Global Subway Systems Learning Module

Subways are a popular form of public transportation worldwide, given their speed, capacity, and lack of reliance on road infrastructure and conditions. Proponents argue that the ease of movement that subways provide promotes growth, helps sustain urbanization, and reduces pollution by diverting traffic from other forms of transportation. However, subways are expensive to build and maintain, and some argue they can divert city resources away from forms of transportation and infrastructure that better serve low-income populations. With these conflicting effects and differing city priorities, studies of subway systems and growth in metropolitan areas can provide tremendous insight for policy makers and urban planners trying to best serve their cities.

A new dataset from “Subways and Urban Growth: Evidence from Earth” (2018), by Marco Gonzalez-Navarro and Matthew Turner, makes incorporating subways into analyses possible for researchers worldwide by providing a record of all global subway stations with their geographic coordinates, dates of construction, mapped routes, and ridership over time. Now updated through 2017, these thoroughly compiled records are a previously unavailable trove of information.

The Geo4Dev tutorial makes utilizing this novel data accessible to all audiences regardless of technical ability, demonstrating all code required to import the subway data, select locations or stations of interest, create summary statistics, and build maps and graphical visualizations. It concludes by replicating the first difference regressions used in “Subways and Urban Growth: Evidence from Earth” to identify the effect of subway systems on ridership of both subways and buses. Users of this tutorial will be provided with all the tools required to begin leveraging this resource for work in research across objectives and disciplines.

Data and Resources

Global Subways Data Tutorial

HTML

Full tutorial on the use of the Global Subways dataset.

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Subways and Urban Growth: Evidence from Earth

Paper replicated in usage example

Authors

Marco Gonzalez-Navarro and Matthew Turner

Publish Date

2018

Journal

Journal of Urban Economics

Abstract

We investigate the relationship between the extent of a city’s subway network, its population and its spatial configuration. For the 632 largest cities in the world we construct panel data describing population, measures of centralization calculated from lights at night data, and the extent of each of the 138 subway systems in these cities. These data indicate that large cities are more likely to have subways but that subways have an economically insignificant effect on urban population growth. Our data also indicate that subways cause cities to decentralize, although the effect is smaller than previously documented effects of highways on decentralization. For a subset of subway cities we observe panel data describing subway and bus ridership. For those cities we find that a 10% increase in subway extent causes about a 6% increase in subway ridership and has no effect on bus ridership.

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Field	Value
Author(s)	Natalie Ayers
Last Updated	August 10, 2021, 16:14 (UTC)
Created	August 10, 2021, 15:21 (UTC)
Stable Link	https://learn.geo4.dev/Subways-Learning-Module.html
Date	2021-08-10
Content Type	Training Materials
Primary Category	Governance & Management
Sub Category	Infrastructure and Transportation
Country Name	Global, Greece
Associated Datasets	Global Subways Data (https://www.dropbox.com/s/dm13mcrkhhhkrll/subway_census_v1.7z?dl=0)
Publishing Organization	Center for Effective Global Action

Dataset

Global Subway Systems Learning Module

Data and Resources

Global Subways Data Tutorial

Subways and Urban Growth: Evidence from Earth

Tags

Additional Info