A method to derive small area estimates of linked commuting trips by mode from open source LODES and ACS data. (March 2023)

• Record Type: Journal Article
• Authors: Credit, Kevin; Arnao, Zander
• Is Part Of: Environment & planning. Volume 50:Number 3(2023)
• Page Start: 709
• Page End: 722
• Publication Date: 2023-03
• Subjects: Travel behaviour -- commuting -- big data -- transportation modelling -- urban analytics; City planning -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.11605
• DOI: 10.1177/23998083221129614
• Languages: English
• ISSNs: 2399-8083

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.