubmed-4382324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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