Self-Organizing Maps
Towards a taxonomy of movement patterns
Information Visualization
Visual cluster analysis of trajectory data with interactive Kohonen maps
Information Visualization
Space-time density of trajectories: exploring spatio-temporal patterns in movement data
International Journal of Geographical Information Science - Geospatial Visual Analytics: Focus on Time Special Issue of the ICA Commission on GeoVisualization
Journal of Location Based Services - GeoVA(t) - Geospatial visual analytics: focus on time. Special issue of the ICA Commission on GeoVisualisation
A conceptual framework and taxonomy of techniques for analyzing movement
Journal of Visual Languages and Computing
An alternative map of the United States based on an n-dimensional model of geographic space
Journal of Visual Languages and Computing
A Tale of One City: Using Cellular Network Data for Urban Planning
IEEE Pervasive Computing
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Mining large-scale smartphone data for personality studies
Personal and Ubiquitous Computing
A review of quantitative methods for movement data
International Journal of Geographical Information Science
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A series of maps were produced that together form a type of atlas of the Nokia Mobile Data Challenge (MDC). Like in a traditional geographic atlas, a limited number of base map configurations is generated, onto which various thematic elements are then overlaid. Two of those base maps are themselves derived from MDC data; the third is referenced in geographic space. Thematic overlays serve several purposes, including elaborating different elements from which the base map geometry had been derived, as well as linking other data to it. The core of the study presented here is an intersection of high-dimensional concepts, dimensionality reduction, geographic analysis, and visualization, intended as a point of departure towards an integrated, attribute-centered understanding of people's movement patterns. Among the advances put forth is a new time-weighted kernel density model approach derived from journey vertices captured via GPS and WLAN.