Rethinking prism anchors: investigating space-time fixity and flexibility of activities using GPS-enabled activity-travel survey data

Keywords: Time Geography, Space-Time Prism Anchor, Spatio-Temporal Analysis, GPS-enable Survey Data
Session Type: Virtual Paper Abstract
Day: Friday
Session Start / End Time: 2/25/2022 02:00 PM (Eastern Time (US & Canada)) - 2/25/2022 03:20 PM (Eastern Time (US & Canada))
Room: Virtual 26

Abstract

Space-time prism is a fundamental concept in time geography that can model an individual’s accessibility to resources under space-time constraints. A prism anchor is defined by activity with a fixed location that cannot be easily rescheduled such as work and school. Trips and other activities such as shopping and recreation are relatively flexible and hence scheduled between prism anchors. However, this fixed-flexible dichotomy cannot capture the increasing complexity of human mobility such as multiple working locations, or inter-person variations regarding scheduling flexibility. To refine the definition of prism anchor, this paper develops a framework to derive personalized prism anchors from person-level mobility data that considers spatial and temporal fixity. For spatial fixity, we apply various spatial indices to distinguish stationary/non-stationary activities and identify the number of representative activity locations. For spatial-temporal fixity, we first use repetitive ratios to measure how frequently an activity repetitively occurs across days. Then, we extract the time intervals when repetitive activities happen at each representative location. Last, we use repetitive intervals and representative locations to define personalized prism anchors. To illustrate our methods, we use two sets of GPS-enabled activity-travel survey data collected in Minnesota, U.S., and Beijing, China. The results suggest that home, work, and school activities were not always fixed in space or time. Our data-driven approaches can derive suitable metrics for each activity type and study area and align well with social-demographic backgrounds. These findings can contribute to a better understanding of individuals’ activity-travel patterns and more accurate estimations of person-based accessibility.