Accessibility Futures

Recently published

  • Anderson, Paul, David Levinson and Pavithra Parthasarathi (2013) Accessibility Futures. Transactions in GIS, 2013, 17(5): 683–705



This study uses accessibility as a performance measure to evaluate a matrix of future land use and network scenarios for planning purposes. The concept of accessibility dates to the 1950s, but this type of application to transportation planning is new. Previous research has established the coevolution of trans- portation and land use, demonstrated the dependence of accessibility on both, and made the case for the use of accessibility measures as a planning tool. This study builds off of these findings by demonstrating the use of accessibility-based performance measures in the Twin Cities Metropolitan Area. This choice of performance measure also allows for transit and highway networks to be compared side-by-side. For roadway modeling, zone-to-zone travel time matrix was computed using stochastic user equilibrium (SUE) assignment with travel time feedback to trip distribution. A database of schedules was used on the transit networks to assign transit routes. This travel time data was joined with the land use data from each scenario to obtain the employment, population, and labor accessibility from each traffic analysis zone (TAZ) within specified time ranges. Tables of person-weighted accessibility were computed for 20 minutes with zone population as the weight for employment accessibility and zone employment as the weight for population and labor accessibility. Maps of accessibility by zone were produced to show the spatial distribution of accessibility across the region. The results show that a scenario where population and employment growth are concentrated in the center of the metropolitan area would produce the highest accessibility no matter which transportation network changes are made. However, another scenario which concentrates population growth in the center of the metropolitan area and shifts employment growth to the periphery consistently outperforms the scenario representing the projected 2030 land use without any growth management strategy.