Authors: Jinwoo Park*, Texas A&M University, Jeon-Young Kang, Kongju National University, Daniel Goldberg, Texas A&M University
Topics: Geographic Information Science and Systems
Keywords: GIS, Spatial Analysis, Spatial Accessibility, Temporal Dynamics, Temporal Clustering, Electric Vehicle Charging Station
Session Type: Virtual Paper
Start / End Time: 3:05 PM / 4:20 PM
Room: Virtual 14
Presentation File: No File Uploaded
The static measurement of spatial accessibility disregards temporal variation in input variables (i.e., supply, demand, and mobility) so that its measures might fail to project practical accessibility. However, incorporating temporal dynamics in the input variables into the measurement is expected to address the issue by enhancing the temporal resolution of measures and describing the temporal fluctuation of measures. Hence, this study aims to examine 24-hour fluctuation of spatial accessibility and delineate significant temporal changes by taking electric vehicle (EV) charging stations in Seoul as a case study. Specifically, we measured each hour’s accessibility over 24 hours based on a complete set of temporally dynamic input variables. Then, we temporally clustered the 24-hour measures of accessibility with the K-means clustering method and compared the clustering results to the static measurement of accessibility. As results, we identified the three significant temporal clusters in the accessibility measures (i.e., nighttime, daytime, and afternoon rush hour) and revealed that the static measurement did not reflect the accessibility during nighttime and afternoon rush hour, which was the expected usage time. Therefore, our approach would shed light on an enhanced assessment of accessibility to urban infrastructure and would help policymakers’ decision-making process about spatial allocations of urban infrastructure.