Density-based trajectory segmentation: the MigrO framework
Overview. MigrO is a platform for the extraction of individual mobility patterns from GPS trajectories, relying on the notion of stay region. A stay region is an 'attractive' area where the moving object resides for a period, possibly experiencing arbitrarily long periods of absence, before moving to a more attractive stay region. The core component is the SeqScan algorithm. MigrO is developed as plug-in for QGIS.
- F. Hachem, M.L. Damiani (2018). Periodic stops discovery through density-based trajectory segmentation. Demo. ACM SIGSPATIAL
- https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/JCICNL. Replication Data for: Cluster-based trajectory segmentation with local noise.
- M.L. Damiani, F. Hachem, H. Issa et al. (2018). Cluster-based trajectory segmentation with local noise (2018). Data Mining and Knowledge Discovery.
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- H. Hachem, M.L. Damiani, H.Issa (2017). Discovering Gatherings Based on Individual Mobility Patterns: Challenges and Direction. IEEE ICDM Workshops. 2017
- H. Issa (2017). Spatio-textual trajectories: models and applications. PhD Thesis
- M.L. Damiani, H. Issa, G. Fotino, M. Heurich, F. Cagnacci (2016). Introducing 'presence' and 'stationarity index' to study partial migration patterns: an application of a spatio-temporal clustering technique. IJGIS, International Journal of Geographical Information Science, Vol. 30, N. 5, pp.907–928
- M.L. Damiani, H. Issa, G. Fotino, F. Hachem, N. Ranc, F. Cagnacci (2015). MigrO: a plug–in for the analysis of individual mobility behavior based on the stay region model. ACM SIGSPATIAL'15. Best demo award
- M.L. Damiani, H. Issa, F. Cagnacci (2014). Extracting stay regions with uncertain boundaries from GPS Trajectories: a case study in animal ecology. ACM SIGSPATIAL ’14.