The role of transport systems in housing insecurity: a mobility-based analysis
dc.contributor.author | Iyer, N | |
dc.contributor.author | Menezes, R | |
dc.contributor.author | Barbosa, H | |
dc.date.accessioned | 2024-09-17T11:56:28Z | |
dc.date.issued | 2024-07-17 | |
dc.date.updated | 2024-09-17T11:24:19Z | |
dc.description.abstract | With trends of urbanisation on the rise, providing adequate housing to individuals remains a complex issue to be addressed. Often, the slow output of relevant housing policies, coupled with quickly increasing housing costs, leaves individuals with the burden of finding housing that is affordable and in a safe location. In this paper, we unveil how transit service to employment hubs, not just housing policies, can prevent individuals from improving their housing conditions. We approach this question in three steps, applying the workflow to 20 cities in the United States of America. First, we propose a comprehensive framework to quantify housing insecurity and assign a housing demographic to each neighbourhood. Second, we use transit-pedestrian networks and public transit timetables (GTFS feeds) to estimate the time it takes to travel between two neighbourhoods using public transportation. Third, we apply geospatial autocorrelation to identify employment hotspots for each housing demographic. Finally, we use stochastic modelling to highlight how commuting to areas associated with better housing conditions results in transit commute times of over an hour in 15 cities. Ultimately, we consider the compounded burdens that come with housing insecurity, by having poor transit access to employment areas. In doing so, we highlight the importance of understanding how negative outcomes of housing insecurity coincide with various urban mechanisms, particularly emphasising the role that public transportation plays in locking vulnerable demographics into a cycle of poverty. | en_GB |
dc.identifier.citation | Vol. 13(1), article 49 | en_GB |
dc.identifier.doi | https://doi.org/10.1140/epjds/s13688-024-00489-8 | |
dc.identifier.uri | http://hdl.handle.net/10871/137477 | |
dc.identifier | ORCID: 0000-0002-3927-969X (Barbosa, Hugo) | |
dc.language.iso | en | en_GB |
dc.publisher | Springer | en_GB |
dc.relation.url | https://data.census.gov/ | en_GB |
dc.relation.url | https://evictionlab.org/eviction-tracking/ | en_GB |
dc.relation.url | https://data.sfgov.org/Housing-and-Buildings/Eviction-Notices/5cei-gny5 | en_GB |
dc.relation.url | https://data.cityofnewyork.us/City-Government/Evictions/6z8x-wfk4 | en_GB |
dc.relation.url | https://lehd.ces.census.gov/data/lodes/ | en_GB |
dc.relation.url | https://github.com/nandini10/Housing-Insecurity | en_GB |
dc.rights | © The Author(s) 2024. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ | en_GB |
dc.subject | Housing Insecurity | en_GB |
dc.subject | Human Mobility | en_GB |
dc.subject | Transit Networks | en_GB |
dc.subject | Commuting Patterns | en_GB |
dc.subject | Social Mobility | en_GB |
dc.title | The role of transport systems in housing insecurity: a mobility-based analysis | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2024-09-17T11:56:28Z | |
dc.identifier.issn | 2193-1127 | |
exeter.article-number | 49 | |
dc.description | This is the final version. Available on open access from Springer via the DOI in this record | en_GB |
dc.description | Data availability: The census and geographic data datasets analysed during the current study are available at https://data.census.gov/ The eviction datasets analysed during the current study are available, for most cities, are available at https://evictionlab.org/eviction-tracking/. The eviction rates for San Francisco and New York can be found at https://data.sfgov.org/Housing-and-Buildings/Eviction-Notices/5cei-gny5 and https://data.cityofnewyork.us/City-Government/Evictions/6z8x-wfk4, respectively. The commuting datasets analysed during the current study are available in the LODES7 repository, https://lehd.ces.census.gov/data/lodes/ Code for reproducing the framework for identifying census tracts based on their vulnerability to housing insecurity, as well as housing demographics’ employment hotspots is available at https://github.com/nandini10/Housing-Insecurity | en_GB |
dc.identifier.eissn | 2193-1127 | |
dc.identifier.journal | EPJ Data Science | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2024-07-01 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2024-07-17 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2024-09-17T11:55:06Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2024-09-17T11:56:35Z | |
refterms.panel | B | en_GB |
refterms.dateFirstOnline | 2024-07-17 |
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in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not
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holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/