Department of Environmental Studies, University of California, Santa Cruz, Santa Cruz, California, United States of America.
Department of Urban Planning, University of California, Los Angeles, Los Angeles, California, United States of America.
PLoS One. 2023 Jan 25;18(1):e0278265. doi: 10.1371/journal.pone.0278265. eCollection 2023.
A better understanding of urban form metrics and their environmental outcomes can help urban policymakers determine which policies will lead to more sustainable growth. In this study, we have examined five urban form metrics-weighted density, density gradient slope, density gradient intercept, compactness, and street connectivity-for 462 metropolitan areas worldwide. We compared urban form metrics and examined their correlations with each other across geographic regions and socioeconomic characteristics such as income. Using the K-Means clustering algorithm, we then developed a typology of urban forms worldwide. Furthermore, we assessed the associations between urban form metrics and two important environmental outcomes: green space access and air pollution. Our results demonstrate that while higher density is often emphasized as the way to reduce driving and thus PM2.5 emissions, it comes with a downside-less green space access and more exposure to PM2.5. Moreover, street connectivity has a stronger association with reduced PM2.5 emissions from the transportation sector. We further show that it is not appropriate to generalize urban form characteristics and impacts from one income group or geographical region to another, since the correlations between urban form metrics are context specific. Our conclusions indicate that density is not the only proxy for different aspects of urban form and multiple indicators such as street connectivity are needed. Our findings provide the foundation for future work to understand urban processes and identify effective policy responses.
更好地理解城市形态指标及其环境结果可以帮助城市政策制定者确定哪些政策将导致更可持续的增长。在这项研究中，我们检查了全球 462 个大都市区的五个城市形态指标——加权密度、密度梯度斜率、密度梯度截距、紧凑度和街道连通性。我们比较了城市形态指标，并检查了它们在地理区域和收入等社会经济特征方面的相互关系。然后，我们使用 K-Means 聚类算法为全球的城市形态开发了一种分类法。此外，我们评估了城市形态指标与两个重要环境结果之间的关联：绿色空间可达性和空气污染。我们的结果表明，虽然通常强调更高的密度是减少驾驶和 PM2.5 排放的方法，但它也带来了一些负面影响——绿色空间可达性降低，PM2.5 暴露增加。此外，街道连通性与减少交通部门 PM2.5 排放的关联更强。我们进一步表明，将城市形态特征和影响从一个收入群体或地理区域推广到另一个是不合适的，因为城市形态指标之间的相关性是特定于上下文的。我们的结论表明，密度不是城市形态不同方面的唯一代表，需要多个指标，如街道连通性。我们的研究结果为未来的工作提供了基础，以了解城市进程并确定有效的政策应对措施。
