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A Multidirectional Optimal Ecotope-Based Algorithm to Delineate a Commuter Shed

2016; Volume: 1; Linguagem: Inglês

10.21433/b3116z0905hw

2573-783X

Daniel Schleith, Michael J. Widener,

Human Mobility and Location-Based Analysis

GIScience 2016 Short Paper Proceedings A Multidirectional Optimal Ecotope-Based Algorithm to Delineate a Commuter Shed D. Schleith, M. J. Widener University of Cincinnati, 401 Braunstein Hall, Cincinnati, OH 45221-0131 Email: schleidk@mail.uc.edu University of Toronto, Sidney Smith Hall, 100 St. George St, Room 5037, Toronto, ON M5S 3G3 Email: michael.widener@utoronto.ca 1. Introduction In commuting research the geographic area under investigation is of crucial importance. When examining commutes occurring in a region of interest, the selection and use of different city, county, or metropolitan region boundaries will have a large impact on analyses of travel times and distances, whether a transit network provides adequate access to jobs, levels of congestion, and so on. This is closely linked to the spatial form of cities (especially in the North American context) where a relatively dense city is surrounded by suburbs with progressively lower densities. Determining what actually constitutes a commuting region (or “commuter shed”) is typically a matter of using administrative boundaries prescribed by the U.S. Census Bureau. In general though, the metropolitan region is often used because it represents a big enough area to capture most of the economic activity occurring inside. The issue with metropolitan boundaries, however, is summarized in Morrill et al. (1999), “… metropolitan areas are widely recognized as far from consistent in meaning or adequate in definition.” The problem is largely attributed to the use of counties as building blocks. Counties that are selected to comprise a metropolitan region are those neighboring the county or counties containing the largest principal city. The neighboring counties are included if they are socially and economically connected to the principal county, as measured by the number of commuters coming into the central county (Office of Management and Budget, 2010). Counties have a large spatial extent, and oftentimes include vast rural spaces with little relationship to the urbanized area of interest to many researchers. A method for providing a more precise measure is warranted. In many ways a commuter shed is like a cluster of commuting activity, where there are significant links between residents moving between relevant, contiguous zones. Here, we use a cluster detection method to delineate the commuter sheds of the counties that make up the Miami, FL metro region. We take census tracts as the building blocks to provide a more precise representation of the commuter shed, and test the spatial interaction of these tracts using the percentage of commutes into the various zones and an advanced spatial clustering statistic.! 2. Relevant Literature As previously mentioned, commuter sheds are the de facto analysis areas of most commuting research, the results of which are sensitive to the definition of the study area. Researchers are therefor interested in these definitions, as they attempt to accurately describe settlement patterns across the country and provide a reasonable assessment of how people move within an urban region. The current method used by the US Census examines the “percent of commutes” in a county to the nearest county containing a central city. So, an outlying county is included if it has at least 15% of its commuters working in that central county (or counties). But an outlying county can only be assigned to one central county and the determination is made based on commutes from the possible central counties added to commutes to the central county.