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利用基于地理信息系统的空间分析方法，在新冠疫情背景下确定不同种族群体的城市绿地可达性：以美国四个城市为例

Using GIS-based spatial analysis to determine urban greenspace accessibility for different racial groups in the backdrop of COVID-19: a case study of four US cities.

作者信息

Pallathadka Arun, Pallathadka Laxmi, Rao Sneha, Chang Heejun, Van Dommelen Dorn

机构信息

Department of Geography, Portland State University, Portland, OR 97201 USA.

GAMC, Rajiv Gandhi University of Health Sciences, Bengaluru, Karnataka 560010 India.

出版信息

GeoJournal. 2022;87(6):4879-4899. doi: 10.1007/s10708-021-10538-8. Epub 2021 Nov 3.

DOI:10.1007/s10708-021-10538-8
PMID:34744264
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8564283/
Abstract

UNLABELLED

As the United States leads COVID-19 cases on global charts, its spatial distribution pattern offers a unique opportunity for studying the social and ecological factors that contribute to the pandemic's scale and size. We use a GIS-data-based approach to evaluate four American cities-Anchorage (Alaska), Atlanta (Georgia), Phoenix (Arizona), and Portland (Oregon) characterized by the significant composition of different racial and ethnic group populations. Building upon previous studies that investigated urban spatial inequalities using the environmental justice framework, we examine: (1) the relative racial vulnerability of Census Block Groups (CBG) and ZIP Code Tabulation Areas (ZCTA) to COVID-19 (2) green space distribution at CBG and ZCTA scale. Using standard normalization methods, we ranked racial vulnerability against % available green space for each city. Our results highlight the legacy of past and present urban planning injustices. The project is useful from environmental justice, public health management, and urban planning perspectives.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10708-021-10538-8.

摘要

未标注

随着美国在全球新冠疫情病例数排行榜上位居榜首，其空间分布模式为研究导致疫情规模的社会和生态因素提供了独特契机。我们采用基于地理信息系统（GIS）数据的方法，对四个美国城市——阿拉斯加的安克雷奇、佐治亚州的亚特兰大、亚利桑那州的凤凰城和俄勒冈州的波特兰进行评估，这些城市以不同种族和族裔群体人口的显著构成特点为特征。基于以往使用环境正义框架调查城市空间不平等的研究，我们考察：（1）人口普查街区组（CBG）和邮政编码分区统计区域（ZCTA）相对于新冠疫情的种族相对脆弱性；（2）CBG和ZCTA尺度上的绿地分布情况。我们使用标准归一化方法，针对每个城市按可用绿地百分比对种族脆弱性进行排名。我们的研究结果凸显了过去和现在城市规划不公正的遗留问题。该项目从环境正义、公共卫生管理和城市规划角度来看都很有用。

补充信息

在线版本包含可在10.1007/s10708-021-10538-8获取的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/0b03e80f5a46/10708_2021_10538_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/8ea4798f958b/10708_2021_10538_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/52986ebac71e/10708_2021_10538_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/63bf8e7e36c0/10708_2021_10538_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/a1a6048255a1/10708_2021_10538_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/28db5d854a23/10708_2021_10538_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/b497ab35a357/10708_2021_10538_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/0b03e80f5a46/10708_2021_10538_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/8ea4798f958b/10708_2021_10538_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/52986ebac71e/10708_2021_10538_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/63bf8e7e36c0/10708_2021_10538_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/a1a6048255a1/10708_2021_10538_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/28db5d854a23/10708_2021_10538_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/b497ab35a357/10708_2021_10538_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93ae/8564283/0b03e80f5a46/10708_2021_10538_Fig7_HTML.jpg

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