scholarly journals A multi-scale analysis of 27,000 urban street networks: Every US city, town, urbanized area, and Zillow neighborhood

2018 ◽  
Vol 47 (4) ◽  
pp. 590-608 ◽  
Author(s):  
Geoff Boeing
Keyword(s):  
Urban Form ◽  
Ad Hoc ◽  
Directed Graphs ◽  
Street Network ◽  
Network Characteristics ◽  
Urban Street ◽  
Multi Scale ◽  
Street Networks ◽  
Urbanized Area ◽  
Data Acquisition And Processing

OpenStreetMap offers a valuable source of worldwide geospatial data useful to urban researchers. This study uses the OSMnx software to automatically download and analyze 27,000 US street networks from OpenStreetMap at metropolitan, municipal, and neighborhood scales—namely, every US city and town, census urbanized area, and Zillow-defined neighborhood. It presents empirical findings on US urban form and street network characteristics, emphasizing measures relevant to graph theory, transportation, urban design, and morphology such as structure, connectedness, density, centrality, and resilience. In the past, street network data acquisition and processing have been challenging and ad hoc. This study illustrates the use of OSMnx and OpenStreetMap to consistently conduct street network analysis with extremely large sample sizes, with clearly defined network definitions and extents for reproducibility, and using nonplanar, directed graphs. These street networks and measures data have been shared in a public repository for other researchers to use.

scholarly journals A Multi-Scale Analysis of 27,000 Urban Street Networks: Every US City, Town, Urbanized Area, and Zillow Neighborhood

2017 ◽  
Author(s):  
Geoff Boeing
Keyword(s):  
Urban Form ◽  
Ad Hoc ◽  
Directed Graphs ◽  
Street Network ◽  
Network Characteristics ◽  
Urban Street ◽  
Multi Scale ◽  
Street Networks ◽  
Urbanized Area ◽  
Data Acquisition And Processing

OpenStreetMap offers a valuable source of worldwide geospatial data useful to urban researchers. This study uses the OSMnx software to automatically download and analyze 27,000 US street networks from OpenStreetMap at metropolitan, municipal, and neighborhood scales - namely, every US city and town, census urbanized area, and Zillow-defined neighborhood. It presents empirical findings on US urban form and street network characteristics, emphasizing measures relevant to graph theory, transportation, urban design, and morphology such as structure, connectedness, density, centrality, and resilience. In the past, street network data acquisition and processing have been challenging and ad hoc. This study illustrates the use of OSMnx and OpenStreetMap to consistently conduct street network analysis with extremely large sample sizes, with clearly defined network definitions and extents for reproducibility, and using nonplanar, directed graphs. These street networks and measures data have been shared in a public repository for other researchers to use.

The Development of Pompeii’s Urban Street Network

2017 ◽  
Author(s):  
Eric E. Poehler
Keyword(s):  
Urban Form ◽  
Formal Analysis ◽  
Street Network ◽  
Urban Street ◽  
Street Networks ◽  
The City ◽  
Present Understanding

Chapter 2 explores the present understanding of Pompeii’s evolution by disassembling the apparent patchwork of grids across the city and reconsiders the presumed awkwardness in their adhesion. To do this, the traditional tools of formal analysis—street alignments and block shapes—are employed with and critiqued by the stratigraphic evidence recovered in the last three decades of excavation below the 79 CE levels. The result is an outline of the development of Pompeii’s urban form as a series of street networks: from the archaic age, through the period of the “hiatus” of the fifth and fourth centuries BCE, to a reorganization of the city’s space so profound that it can genuinely be considered a refoundation, and finally to the adjustments of a refounded city in the Colonial, Augustan, and post-earthquake(s) periods.

scholarly journals Understanding Chinese Urban Form: The Universal Fractal Pattern of Street Networks over 298 Cities

2020 ◽  
Vol 9 (4) ◽  
pp. 192 ◽  
Author(s):  
Ding Ma ◽  
Renzhong Guo ◽  
Ye Zheng ◽  
Zhigang Zhao ◽  
Fangning He ◽  
...  
Keyword(s):  
Urban Form ◽  
Physical Structure ◽  
Urban Morphology ◽  
Street Network ◽  
Urban Street ◽  
Street Networks ◽  
Topological Measures ◽  
Heavy Tailed ◽  
Definition Of ◽  
Almost All

Urban form can be reflected by many city elements, such as streets. A street network serves as the backbone of a city and reflects a city’s physical structure. A street network’s topological measures and statistical distributions have been widely investigated in recent years, but previous studies have seldom characterized the heavy-tailed distribution of street connectivities from a fractal perspective. The long-tail distribution of street connectivities can be fractal under the new, third definition: a set or pattern is fractal if the scaling of far more small things than large ones recurs at least twice. The number of recurred scaling patterns of far more less-connected streets than well-connected ones greatly helps in measuring the scaling hierarchy of a street network. Moreover, it enables us to examine the potential fractality of urban street networks at the national scale. In this connection, the present study aims to contribute to urban morphology in China through the investigation of the ubiquity of fractal cities from the lens of street networks. To do this, we generate hundreds of thousands of natural streets from about 4.5 million street segments over 298 Chinese cities and adopted power-law detection as well as three fractal metrics that emerged from the third definition of fractal. The results show that almost all cities bear a fractal structure in terms of street connectivities. Furthermore, our multiple regression analysis suggests that the fractality of street networks is positively correlated with urban socioeconomic status and negatively correlated with energy consumption. Therefore, the fractal metrics can be a useful supplement to traditional street-network configuration measures such as street lengths.

scholarly journals Quantitative analysis of the topologic morphology of urban street network based on system coupling theory

2020 ◽  
Author(s):  
Yan Xiao ◽  
◽  
Bingxin Wang ◽  
Hui Sun ◽  
◽  
...  
Keyword(s):  
Urban Form ◽  
Urban Morphology ◽  
Street Network ◽  
Urban Streets ◽  
Urban Street ◽  
Spatial Coupling ◽  
Multi Scale ◽  
Spatial Morphology ◽  
Cultural Connotations ◽  
System Coupling

Researchers are increasingly paying attention to urban morphology to address problems regarding urban form and to sustain the development of urban economy, society, and environments. A preliminary research framework was built to conduct coupling analyses on street form and block functions. These analyses are implemented using a planar graph method and using quantitative descriptions of the urban streets functions, but the coupling relation of street morphology and block function cannot be well defined, and it often cannot be analyzed in multi-level and multi-scale. Along with two proposed measuring parameters (connectivity and accessibility of coupling networks), the framework was used to quantitatively analyze the coupling coordination degree of the topologic morphology and functional structure of block samples for various urban streets. Through empirical research on different samples from Dalian, China, we validated the operability and urban street network coupling analysis in different spatial regions in built environments. This technique can be used to study the overall spatial morphology and design urban streets at different scales and scopes. Further, it helps recognize the space and cultural connotations of urban streets via spatial coupling, compare different urban textures, and predict design results to foster discussions on the optimization of urban planning design schemes.

scholarly journals Off the Grid... and Back Again? The Recent Evolution of American Street Network Planning and Design

2020 ◽  
Author(s):  
Geoff Boeing
Keyword(s):  
Urban Form ◽  
Design Patterns ◽  
Open Data ◽  
Urban Spatial Structure ◽  
Street Network ◽  
Street Networks ◽  
Planning And Design ◽  
Orientation Order ◽  
Established Relationship ◽  
Intersection Density

This morphological study identifies and measures recent nationwide trends in American street network design. Historically, orthogonal street grids provided the interconnectivity and density that researchers identify as important factors for reducing vehicular travel and emissions and increasing road safety and physical activity. During the 20th century, griddedness declined in planning practice alongside declines in urban form compactness, density, and connectivity as urbanization sprawled around automobile dependence. But less is known about comprehensive empirical trends across US neighborhoods, especially in recent years. This study uses public and open data to examine tract-level street networks across the entire US. It develops theoretical and measurement frameworks for a quality of street networks defined here as griddedness. It measures how griddedness, orientation order, straightness, 4-way intersections, and intersection density declined from 1940 through the 1990s while dead-ends and block lengths increased. However, since 2000, these trends have rebounded, shifting back toward historical design patterns. Yet, despite this rebound, when controlling for topography and built environment factors all decades post-1939 are associated with lower griddedness than pre-1940. Higher griddedness is associated with less car ownership—which itself has a well-established relationship with vehicle kilometers traveled and greenhouse gas emissions—while controlling for density, home and household size, income, jobs proximity, street network grain, and local topography. Interconnected grid-like street networks offer practitioners an important tool for curbing car dependence and emissions. Once established, street patterns determine urban spatial structure for centuries, so proactive planning is essential.

scholarly journals Multifractal scaling analyses of urban street network structure: The cases of twelve megacities in China

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246925
Author(s):  
Yuqing Long ◽  
Yanguang Chen
Keyword(s):  
Fractal Dimension ◽  
Clustering Algorithm ◽  
Scaling Law ◽  
Central Area ◽  
Direct Determination ◽  
Traffic Networks ◽  
Street Network ◽  
Urban Street ◽  
Street Networks ◽  
Multifractal Scaling

Traffic networks have been proved to be fractal systems. However, previous studies mainly focused on monofractal networks, while complex systems are of multifractal structure. This paper is devoted to exploring the general regularities of multifractal scaling processes in the street network of 12 Chinese cities. The city clustering algorithm is employed to identify urban boundaries for defining comparable study areas; box-counting method and the direct determination method are utilized to extract spatial data; the least squares calculation is employed to estimate the global and local multifractal parameters. The results showed multifractal structure of urban street networks. The global multifractal dimension spectrums are inverse S-shaped curves, while the local singularity spectrums are asymmetric unimodal curves. If the moment order q approaches negative infinity, the generalized correlation dimension will seriously exceed the embedding space dimension 2, and the local fractal dimension curve displays an abnormal decrease for most cities. The scaling relation of local fractal dimension gradually breaks if the q value is too high, but the different levels of the network always keep the scaling reflecting singularity exponent. The main conclusions are as follows. First, urban street networks follow multifractal scaling law, and scaling precedes local fractal structure. Second, the patterns of traffic networks take on characteristics of spatial concentration, but they also show the implied trend of spatial deconcentration. Third, the development space of central area and network intensive areas is limited, while the fringe zone and network sparse areas show the phenomenon of disordered evolution. This work may be revealing for understanding and further research on complex spatial networks by using multifractal theory.

scholarly journals The structure, centrality, and scale of urban street networks: Cases from Pre-Industrial Afro-Eurasia

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259680
Author(s):  
Mark Altaweel ◽  
Jack Hanson ◽  
Andrea Squitieri
Keyword(s):  
Urban Systems ◽  
Network Centrality ◽  
Street Network ◽  
Transport Costs ◽  
Urban Centers ◽  
Urban Settings ◽  
Urban Street ◽  
Street Networks ◽  
Linear Manner ◽  
Urban Sites

Cities and towns have often developed infrastructure that enabled a variety of socio-economic interactions. Street networks within these urban settings provide key access to resources, neighborhoods, and cultural facilities. Studies on settlement scaling have also demonstrated that a variety of urban infrastructure and resources indicate clear population scaling relationships in both modern and ancient settings. This article presents an approach that investigates past street network centrality and its relationship to population scaling in urban contexts. Centrality results are compared statistically among different urban settings, which are categorized as orthogonal (i.e., planned) or self-organizing (i.e., organic) urban settings, with places having both characteristics classified as hybrid. Results demonstrate that street nodes have a power law relationship to urban area, where the number of nodes increases and node density decreases in a sub-linear manner for larger sites. Most median centrality values decrease in a negative sub-linear manner as sites are larger, with organic and hybrid urban sites’ centrality being generally less and diminishing more rapidly than orthogonal settings. Diminishing centrality shows comparability to modern urban systems, where larger urban districts may restrict overall interaction due to increasing transport costs over wider areas. Centrality results indicate that scaling results have multiples of approximately ⅙ or ⅓ that are comparable to other urban and road infrastructure, suggesting a potential relationship between different infrastructure features and population in urban centers. The results have implications for archaeological settlements where urban street plans are incomplete or undetermined, as it allows forecasts to be made on past urban sites’ street network centrality. Additionally, a tool to enable analysis of street networks and centrality is provided as part of the contribution.

scholarly journals Planarity and Street Network Representation in Urban Form Analysis

2018 ◽  
Author(s):  
Geoff Boeing
Keyword(s):  
Real World ◽  
Travel Behavior ◽  
Urban Form ◽  
Design Patterns ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Two Dimensions ◽  
Street Network ◽  
Form Analysis ◽  
Street Networks

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.

scholarly journals The Relative Circuity of Walkable and Drivable Urban Street Networks

2017 ◽  
Author(s):  
Geoff Boeing
Keyword(s):  
Urban Space ◽  
Network Structure ◽  
Past Research ◽  
Street Network ◽  
Urban Street ◽  
Street Networks ◽  
Straight Line ◽  
And Performance ◽  
Relative Structure ◽  
Us Cities

Circuity, the ratio of network distances to straight-line distances, is an important measure of urban street network structure and transportation efficiency. Circuity results from a circulation network’s configuration, planning, and underlying terrain. In turn, it impacts how humans use urban space for settlement and travel. Although past research has examined overall street network circuity, researchers have not studied the relative circuity of walkable versus drivable circulation networks. To address this gap, this study uses OpenStreetMap data to explore relative network circuity. We download walkable and drivable networks for 40 US cities using the OSMnx software, which we then use to simulate two million routes and analyze circuity to characterize network structure. We find that walking networks tend to allow for more direct trips than driving networks do in most cities: average driving circuity exceeds average walking circuity in all but four of the cities that exhibit statistically significant differences between network types. We discuss various reasons for this phenomenon, illustrated with case studies. Network circuity also varies substantially between different types of places. These findings underscore the value of using network-based distances rather than straight-line distances when studying urban travel and access. They also suggest the importance of differentiating between walkable and drivable circulation networks when modeling and characterizing urban street networks: although different modes’ networks overlap in any given city, their relative structure and performance vary in most cities.

Topological Analysis of Urban Street Networks

10.1068/b306 ◽  
2004 ◽  
Vol 31 (1) ◽  
pp. 151-162 ◽  
Author(s):  
Bin Jiang ◽  
Christophe Claramunt
Keyword(s):  
Topological Analysis ◽  
Small World ◽  
Clustering Coefficient ◽  
Graph Representation ◽  
Small World Networks ◽  
Street Network ◽  
Scale Free ◽  
Urban Street ◽  
Street Networks ◽  
Functional Graph

The authors propose a topological analysis of large urban street networks based on a computational and functional graph representation. This representation gives a functional view in which vertices represent named streets and edges represent street intersections. A range of graph measures, including street connectivity, average path length, and clustering coefficient, are computed for structural analysis. In order to characterise different clustering degrees of streets in a street network they generalise the clustering coefficient to a k-clustering coefficient that takes into account k neighbours. Based on validations applied to three cities, the authors show that large urban street networks form small-world networks but exhibit no scale-free property.

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