580
Views
4
CrossRef citations to date
0
Altmetric
Research Article

Attribute trajectory analysis: a framework to analyse attribute changes using trajectory analysis techniques

ORCID Icon &
Pages 1043-1059 | Received 14 Jun 2017, Accepted 29 Jan 2018, Published online: 07 Feb 2018

References

  • Andersson, M., et al. 2008. Reporting leaders and followers among trajectories of moving point objects. GeoInformatica, 12 (4), 497–528. doi:10.1007/s10707-007-0037-9
  • Benkert, M., et al. 2008. Reporting flock patterns. Computational Geometry, 41 (3), 111–125. doi:10.1016/j.comgeo.2007.10.003
  • Buchin, K., et al., 2013. Trajectory grouping structure. In: F. Dehne, R. Solis-Oba, and J.-R. Sack, eds. Algorithms and data structures: 13th International Symposium, WADS 2013, London, ON, Canada, August 12-14, 2013. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 219–230.
  • Carvalho Júnior, O.A., et al. 2011. A new approach to change vector analysis using distance and similarity measures. Remote Sensing, 3 (11), 2473–2493. doi:10.3390/rs3112473
  • Chen, J., et al. 2003. Land-use/land-cover change detection using improved change-vector analysis. Photogrammetric Engineering & Remote Sensing, 69 (4), 369–379. doi:10.14358/PERS.69.4.369
  • Chen, J., et al. 2011. Change vector analysis in posterior probability space: a new method for land cover change detection. IEEE Geoscience and Remote Sensing Letters, 8 (2), 317–321. doi:10.1109/LGRS.2010.2068537
  • Chen, L., et al., 2005. Robust and fast similarity search for moving object trajectories. Proceedings of the 2005 ACM SIGMOD international conference on Management of data. Baltimore, Maryland: ACM, 491–502.
  • Chen, L. and Ng, R., 2004. On the marriage of Lp-norms and edit distance. Proceedings of the Thirtieth international conference on very large data bases - Volume 30. Toronto, Canada: VLDB Endowment, 792–803.
  • De Lucca Siqueira, F. and Bogorny, V., 2011. Discovering chasing behavior in moving object trajectories. Transactions in GIS, 15 (5), 667–688. doi:10.1111/tgis.2011.15.issue-5
  • Degaetano, A.T., 1996. Delineation of mesoscale climate zones in the Northeastern United States using a novel approach to cluster analysis. Journal of Climate, 9 (8), 1765–1782. doi:10.1175/1520-0442(1996)009<1765:DOMCZI>2.0.CO;2
  • Duan, H., et al., 2010. Vegetation change based on temporal trajectory analysis with multi-temporal CBERS/CCD data in the lower reaches of Tarim River. Arid Land Geography, 33 (2), 263–271.
  • Gronau, I. and Moran, S., 2007. Optimal implementations of UPGMA and other common clustering algorithms. Information Processing Letters, 104 (6), 205–210. doi:10.1016/j.ipl.2007.07.002
  • Hamilton, J.D., 1994. Time series analysis. Princeton, NJ: Princeton University Press.
  • Jeung, H., et al. 2008a. Discovery of convoys in trajectory databases. Proc. VLDB Endow., 1 (1), 1068–1080. doi:10.14778/1453856.1453971
  • Jeung, H., Shen, H.T., and Zhou, X, 2008b. Convoy queries in spatio-temporal databases. In: IEEE 24th International Conference on Data Engineering, 7-12 April 2008. Cancun, Mexico: IEEE, 1457–1459.
  • Kalnis, P., Mamoulis, N., and Bakiras, S., 2005. On discovering moving clusters in spatio-temporal data. In: C. Bauzer Medeiros, M.J. Egenhofer, and E. Bertino, eds. Advances in spatial and temporal databases: 9th international symposium, SSTD 2005, Angra dos Reis, Brazil, August 22-24, 2005. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 364–381.
  • Keogh, E.J. and Pazzani, M.J., 2000. Scaling up dynamic time warping for datamining applications. Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining. Boston, Massachusetts, USA: ACM, 285–289.
  • Kottek, M., et al. 2006. World Map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15 (3), 259–263. doi:10.1127/0941-2948/2006/0130
  • Laube, P., Imfeld, S., and Weibel, R., 2005a. Discovering relative motion patterns in groups of moving point objects. International Journal of Geographical Information Science, 19 (6), 639–668. doi:10.1080/13658810500105572
  • Laube, P., Van Kreveld, M., and Imfeld, S., 2005b. Finding REMO — detecting relative motion patterns in geospatial lifelines. Developments in Spatial Data Handling: 11th International Symposium on Spatial Data Handling. Berlin, Heidelberg: Springer Berlin Heidelberg, 201–215.
  • Liu, G., et al., 2012. Analysis of vegetation landscape pattern dynamics based on trajectory change detection: a case study of ecological water transportation in the lower reaches of Tarim River. Journal of Desert Research, 32 (5), 1472–1478.
  • Malila, W.A., 1980. Change vector analysis: an approach for detecting forest changes with Landsat. In: LARS symposia.
  • Mertens, B. and Lambin, E.F., 2000. Land-cover-change trajectories in Southern Cameroon. Annals of the Association of American Geographers, 90 (3), 467–494. doi:10.1111/0004-5608.00205
  • Ong, R., 2011. From pattern discovery to pattern interpretation of semantically-enriched trajectory data. Thesis (PhD). University of Pisa, Pisa.
  • Paterson, M. and Dančík, V., 1994. Longest common subsequences. In: I. Prívara, B. Rovan, and P. Ruzička, eds. Mathematical foundations of computer science 1994: 19th international symposium, MFCS’94 Košice, Slovakia, August 22–26, 1994 Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 127–142.
  • Raubal, M., 2004. Formalizing conceptual spaces. In: A.C. Varzi and L. Vieu, eds. Formal ontology in information systems, proceedings of the third international conference (FOIS 2004). Amsterdam: IOS Press, 153–164.
  • Raubal, M., et al., 2008. Representing concepts in time. In: C. Freksa, eds. Spatial cognition VI. Learning, reasoning, and talking about space: international conference spatial cognition 2008, Freiburg, Germany, September 15-19, 2008. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 328–343.
  • Singh, S., and Talwar, R., 2013. Review on different change vector analysis algorithms based change detection techniques. In: IEEE Second International Conference on Image Information Processing (ICIIP-2013), 9-11 December 2013. Shimla, India: IEEE, 136–141.
  • Skupin, A., 2007. Where do you want to go today [in attribute space]? In: H.J. Miller, ed. Societies and cities in the age of instant access. Dordrecht: Springer Netherlands, 133–149.
  • Skupin, A. and Hagelman, R., 2005. Visualizing demographic trajectories with self-organizing maps. GeoInformatica, 9 (2), 159–179. doi:10.1007/s10707-005-6670-2
  • Skupin, A., 2002. On geometry and transformation in map-like information visualization. In: K. Börner and C. Chen, eds. Visual interfaces to digital libraries. Berlin, Heidelberg: Springer Berlin Heidelberg, 161–170.
  • Toohey, K. and Duckham, M., 2015. Trajectory similarity measures. SIGSPATIAL Special, 7 (1), 43–50. doi:10.1145/2782759
  • Unal, Y., Kindap, T., and Karaca, M., 2003. Redefining the climate zones of Turkey using cluster analysis. International Journal of Climatology, 23 (9), 1045–1055. doi:10.1002/(ISSN)1097-0088
  • Wachowicz, M., et al. 2011. Finding moving flock patterns among pedestrians through collective coherence. International Journal of Geographical Information Science, 25 (11), 1849–1864. doi:10.1080/13658816.2011.561209
  • Wang, D., et al. 2012. Spatio-temporal pattern analysis of land use/cover change trajectories in Xihe watershed. International Journal of Applied Earth Observation and Geoinformation, 14 (1), 12–21. doi:10.1016/j.jag.2011.08.007
  • Warren Liao, T., 2005. Clustering of time series data—a survey. Pattern Recognition, 38 (11), 1857–1874. doi:10.1016/j.patcog.2005.01.025
  • WMO. 2010. World meteorological organization standard normals [online]. United Nations statistics division. Available from: http://data.un.org/Explorer.aspx?d=CLINO [Accessed 26 Oct 2016].
  • Zhang, X. and Yan, X., 2014. Spatiotemporal change in geographical distribution of global climate types in the context of climate warming. Climate Dynamics, 43 (3), 595–605. doi:10.1007/s00382-013-2019-y
  • Zhang, Y.H. and Liu, H.P., 2016. Trajectory-based analysis of urban land-cover change detection. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B7, 607–610. doi:10.5194/isprsarchives-XLI-B7-607-2016
  • Zhou, Q., Li, B., and Kurban, A., 2008a. Spatial pattern analysis of land cover change trajectories in Tarim Basin, northwest China. International Journal of Remote Sensing, 29 (19), 5495–5509. doi:10.1080/01431160802060938
  • Zhou, Q., Li, B., and Kurban, A., 2008b. Trajectory analysis of land cover change in arid environment of China. International Journal of Remote Sensing, 29 (4), 1093–1107. doi:10.1080/01431160701355256

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.