Measuring and Visualizing Place-Based Space-Time Job Accessibility
Document Type
Article
Publication Date
2019
Keywords
Census Transportation Planning Products (CTPP), Dasymetric mapping, Gravity-based model, Space-time job accessibility, Volumetric rendering
Digital Object Identifier (DOI)
https://doi.org/10.1016/j.jtrangeo.2018.12.002
Abstract
Place-based accessibility measures, such as the gravity-based model, are widely applied to study the spatial accessibility of workers to job opportunities in cities. However, gravity-based measures often suffer from three main limitations: (1) they are sensitive to the spatial configuration and scale of the units of analysis, which are not specifically designed for capturing job accessibility patterns and are often too coarse; (2) they omit the temporal dynamics of job opportunities and workers in the calculation, instead assuming that they remain stable over time; and (3) they do not lend themselves to dynamic geovisualization techniques. In this paper, a new methodological framework for measuring and visualizing place-based job accessibility in space and time is presented that overcomes these three limitations. First, discretization and dasymetric mapping approaches are used to disaggregate counts of jobs and workers over specific time intervals to a fine-scale grid. Second, Shen's (1998) gravity-based accessibility measure is modified to account for temporal fluctuations in the spatial distributions of the supply of jobs and the demand of workers and is used to estimate hourly job accessibility at each cell. Third, a four-dimensional volumetric rendering approach is employed to integrate the hourly job access estimates into a space-time cube environment, which enables the users to interactively visualize the space-time job accessibility patterns. The integrated framework is demonstrated in the context of a case study of the Tampa Bay region of Florida. The findings demonstrate the value of the proposed methodology in job accessibility analysis and the policy-making process.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Journal of Transport Geography, v. 74, p. 278-288
Scholar Commons Citation
Hu, Yujie and Downs, Joni A., "Measuring and Visualizing Place-Based Space-Time Job Accessibility" (2019). School of Geosciences Faculty and Staff Publications. 1454.
https://digitalcommons.usf.edu/geo_facpub/1454