Using Onthemap for the analysis of commuting distances of low-income workers in Shelby County, TN

Authors: Angela Antipova*, University of Memphis
Topics: Transportation Geography, Urban and Regional Planning, Urban Geography
Keywords: OnTheMap, low-income residential workers, commuting distances, travel
Session Type: Paper
Day: 4/4/2019
Start / End Time: 1:10 PM / 2:50 PM
Room: Jackson, Marriott, Mezzanine Level
Presentation File: No File Uploaded


We Used OnTheMap Version 6, a web-based mapping and reporting application to identify residential location of local labor force by category, specifically workers and low-income residential workers. To define a low-income worker and a low-income residential neighborhood, consistent criteria have been used. The former definition agreed with the wage-based definition of poverty for a full-time worker developed by the Economic Policy Institute using government data sources, while the identified residential areas of low-income workers are in agreement with prior research findings regarding residential location of low-wage workers in low-income families with children who are more likely to reside in central cities suggesting only a limited access to better-paying jobs in growing suburban areas among low-income workers (Acs and Nichols, 2007). 42 tracts out of 221 in total met this criterion of a designation as a residential low income neighborhood. Within these low income tracts, 35,289 resident workers (9.25%) lived in Shelby County, TN in 2010. Identified low income residential areas were exported in a shapefile format to transportation-analysis software TransCAD. To analyze job flows, part 3 of the 2006-2010 Census Transportation Planning Products (CTPP) was used which is organized by the commuting flows between residential and employment tracts. The file used in this study contains all tract pairs which present flows without distinguishing a mode of transportation. Using the O-D flow matrix, desire lines were produced to visualize where workers and low-income workers travel for work. We compared travel distance distribution for all workers and for low-income workers.

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