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数据洞察可持续城市:谷歌街景衍生城市绿地与谷歌航拍衍生污染水平之间的关联。

Data Insights for Sustainable Cities: Associations between Google Street View-Derived Urban Greenspace and Google Air View-Derived Pollution Levels.

机构信息

Discipline of Civil, Structural & Environmental Engineering, School of Engineering & Architecture, University College Cork, Cork T12 K8AF, Ireland.

MaREI, the SFI Research Centre for Energy, Climate & Marine, University College Cork, Ringaskiddy, CorkP43 C573, Ireland.

出版信息

Environ Sci Technol. 2023 Dec 5;57(48):19637-19648. doi: 10.1021/acs.est.3c05000. Epub 2023 Nov 16.

Abstract

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 μm (PM), 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 ( < 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 NO 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.

摘要

城市化进程的空前加速引发了城市环境健康问题,包括全球城市空气污染的加剧。缓解空气污染的策略,包括绿色城市规划,对于可持续和健康的城市至关重要。通过利用庞大的数字数据集和新的分析工具,对城市绿地和污染指标的最先进研究已经加速。在这项研究中,我们研究了谷歌街景衍生的城市绿地水平与谷歌空气视图衍生的空气质量之间的关联,这两者都以极高的分辨率、准确性和规模沿着都柏林市的整个道路网络进行了解析。使用 5,030,143 个谷歌空气视图测量值来量化小于 2.5μm(PM)的颗粒物、二氧化氮、一氧化氮、一氧化碳和二氧化碳,并用 403,409 个谷歌街景视图图像来量化绿地。观察到城市绿地与污染之间存在显著的(<0.001)负相关关系。例如,在四分位间距内增加绿景指数与在点位置空间分辨率处 NO 降低 7.4%[95%置信区间:-13.1%,-1.3%]有关。我们深入了解了如何利用大规模数字数据阐明城市环境相互作用,这将对可持续未来城市的规划和政策产生重要影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83d0/10702516/7c196eeec335/es3c05000_0001.jpg

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