Visual Analytics for Understanding Spatial Situations from Episodic Movement Data
Continuing advances in modern data acquisition techniques result in rapidly growing amounts of geo-referenced data about moving objects and in emergence of new data types. We define episodic movement data as a new complex data type to be considered in the research fields relevant to data analysis. In episodic movement data, position measurements may be separated by large time gaps, in which the positions of the moving objects are unknown and cannot be reliably reconstructed. Many of the existing methods for movement analysis are designed for data with fine temporal resolution and cannot be applied to discontinuous trajectories. We present an approach utilising Visual Analytics methods to explore and understand the temporal variation of spatial situations derived from episodic movement data by means of spatio-temporal aggregation. The situations are defined in terms of the presence of moving objects in different places and in terms of flows (collective movements) between the places. The approach, which combines interactive visual displays with clustering of the spatial situations, is presented by example of a real dataset collected by Bluetooth sensors.
- 5.Boyandin I, Bertini E, Lalanne D (2010) Visualizing the world’s refugee data with JFlowMap. In: Poster abstracts at Eurographics/IEEE-VGTC symposium on visualisation Google Scholar
- 6.Bruno R, Delmastro F (2003) Design and analysis of a bluetooth-based indoor localisation system. In: Proc personal wireless communications (PWC), IFIP-TC6 8th international conference, pp 711–725 Google Scholar
- 8.Jankowski P, Andrienko N, Andrienko G, Kisilevich S (2010) Discovering landmark preferences and movement patterns from photo postings. In: Transaction in GIS, 2010, vol 46, pp 833–852 Google Scholar
- 9.Keim D, Andrienko G, Fekete J-D, Görg C, Kohlhammer J, Melançon G (2008) Visual analytics: definition, process, and challenges. In: Kerren A, Stasko JT, Fekete J-D, North C (eds) Information visualisation—human-centered issues and perspectives. Lecture notes in computer science, vol 4950. Springer, Berlin, pp 154–175 Google Scholar
- 10.Kraak M-J, Ormeling F (2003) Cartography: visualisation of spatial data, 2nd edn. Pearson Education, Harlow Google Scholar
- 13.Stange H, Liebig T, Hecker D, Andrienko G, Andrienko N (2011) Analytical workflow of monitoring human mobility in big event settings using bluetooth. In: Third international workshop on indoor spatial awareness (ISA 2011), 1 November, 2011, Chicago, USA Google Scholar