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Related Experiment Video

Updated: Jan 15, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
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Raw and pre-processed cruise passengers' GPS tracking datasets.

Mauro Ferrante1, Andrea Perri2, Stefano De Cantis3

  • 1Department of Culture and Society, University of Palermo. Viale delle Scienze - Ed. 15, 90128 Palermo Italy.

Data in Brief
|October 13, 2025
PubMed
Summary

This study pioneers GPS tracking for cruise passenger behavior analysis, offering valuable spatio-temporal data and a novel algorithm for data cleaning. The freely available dataset aids research in tourism and human mobility.

Keywords:
Global positioning system (GPS)Pre-ProcessingTourist mobilityTracking technology

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Area of Science:

  • Tourism Research
  • Human Mobility Studies
  • Geographic Information Systems (GIS)

Background:

  • Global Positioning System (GPS) technology provides precise spatio-temporal data crucial for understanding human mobility patterns.
  • Existing research has not extensively utilized GPS technology for analyzing the specific behavior of cruise passengers at tourist destinations.

Purpose of the Study:

  • To investigate the spatio-temporal behavior of cruise passengers at their destination using GPS technology.
  • To introduce a novel algorithm for pre-processing GPS data, including outlier detection and imputation.
  • To make a valuable dataset of cruise passenger mobility freely available for further research.

Main Methods:

  • Selected cruise passengers carried GPS data loggers recording geographic coordinates and timestamps.
  • A pseudo-systematic sampling strategy was used to select participants.
  • A custom algorithm employing dynamic moving medians was developed to clean and impute GPS data, considering temporal and spatial distances.

Main Results:

  • The study successfully applied GPS technology to gather detailed spatio-temporal insights into cruise passenger behavior.
  • The developed algorithm effectively identified and corrected noise points and missing values in GPS data.
  • Demonstrated efficacy of the data processing algorithm using cruise passenger data from Palermo, Italy.

Conclusions:

  • GPS technology offers significant potential for in-depth analysis of tourist behavior and human mobility.
  • The pre-processed dataset and developed algorithm contribute to advancing methodologies in tourism research and mobility studies.
  • Making such datasets openly available fosters collaborative development and broader application in urban planning, transportation, and tourism.