Authors: Ying Song*, University of Minnesota - Minneapolis, MN, Yingling Fan, University of Minnesota - Twin Cities, Julian Wolfson, University of Minnesota - Twin Cities
Topics: Geographic Information Science and Systems, Transportation Geography, Spatial Analysis & Modeling
Keywords: smartphone-based activity survey, individual movement trajectories, object-oriented programming, spatiotemporal database
Session Type: Paper
Start / End Time: 1:10 PM / 2:50 PM
Room: Roosevelt 3, Marriott, Exhibition Level
Presentation File: No File Uploaded
Recent developments in location-aware technologies and georeferenced social media enables us to track individual movement and activity participation in urban space across time. However, these sources are usually “data-thin” and lack contextual information. By contrast, activity diaries are “data-rich” but are limited by their retrospective nature and do not contain spatial information such as trip route and activity location. Smartphone-based activity surveys can contextualize movement trajectories by allowing participants to provide their social-demographic profiles, actual trip purposes and travel modes, and schematic attributes such as their emotion status. This paper proposes a framework to organize and analyze these smartphone-based activity surveys. First, we define classes, methods and functions to use for building a spatiotemporal database and for object-oriented programming. We also discuss data types and behavior rules for database management. Then, the paper presents a taxonomy for analyzing individual mobility and accessibility using these classes, methods and functions. To illustrate the data schema and methods, the paper uses data collected by the Daynamica smartphone app in the Twin Cities metro area in Minnesota and investigates emotion changes associated with activity participations and modes of travel.