These examples show several common usecases of trackintel.

The example data (found under examples/data) were generated or tracked using different tools:

• gpsies_trajectory.csv manually generated using GPSies.

• posmo_trajectory.csv automatically tracked using POSMO Segments, see also Android App Store and Apple App Store.

• geolife_trajectory.csv and pfs_tutorial.geojson is from the widely used Geolife trajectory dataset [1-3].

• google_trajectory.csv is a random excerpt from a location track by Google Maps.

Run any example as:

python preprocess_trajectories.py
python import_export_postgis.py
python setup_example_database.py

Several examples, such as preprocess_trajectories.py will generate output plots in the examples/out directory. For examples involving a database connection, you can adapt the config.json file.

[1] Yu Zheng, Lizhu Zhang, Xing Xie, Wei-Ying Ma. Mining interesting locations and travel sequences from GPS trajectories. In Proceedings of International conference on World Wild Web (WWW 2009), Madrid Spain. ACM Press: 791-800.

[2] Yu Zheng, Quannan Li, Yukun Chen, Xing Xie, Wei-Ying Ma. Understanding Mobility Based on GPS Data. In Proceedings of ACM conference on Ubiquitous Computing (UbiComp 2008), Seoul, Korea. ACM Press: 312-321.

[3] Yu Zheng, Xing Xie, Wei-Ying Ma, GeoLife: A Collaborative Social Networking Service among User, location and trajectory. Invited paper, in IEEE Data Engineering Bulletin. 33, 2, 2010, pp. 32-40.