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Trajectory Data Analyses for Pedestrian Space-time Activity Study

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GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data.

Shuai Zhou¹, Yanling Li¹, Guangqing Chi¹

¹The Pennsylvania State University, University Park, PA 16801, USA.

Journal of Behavioral Data Science

|March 14, 2022

Summary

This summary is machine-generated.

This study introduces GPS2space, a Python library for processing Global Positioning System (GPS) data to analyze individual activity spaces and shared spaces. It simplifies extracting meaningful mobility and behavioral patterns from raw GPS coordinates.

Keywords:

Python behavior genetics latent growth curve model spatial measure twins

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Area of Science:

Behavioral Science
Geographic Information Systems (GIS)
Computational Social Science

Background:

Global Positioning System (GPS) data from digital devices offer insights into behavioral patterns.
Raw GPS data requires significant processing to reveal individual mobility and activity dynamics.
Behavioral scientists often lack the expertise for complex GPS data integration and analysis.

Purpose of the Study:

Introduce GPS2space, a free, open-source Python library for processing GPS data.
Facilitate the integration of GPS data with Geographic Information Systems (GIS).
Enable the extraction of key spatial features: individual activity space and shared space.

Main Methods:

Developed GPS2space, a Python library for GPS data processing and GIS integration.
Utilized data from the Colorado Online Twin Study for demonstration.
Extracted and analyzed individual activity space and twin siblings' shared space.

Main Results:

Demonstrated GPS2space's utility in exploring seasonal and age-related changes in activity space.
Showcased analysis of gender, zygosity, and age-related differences in shared space.
Successfully extracted spatial features relevant to intra-individual and inter-individual dynamics.

Conclusions:

GPS2space simplifies the analysis of complex GPS data for behavioral research.
The library facilitates the study of individual and shared spatial behaviors.
Future developments and potential applications of GPS2space were discussed.