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Cityscape: Volume 20 Number 1 | Selected Outcomes of Housing Assistance


The goal of Cityscape is to bring high-quality original research on housing and community development issues to scholars, government officials, and practitioners. Cityscape is open to all relevant disciplines, including architecture, consumer research, demography, economics, engineering, ethnography, finance, geography, law, planning, political science, public policy, regional science, sociology, statistics, and urban studies.

Cityscape is published three times a year by the Office of Policy Development and Research (PD&R) of the U.S. Department of Housing and Urban Development.

Selected Outcomes of Housing Assistance

Volume 20, Number 1

Mark D. Shroder

Michelle P. Matuga

Do It Yourself: Obtaining Updated Transit Stop and Route Shapefiles in Urban and Nonurban Areas

Seva Rodnyansky
University of Southern California

Research that combines housing and transportation aims to jointly understand the elements of neighborhood accessibility, affordability, and sustainability. Access to highquality public transit and nonmotorized transportation helps reduce emissions and transportation costs for all households, including those with lower incomes. Transit access also expands the range of community destinations and shopping opportunities for those without cars. However, researchers often struggle to obtain accurate, geocoded data—especially in suburban and nonurban areas—on transit station locations, routes, and schedules. This article highlights a newer tool, the General Transit Feed Specification (GTFS) from Google, which provides an open source database of updated transit data. This free data source combines static and dynamic transit data and can be incorporated into analysis using geographic information system, or GIS, software. It also significantly eases cross-sectional, rural, and metropolitan-areawide analyses of housing using transportation as a key input. This article summarizes the GTFS data type, gives an overview of methods for using the data, explores current uses of the data, and suggests future applications.

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