Planarity and Street Network Representation in Urban Form Analysis

Abstract

Models of street networks underlie research in urban travel behavior, accessibility, design patterns, and morphology. These models are commonly defined as planar, meaning they can be represented in two dimensions without any underpasses or overpasses. However, real-world urban street networks exist in three-dimensional space and frequently feature grade separation such as bridges and tunnels: planar simplifications can be useful but they also impact the results of real-world street network analysis. This study measures the nonplanarity of drivable and walkable street networks in the centers of 50 cities worldwide, then examines the variation of nonplanarity across a single city. It develops two new indicators - the Spatial Planarity Ratio and the Edge Length Ratio - to measure planarity and describe infrastructure and urbanization. While some street networks are approximately planar, we empirically quantify how planar models can inconsistently but drastically misrepresent intersection density, street lengths, routing, and connectivity.

References in corpus (11)

• Spatial Networks
• OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks
• Centrality Measures in Spatial Networks of Urban Streets
• The spatial structure of networks
• Structural Properties of Planar Graphs of Urban Street Patterns
• Modeling urban street patterns
• Random planar graphs and the London street network
• Urban street networks: a comparative analysis of ten European cities
• Limited Urban Growth: London's Street Network Dynamics since the 18th Century
• Urban road networks -- Spatial networks with universal geometric features? A case study on Germany's largest cities
• Elementary processes governing the evolution of road networks

Cited by in corpus (8)

• Urban Spatial Order: Street Network Orientation, Configuration, and Entropy
• A Multi-Scale Analysis of 27,000 Urban Street Networks: Every US City, Town, Urbanized Area, and Zillow Neighborhood
• Data-driven strategies for optimal bicycle network growth
• The Right Tools for the Job: The Case for Spatial Science Tool-Building
• The Morphology and Circuity of Walkable and Drivable Street Networks
• A review of the structure of street networks
• Towards a classification of planar maps
• Vulnerable Connectivity Caused by Local Communities in Spatial Networks