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Abstract

The focus of this manuscript is 1) to compute a transit accessibility index based on demographic/socio-economic characteristics and land use characteristics for each transit stop and route and the entire study area, and 2) identify inaccessible areas to provide an improved public transportation system that maximizes market potential. Transit accessibility indices were computed using spatially-extracted data within a pre-defined walking distance or time (0.25 miles or 5 minutes) for each transit stop (bus-stop) and route, and the entire study area. Results from linear regression analysis showed a statistically significant relationship between boardings and alightings, and the computed transit accessibility index based on demographic/socio-economic characteristics and land use characteristics for transit stops. The spatial distributions of computed transit accessibility indices were used to illustrate identification of spatial gaps, selection of ideal locations for transit stops along a route, extension of an existing route, identification of new transit routes, and expansion of transit area coverage.

DOI

http://dx.doi.org/10.5038/2375-0901.14.2.6

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