共 8 条
Data Insights for Sustainable Cities: Associations between Google Street View-Derived Urban Greenspace and Google Air View-Derived Pollution Levels
被引:7
|作者:
Sabedotti, Maria E. S.
[1
,2
,3
]
O'Regan, Anna C.
[1
,2
,3
]
Nyhan, Marguerite M.
[1
,2
,3
]
机构:
[1] Univ Coll Cork, Sch Engn & Architecture, Discipline Civil Struct & Environm Engn, Cork T12 K8AF, Ireland
[2] Univ Coll Cork, SFI Res Ctr Energy Climate & Marine, MaREI, Cork P43 C573, Ireland
[3] Univ Coll Cork, Environm Res Inst, Cork T23 XE10, Ireland
基金:
爱尔兰科学基金会;
关键词:
urban greenspace;
air pollution;
Google AirView;
Google Street View;
urban analytics;
sustainable cities;
PATTERNS;
EXPOSURE;
PLATFORM;
QUALITY;
IMPACT;
CHINA;
D O I:
10.1021/acs.est.3c05000
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Unprecedented levels of urbanization have escalated urban environmental health issues, including increased air pollution in cities globally. Strategies for mitigating air pollution, including green urban planning, are essential for sustainable and healthy cities. State-of-the-art research investigating urban greenspace and pollution metrics has accelerated through the use of vast digital data sets and new analytical tools. In this study, we examined associations between Google Street View-derived urban greenspace levels and Google Air View-derived air quality, where both have been resolved in extremely high resolution, accuracy, and scale along the entire road network of Dublin City. Particulate matter of size fraction less than 2.5 mu m (PM2.5), nitrogen dioxide, nitric oxide, carbon monoxide, and carbon dioxide were quantified using 5,030,143 Google Air View measurements, and greenspace was quantified using 403,409 Google Street View images. Significant (p < 0.001) negative associations between urban greenspace and pollution were observed. For example, an interquartile range increase in the Green View Index was associated with a 7.4% [95% confidence interval: -13.1%, -1.3%] decrease in NO2 at the point location spatial resolution. We provide insights into how large-scale digital data can be harnessed to elucidate urban environmental interactions that will have important planning and policy implications for sustainable future cities.
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页码:19637 / 19648
页数:12
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