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Measuring and visualizing place-based space-time job accessibility
Institution:1. Department of Civil Engineering, University of Toronto, 35 St George Street, Toronto, ON, M5S1A4, Canada;2. Transportation Consultant at Arup, 2 Bloor St E, Toronto, ON, M4W 1A8, Canada;1. Department of Spatial Science, Curtin University, Kent Street, Bentley, WA 6102, Australia;2. School of Design and the Built Environment, Curtin University, Kent Street, Bentley, WA 6102, Australia;3. School of Management, Hangzhou Dianzi University, Hangzhou 310018, China;4. Department of Architecture and Planning, University of Botswana, P/B 0061, Gaborone, Botswana
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.
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