通过分析全球城市交通网络图像，揭示其与空气污染的几何关联。
Transport Network, Graph, and Air Pollution
- 基于30万张城市图像构建交通网络图谱，提取12项拓扑指标
- 发现连接度提升、道路类型均衡可显著降低污染
- 为城市规划提供去开发干扰的基础设施优化方案
空气污染可依托交通网络的都市结构进行研究。交通网络可通过设计模型以几何与拓扑图特征进行分析。现有研究因模型局限且特征不足，缺乏全面视角。本研究通过0.3百万张全球城市图像解读，发现污染相关交通网络的几何模式，并将其归纳为12项指标以探究网络-污染关联。结果表明，提升连通性、均衡道路类型及避免极端聚类系数对缓解污染有益。作为纯图论研究，该方法通过分离永久基础设施与衍生开发的影响，为更精准高效的污染减排提供城市规划支持。
原文摘要 · Abstract (English)
Air pollution can be studied in the urban structure regulated by transport networks. Transport networks can be studied as geometric and topological graph characteristics through designed models. Current studies do not offer a comprehensive view as limited models with insufficient features are examined. Our study finds geometric patterns of pollution-indicated transport networks through 0.3 million image interpretations of global cities. These are then described as part of 12 indices to investigate the network-pollution correlation. Strategies such as improved connectivity, more balanced road types and the avoidance of extreme clustering coefficient are identified as beneficial for alleviated pollution. As a graph-only study, it informs superior urban planning by separating the impact of permanent infrastructure from that of derived development for a more focused and efficient effort toward pollution reduction.
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