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Development of a method for walking step observation based on large-scale GPS data.

Shohei Nagata1, Tomoki Nakaya2,3, Tomoya Hanibuchi1

  • 1Graduate School of Environmental Studies, Tohoku University, 468-1 Aoba, Aramaki, Aoba-ku, Sendai, 980-0845, Japan.

International Journal of Health Geographics
|September 7, 2022
PubMed
Summary

This study developed a method to estimate daily walking steps using large-scale global positioning system (GPS) data from smartphones. The findings show that urban environments and proximity to train stations encourage more steps, aiding public health research.

Keywords:
Big dataGlobal positioning systemsHuman mobilityPhysical activityWalking

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Area of Science:

  • Public Health
  • Geospatial Data Analysis
  • Epidemiology

Background:

  • Smartphone global positioning system (GPS) data offers potential for large-scale physical activity monitoring.
  • Limitations in commercial GPS data (e.g., personal attributes, activity specifics) have hindered its use in research.
  • This study addresses the need for methods to utilize large-scale GPS data for physical activity assessment.

Purpose of the Study:

  • To develop a simple method for estimating daily walking steps using large-scale global positioning system (GPS) data.
  • To investigate the relationship between land use and daily step counts within an activity space.
  • To enable retrospective, large-scale observation of physical activity for public health.

Main Methods:

  • Utilized smartphone GPS logs and step count data from users in Sendai City, Japan.
  • Modeled the relationship between land use exposure and daily step counts using a subset of data with step information.
  • Applied the developed model to a larger dataset of GPS logs to estimate and visualize geographic distribution of step counts.

Main Results:

  • Positive associations were found between visiting high-rise buildings, parks, public spaces, and railway areas and increased step counts.
  • Negative associations were observed with low-rise buildings and factory areas.
  • Daily step counts were higher in urban than suburban areas, with mitigation of decreased steps near train stations and a drop during heavy rainfall.

Conclusions:

  • The developed method demonstrates the feasibility of assessing walking steps using large-scale GPS logs.
  • Findings align with previous research on land use and physical activity.
  • The methodology can support future public health policies and interventions through large-scale physical activity monitoring.