EVALUATING THE ACCESSIBILITY OF RESIDENTIAL AREAS FOR BICYCLING AND WALKING USING GIS

Abstract

Accessibility, or the ease of travel between two locations, is an appropriate measure for walking and cycling because of the heavily constrained nature of walking and cycling trips. Much attention has been focused in recent years on the connection between the built environment and the transportation system. This relationship is especially relevant for walking and cycling as literature has shown that spatial layout and infrastructure design are significant factors in the ability to make walking and cycling trips. Unfortunately, a quality method does not exist to quantify walking and cycling accessibility. Most accessibility measures have concentrated on the macro level while walking and cycling by nature occurs mainly at the micro level. The few attempts at measuring micro-scale accessibility have serious drawbacks. This thesis synthesized recent research on the connection between the built environment and transportation to develop a new accessibility measure that can identify areas conducive to walking and biking. This measure, the Pedestrian and Cycling Accessibility Measure (PCAM), is based on the concept of the 3Ds, or density, diversity, and design. Corresponding to this research, the PCAM first considers the proximity of residential areas to specific destinations within walking and biking ranges (density) and the mix of destinations immediately surrounding these destinations (diversity). This part of the PCAM demonstrates the potential for walking and biking trips in a given area. Once this analysis is complete, the physical design of the pedestrian and cycling infrastructure (or lack thereof) are examined to determine if the necessary infrastructure is in place to support the potential walking and biking travel (design). After developing the PCAM, a geographic information system (GIS) was used to implement the measure and display the results. The PCAM was applied to the Charlottesville/Albemarle region of Virginia to demonstrate the results of the analysis and the capabilities of GIS for calculating and displaying accessibility. The GIS results show that this analysis presents a large amount of detail over the study area and can be displayed in a variety of ways. The regional maps give an overview of accessibility for the study area showing that it is highest in the high-density, mixed-use areas. Any point on the map can be queried to reveal how the PCAM score was calculated for that specific point. Map layers can also be used for more in-depth calculation such as subtracting the actual infrastructure design from the potential accessibility to reveal areas in need of infrastructure improvements. While there were some limitations to the analysis due to unavailable or inadequate data, the GIS application proved to be an ideal environment for measuring accessibility. GIS is well suited to handle the spatial nature of the data and the number of calculations necessary to calculate the PCAM. The mapping features of GIS and ability to view the underlying data for the maps allow the results to be presented in a number of useful ways.

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