An open software environment to make spatial access metrics more accessible

James Saxon, Julia Koschinsky (), Karina Acosta, Vidal Anguiano, Luc Anselin and Sergio Rey
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James Saxon: University of Chicago
Julia Koschinsky: University of Chicago
Vidal Anguiano: University of Chicago
Luc Anselin: University of Chicago
Sergio Rey: University of California

Journal of Computational Social Science, 2022, vol. 5, issue 1, No 12, 265-284

Abstract: Abstract This article introduces a new open software environment to support the measurement of a range of accessibility indices at scales going from the local to the national. In practice, the use of such indices has been impeded by the lack of open resources and the computational burden associated with large scale analyses. The environment consists of three parts: a new package, access, as part of the Python-based PySAL Spatial Analysis Library, a user-friendly point-and-click web implementation of the access computations, and support for the calculation of large-scale travel cost matrices, including a set of pre-computed origin-destination distance matrices for all the census tracts in the U.S. and census blocks in the 20 major cities. All three elements are open source and free to use. After motivating the development of the software environment, and situating the problem of access measurement in the literature, we briefly describe six commonly used access metrics. We then discuss in more detail the three important components of our software infrastructure. We close with an empirical illustration pertaining to access to health care providers, comparing the approach in the package to that taken in the web application.

Keywords: Spatial access; Open science; Travel time computation (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s42001-021-00126-8

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