Date of Award
Open Access Thesis
College of Arts and Sciences
Accessibility measurement has always been an important question in different areas including transportation, urban planning, politics, and sociology. However, how to measure transportation accessibility in different areas have been limited to data availability and technology. Recently, with increasing availability in public transportation data, we found a gap between current methods and large volume of data now available. This thesis developed a new method to measure multi-mode transportation data, including taxi, bus, and subway. Based on this measurement, we can visualize and understand the spatiotemporal patterns of accessibility in New York City (NYC). With historical travel records and public transit schedule, Relative Index (RI) is developed in this thesis to measure and compare the differences in the accessibility in NYC. RI distribution patterns during different time periods were also compared and analyzed for more information about transportation in NYC. By the end of this thesis, a practical application that measured accessibility for nine major hospitals in NYC was provided. Results in this thesis showed that subways have more impacts about accessibility than bus. Also, service frequency during different time of a day has affect accessibility.
Jiang, Y.(2017). Urban Accessibility Measurement and Visualization — A Big Data Approach. (Master's thesis). Retrieved from https://scholarcommons.sc.edu/etd/4136