Credit, Kevin and Arnao, Zander (2023) A method to derive small area estimates of linked commuting trips by mode from open source LODES and ACS data. Environment and Planning B: Urban Analytics and City Science, 50 (3). pp. 709-722. ISSN 2399-8083

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Abstract

This paper describes a fully customizable open source method to create linked origin-destination data on commuting flows by mode at the Census tract scale by combining LODES and ACS data from the US Census Bureau. With additional work, the method could be scaled to the entire US (with a small number of exceptions) for every year from 2002 to 2019. For demonstration purposes, the paper applies this method to 2015 commuting flows in Cook County, Illinois. At an aggregate scale, the results of this application show that commuting by all modes is dominated by travel to large regional employment centres. However, the pattern is more localised for the walking mode, and focused along corridors of mode-specific infrastructure investment for the cycling and transit modes, as might be expected. The auto and work from home modes demonstrate the most distributed pattern of travel, revealing more instances of commuting to regional sub-centres than the other modes.

Item Type:	Article
Keywords:	Travel behaviour; commuting; big data; transportation modelling; urban analytics;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG Faculty of Social Sciences > Geography Faculty of Social Sciences > Research Institutes > Maynooth University Social Sciences Institute, MUSSI
Item ID:	18663
Identification Number:	https://doi.org/10.1177/23998083221129614
Depositing User:	Kevin Credit
Date Deposited:	18 Jun 2024 12:00
Journal or Publication Title:	Environment and Planning B: Urban Analytics and City Science
Publisher:	SAGE Publications
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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