Using GIS to measure the effect of overlapping service areas on passenger boardings at bus stops

URISA Journal

Volumn 19, Issue 1, 2007, Pages 5-11

  Kimpel, Thomas J ^a   Dueker, Kenneth J ^a   El Geneidy, Ahmed M ^b  

^a PORTLAND STATE UNIVERSITY   (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34548141900     PISSN: 10458077     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (22)

1. Ammons, D. N. 2001. Municipal benchmarks: assessing local performance and establishing community standards. Thousand Oaks, CA: Sage Publications.
2. Azar, K. T., and J. E Ferreira. 1994. Integrating geographic information systems into transit ridership forecast models. Journal of Advanced Transportation 29(3): 263-79.
3. Chu, X. 2004. Ridership models at the stop level. Tampa, FL: Center for Urban Transportation Research, University of South Florida, Report No. BC137-31.
4. Furth, R G., B. Hemily, T. H. Mueller, and J. G. Strathman. 2003. Uses of archived AVL-APC data to improve transit performance and management: review and potential. Washington, D.C.: Transportation Research Board. TRCP Report No. 23 (Project H-28), http://gulliver.trb.org/publications/ tcrp/tcrp_webdoc_23.pdf.
5. Handy, S. L., and D. A. Niemeier. 1997. Measuring accessibility: An exploration of issues and alternatives. Environment and Planning A 29(7): 1,175-94.
6. Hansen, W. 1959. How accessibility shapes land use. Journal of the American Institute of Planners 25(2): 73-76.
7. Hartgen, D., and M. W. Horner. 1997. A route-level transit ridership forecasting model for lane transit district: Eugene, Oregon. Charlotte, NC: Center for Interdisciplinary Transportation Studies, Report No. 170.
8. Horowitz, A. J. 1984. Simplifications for single-route transit ridership forecasts. Transportation 12: 261-75.
9. Hsiao, S., J. Lu, J. Sterling, and M. Weatherford. 1997. Use of geographic information system for analysis of transit pedestrian access. Transportation Research Record 1604: 50-59.
10. Kemp, M. A. 1981. A simultaneous equations analysis of route demand and supply, and its application to the San Diego bus system. Washington, D.C.: UMTA, Report DTUM-60-80-71001.
11. Kimpel, T. J. 2001. Time point-level analysis of transit service reliability and passenger demand. Portland, OR: Unpublished Doctor of Philosophy in Urban Studies, Portland State University.
12. Kittelson and Associates. 2003. Transit capacity and quality of service manual. Washington, D.C.: U.S. Department of Transportation.
13. Levinson, H. S., and O. Brown-West. 1984. Estimating bus ridership. Transportation Research Record 994: 8-12.
14. Makri, M., and C. Folkesson. 1999. Accessibility measures for analyses of land-use and travelling with geographical information systems. Department of Technology and Society, Lund Institute of Technology, Sweden, 1- 17.
15. Miller, H., and S. Shaw. 2001. Geographic information systems for transportation: principles and applications. New York: Oxford University Press.
16. Neilson, G., and W. Fowler. 1972. Relation between transit ridership and walking distances in a low-density Florida retirement area. Highway Research Record 403: 26-34.
17. O'Neill, W. A., R. D. Ramsey, and J. Chou. 1992. Analysis of transit service areas using geographic information systems. Transportation Research Record 1364: 131-38.
18. Peng, Z., and K.J. Ducker. 1995. Spatial dataintegration in route-level transit demand modeling. URISA Journal 7: 26-37.
19. Song, S. 1996. Some tests of alternative accessibility measures: A population density approach. Land Economics 72(4): 474-82.
20. Vuchic, V. 2005. Urban transit: operations, planning and economics. Hoboken, NJ: John Wiley and Sons, Inc.
21. Zhao, F. 1998. GIS analysis of the impact of community design on transit accessibility. Proceedings of the ASCE South Florida Section 1998 Annual Meeting, Sanibel Island, Florida, 1-12.
22. Zhao, F., L. Chow, M. Li, I. Ubaka, and A. Gan. 2003. Forecasting transit walk accessibility: regression model alternative to buffer method. Transportation Research Record 1835: 34-41.