Urban Spatial Order: Street Network Orientation, Configuration, and Entropy (1808.00600v4)

Abstract: Street networks may be planned according to clear organizing principles or they may evolve organically through accretion, but their configurations and orientations help define a city's spatial logic and order. Measures of entropy reveal a city's streets' order and disorder. Past studies have explored individual cases of orientation and entropy, but little is known about broader patterns and trends worldwide. This study examines street network orientation, configuration, and entropy in 100 cities around the world using OpenStreetMap data and OSMnx. It measures the entropy of street bearings in weighted and unweighted network models, along with each city's typical street segment length, average circuity, average node degree, and the network's proportions of four-way intersections and dead-ends. It also develops a new indicator of orientation-order that quantifies how a city's street network follows the geometric ordering logic of a single grid. A cluster analysis is performed to explore similarities and differences among these study sites in multiple dimensions. Significant statistical relationships exist between city orientation-order and other indicators of spatial order, including street circuity and measures of connectedness. On average, US/Canadian study sites are far more grid-like than those elsewhere, exhibiting less entropy and circuity. These indicators, taken in concert, help reveal the extent and nuance of the grid. These methods demonstrate automatic, scalable, reproducible tools to empirically measure and visualize city spatial order, illustrating complex urban transportation system patterns and configurations around the world.

• The paper introduces the orientation-order indicator (φ) to quantify street network grid-likeness and analyzes its relationship with spatial order across 100 global cities.
• Key findings reveal that cities in the US and Canada show higher grid-likeness (lower entropy and circuity) compared to cities in Europe.
• Cities with higher orientation-order (φ) values demonstrate greater street network connectedness and less circuity, exemplified by Chicago's highly grid-aligned network.

Overview of Urban Spatial Order: Street Network Orientation, Configuration, and Entropy

The research paper authored by Geoff Boeing conducts a comprehensive analysis of street network orientation, configuration, and entropy across 100 cities globally. Utilizing OpenStreetMap data alongside the OSMnx toolkit, the paper quantitatively explores how street networks influence the spatial order of urban environments. This examination is pivotal for understanding both the practical and theoretical aspects of urban planning, transportation design, and city morphology.

Methodology and Approach

The paper employs an empirical approach to model street network configuration and entropy. It introduces the orientation-order indicator, φ, which quantifies the alignment of a city's street network with the geometric logic of a grid. The research encompasses various quantitative measures, including the entropy of street bearings, street segment length, circuity, average node degree, and the proportions of four-way intersections and dead-ends.

The analysis involves cluster analysis to identify and compare trends and patterns among global urban environments. It utilizes statistical methods to evaluate relationships between street network orientation, circuity, and connectedness, offering a nuanced view of the spatial order exhibited in different urban contexts.

Key Findings and Numerical Results

The results indicate significant statistical relationships between city orientation-order and spatial order indicators such as street circuity and connectedness. On average, cities in the United States and Canada demonstrate a higher degree of grid-likeness, exhibiting lower entropy and circuity compared to their global counterparts. Conversely, European cities tend to show higher orientation entropy and less defined grid structures.

One of the prominent revelations is that cities with higher φ values exhibit greater connectedness and less street network circuity. For example, Chicago, highlighted as an extreme outlier, scores a φ of 0.90, suggesting its street network is 90% aligned with a perfect grid, which starkly contrasts with cities like Charlotte that have higher entropy and disordered orientation.

Implications and Future Research Directions

This paper holds implications for advancing urban planning methodologies by providing quantitative tools to measure and visualize urban spatial order. The scalable nature of these methods allows for broad application across various scales and regions, promoting better-informed decisions in urban design and transportation planning.

Future research could delve into the relationship between topography, city development eras, design paradigms, and street network evolution. This could enrich our understanding of how these factors interplay in shaping urban spatial order, potentially leading to the development of a comprehensive grid-index. Such advancements would integrate additional attributes, like streetscape and network width, further exploring urban form's impact on walkability and transit behavior.

Conclusion

Geoff Boeing's research contributes significantly to urban spatial studies by offering a robust framework for examining street network orientation and entropy across global cities. The findings emphasize the diverse patterns of urban organization, with particular attention to the high degree of order present in North American street networks compared to other regions. This research not only informs urban planning and spatial analysis but also sets the stage for future studies to explore deeper intricacies of urban morphology and its implications on human dynamics and city planning.