Name
Abstract | ||
|---|---|---|
In commuting research the geographic area under investigation is of central 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 research examines two cluster detection methods to delineate the commuter shed of Miami, Florida and Cincinnati, Ohio. These clusters are then compared to a series of government delineated boundaries often used in commuting research for a jobs-housing balance analysis of each. The results of the clustering methods are different for the two regions due to the differing urban forms of each. The results demonstrate that the decision of what boundary to use for research on commuting can lead to drastically different results. While there is not necessarily any correct boundary, one may be more appropriate and the rationale for such should be more thoroughly discussed. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compenvurbsys.2018.04.004 | Computers, Environment and Urban Systems |
Keywords | Field | DocType |
Commuting,Commuter Shed,Spatial Clusters,MAUP | Miami,Data mining,Regional science,Cluster analysis,Metropolitan area,Geography,Government | Journal |
Volume | ISSN | Citations |
71 | 0198-9715 | 1 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| D. Schleith | 1 | 1 | 0.35 |
| Michael J. Widener | 2 | 9 | 1.26 |
| C. Kim | 3 | 1 | 0.69 |
| Lin Liu | 4 | 150 | 26.85 |