Raw and pre-processed cruise passengers' GPS tracking datasets.

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.