scholarly journals Urban Street Network Analysis in a Computational Notebook

2020 ◽  
Author(s):  
Geoff Boeing
Keyword(s):  
Network Analysis ◽  
Street Network ◽  
Urban Street

scholarly journals Urban Street Network Analysis in a Computational Notebook

REGION ◽  
2020 ◽  
Vol 6 (3) ◽  
pp. 39-51 ◽  
Author(s):  
Geoff Boeing
Keyword(s):  
Network Analysis ◽  
Spatial Data ◽  
Street Network ◽  
Urban Street ◽  
Street Networks ◽  
Points Of Interest ◽  
The World ◽  
Study Sites ◽  
Python Package

Computational notebooks offer researchers, practitioners, students, and educators the ability to interactively run code and disseminate reproducible workflows that weave together code, visuals, and narratives. This article explores the potential of computational notebooks in urban analytics and planning, demonstrating their utility through a case study of OSMnx and its tutorials repository. OSMnx is a Python package for working with OpenStreetMap data and modeling, analyzing, and visualizing street networks anywhere in the world. Its official demos and tutorials are distributed as open-source Jupyter notebooks on GitHub. This article showcases this resource by documenting the repository and demonstrating OSMnx interactively through a synoptic tutorial adapted from the repository. It illustrates how to download and model street networks for various study sites, compute network indicators, visualize street centrality, calculate routes, and work with other spatial data such as building footprints and points of interest. Computational notebooks can empower guides for introducing methods to new users and can help researchers reach broader audiences interested in learning from, adapting, and remixing their work. Due to their utility and versatility, the ongoing adoption of computational notebooks in urban planning, analytics, and related geocomputation disciplines should continue into the future.

scholarly journals Urban Street Network Analysis in a Computational Notebook

2020 ◽  
Author(s):  
Geoff Boeing
Keyword(s):  
Network Analysis ◽  
Spatial Data ◽  
Street Network ◽  
Urban Street ◽  
Street Networks ◽  
Points Of Interest ◽  
The World ◽  
Study Sites ◽  
Python Package

Computational notebooks offer researchers, practitioners, students, and educators the ability to interactively conduct analytics and disseminate reproducible workflows that weave together code, visuals, and narratives. This article explores the potential of computational notebooks in urban analytics and planning, demonstrating their utility through a case study of OSMnx and its tutorials repository. OSMnx is a Python package for working with OpenStreetMap data and modeling, analyzing, and visualizing street networks anywhere in the world. Its official demos and tutorials are distributed as open-source Jupyter notebooks on GitHub. This article showcases this resource by documenting the repository and demonstrating OSMnx interactively through a synoptic tutorial adapted from the repository. It illustrates how to download urban data and model street networks for various study sites, compute network indicators, visualize street centrality, calculate routes, and work with other spatial data such as building footprints and points of interest. Computational notebooks help introduce methods to new users and help researchers reach broader audiences interested in learning from, adapting, and remixing their work. Due to their utility and versatility, the ongoing adoption of computational notebooks in urban planning, analytics, and related geocomputation disciplines should continue into the future.

scholarly journals A New Methodology to Study Street Accessibility: A Case Study of Avila (Spain)

2021 ◽  
Vol 10 (7) ◽  
pp. 491
Author(s):  
Manuel Curado ◽  
Rocio Rodriguez ◽  
Manuel Jimenez ◽  
Leandro Tortosa ◽  
Jose F. Vicent
Keyword(s):  
Network Analysis ◽  
The Other ◽  
Centrality Measures ◽  
Innovative Behavior ◽  
Street Network ◽  
Commercial Activity ◽  
Determining Factors ◽  
Combine Network ◽  
The City

Taking into account that accessibility is one of the most strategic and determining factors in economic models and that accessibility and tourism affect each other, we can say that the study and improvement of one of them involved the development of the other. Using network analysis, this study presents an algorithm for labeling the difficulty of the streets of a city using different accessibility parameters. We combine network structure and accessibility factors to explore the association between innovative behavior within the street network, and the relationships with the commercial activity in a city. Finally, we present a case study of the city of Avila, locating the most inaccessible areas of the city using centrality measures and analyzing the effects, in terms of accessibility, on the commerce and services of the city.

scholarly journals Global trends toward urban street-network sprawl

2020 ◽  
Vol 117 (4) ◽  
pp. 1941-1950 ◽  
Author(s):  
Christopher Barrington-Leigh ◽  
Adam Millard-Ball
Keyword(s):  
Time Series ◽  
Sustainable Urban Development ◽  
Street Network ◽  
High Resolution Data ◽  
Global Trends ◽  
Urban Street ◽  
Graph Theoretic ◽  
Time Period ◽  
Path Dependent ◽  
Changes Over Time

We present a global time series of street-network sprawl—that is, sprawl as measured through the local connectivity of the street network. Using high-resolution data from OpenStreetMap and a satellite-derived time series of urbanization, we compute and validate changes over time in multidimensional street connectivity measures based on graph-theoretic and geographic concepts. We report on global, national, and city-level trends since 1975 in the street-network disconnectedness index (SNDi), based on every mapped node and edge in the world. Streets in new developments in 90% of the 134 most populous countries have become less connected since 1975, while just 29% show an improving trend since 2000. The same period saw a near doubling in the relative frequency of a street-network type characterized by high circuity, typical of gated communities. We identify persistence in street-network sprawl, indicative of path-dependent processes. Specifically, cities and countries with low connectivity in recent years also had relatively low preexisting connectivity in our earliest time period. We discuss implications for policy intervention in road building in new and expanding cities as a top priority for sustainable urban development.

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 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.

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