• Patrick LaubeEmail author
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)


This book has a thesis, it makes the case for Computational Movement Analysis (CMA), as an interdisciplinary umbrella for contributions from a wide range of fields aiming for a better understanding of movement processes. This first chapter explains why this inclusive umbrella is a contribution, what it involves, and which fields it borrows methods and concepts from.


Movement Data Movement Trace Movement Ecology Geographic Information Science Move Object Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Anselin, L. (1990). What is special about spatial data? In D. A. Griffith (Ed.), Statistics, past, present, and future, monograph Series (pp. 63–77). Ann Arbor, MI: Institute of Mathematical Geography.Google Scholar
  2. Claussen, D. L., Finkler, M. S., & Smith, M. M. (1997). Thread trailing of turtles: Methods for evaluating spatial movements and pathway structure. Canadian Journal of Zoology-Revue Canadienne De Zoologie, 75(12), 2120–2128.CrossRefGoogle Scholar
  3. Frank, A. U. (1998). Different types of times in GIS. In M. J. Egenhofer & R. G. Colledge (Eds.), Spatial and temporal reasoning in geographic information systems (pp. 40–62). Oxford, UK: Oxford University Press.Google Scholar
  4. Frank, A. U. (2001). Socio-economic units: Their life and motion. In A. U. Frank, J. Raper, & J. P. Cheylan (Eds.), Life and motion of socio-economic units (Vol. 8, pp. 21–34)., GISDATA London, UK: Taylor & Francis.Google Scholar
  5. Galton, A. (2005). Dynamic collectives and their collective dynamics. In A. Cohn & D. M. Mark (Eds.), Spatial information theory, proceedings (Vol. 3693, pp. 300–315)., Lecture Notes in Computer Science Berlin: Springer.CrossRefGoogle Scholar
  6. Goodchild, M. F. (1992). Geographical information science. International Journal of Geographical Information Systems, 6(1), 31–45.CrossRefGoogle Scholar
  7. Goodchild, M. F. (2001). A geographer looks at spatial information theory. Spatial information theory (Vol. 2205, pp. 1–13)., Lecture Notes in Computer Science Berlin: Springer.CrossRefGoogle Scholar
  8. Gudmundsson, J., Laube, P., & Wolle, T. (2012). Computational movement analysis. In W. Kresse & D. M. Danko (Eds.), Springer handbook of geographic information (pp. 423–438). Berlin: Springer.Google Scholar
  9. Holyoak, M., Casagrandi, R., Nathan, R., Revilla, E., & Spiegel, O. (2008). Trends and missing parts in the study of movement ecology. Proceedings of the National Academy of Sciences, 105(49), 19060–19065.CrossRefGoogle Scholar
  10. Miller, H., & Han, J. (Eds.). (2009). Geographic data mining and knowledge discovery (2nd ed.). Boca Raton, FL: CRC Press.Google Scholar
  11. Shamoun-Baranes, J., van Loon, E. E., Purves, R. S., Speckmann, B., Weiskopf, D., & Camphuysen, C. J. (2012). Analysis and visualization of animal movement. Biology Letters, 8(1), 6–9.CrossRefGoogle Scholar
  12. Walker, M. M. (1998). On a wing and a vector: A model for magnetic navigation by homing pigeons. Journal of Theoretical Biology, 192(3), 341–349.CrossRefGoogle Scholar
  13. Worboys, M., & Duckham, M. (2004). GIS—A computing perspective (2nd ed.). New York: CRC Press.Google Scholar

Copyright information

© The Author(s) 2014

Authors and Affiliations

  1. 1.Institute of Natural Resource SciencesZurich University of Applied SciencesWädenswilSwitzerland

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