1,429
Views
2
CrossRef citations to date
0
Altmetric
Articles

Motion of animated streamlets appears to surpass their graphical alterations in human visual detection of vector field maxima

ORCID Icon & ORCID Icon
Pages 489-501 | Received 21 May 2018, Accepted 25 Nov 2018, Published online: 10 Jan 2019

References

  • Anderson, M. J. (2001). A new method for non-parametric multivariate analysis of variance. Austral Ecology, 26(1), 32–46. doi:10.1111/j.1442-9993.2001.01070.pp.x
  • Bertin, J. (1967). Sémiologie graphique: Les diagrammes, les réseaux, les cartes. Paris: Mouton.
  • Boyandin, I., Bertini, E., & Lalanne, D. (2012). A qualitative study on the exploration of temporal changes in flow maps with animation and small-multiples. Computer Graphics Forum, 31, 1005–1014. doi:10.1111/cgf.2012.31.issue-3pt2
  • Campbell, C. S., & Egbert, S. L. (1990). Animated cartography: Thirty years of scratching the surface. Cartographica, 27(2), 24–46. doi:10.3138/V321-5367-W742-1587
  • Castronovo, D. A., Chui, K. K., & Naumova, E. N. (2009). Dynamic maps: A visual-analytic methodology for exploring spatio-temporal disease patterns. Environmental Health, 8(1), 61. doi:10.1186/1476-069X-8-61
  • Cinnamon, J., Rinner, C., Cusimano, M. D., Marshall, S., Bekele, T., Hernandez, T., … Chipman, M. L. (2009). Evaluating web-based static, animated and interactive maps for injury prevention. Geospatial Health, 4(1), 3–16. doi:10.4081/gh.2009.206
  • DiBiase, D., MacEachren, A. M., Krygier, J. B., & Reeves, C. (1992). Animation and the role of map design in scientific visualization. Cartography and Geographic Information Systems, 19(4), 201–214. doi:10.1559/152304092783721295
  • Dorling, D. (1992). Stretching space and splicing time: From cartographic animation to interactive visualization. Cartography and Geographic Information Systems, 19(4), 215–227. doi:10.1559/152304092783721259
  • Dreher, J.-C., Koechlin, E., Ali, S. O., & Grafman, J. (2002). The roles of timing and task order during task switching. NeuroImage, 17(1), 95–109. doi:10.1006/nimg.2002.1169
  • Fabrikant, S. I., Rebich-Hespanha, S., Andrienko, N., Andrienko, G., & Montello, D. R. (2008). Novel method to measure inference affordance in static small-multiple map displays representing dynamic processes. Cartographic Journal, 45(3), 201–215. doi:10.1179/000870408X311396
  • Ferreira, N., Poco, J., Vo, H. T., Freire, J., & Silva, C. T. (2013). Visual exploration of big spatio-temporal urban data: A study of New York City taxi trips. IEEE Transactions on Visualization and Computer Graphics, 19(12), 2149–2158. doi:10.1109/TVCG.2013.226
  • Ganguli, M., Snitz, B. E., Lee, C.-W., Vanderbilt, J., Saxton, J. A., & Chang, -C.-C. H. (2010). Age and education effects and norms on a cognitive test battery from a population-based cohort: The Monongahela-Youghiogheny healthy aging team. Aging & Mental Health, 14(1), 100–107. doi:10.1080/13607860903071014
  • Griffin, A. L., MacEachren, A. M., Hardisty, F., Steiner, E., & Li, B. (2006). A comparison of animated maps with static small-multiple maps for visually identifying space-time clusters. Annals of the Association of American Geographers, 96(4), 740–753. doi:10.1111/j.1467-8306.2006.00514.x
  • Halpern, D. F., & Collaer, M. L. (2005). More than meets the eye. In P. Shah, & A. Miyake (Eds.), The Cambridge handbook of visuospatial thinking (pp. 170). New York: Cambridge University Press.
  • Harrower, M. (2007). The cognitive limits of animated maps. Cartographica: the International Journal for Geographic Information and Geovisualization, 42(4), 349–357. doi:10.3138/carto.42.4.349
  • Harrower, M., & Fabrikant, S. (2008). The role of map animation for geographic visualization. In M. Dodge, M. McDerby, & M. Turner (Eds.), Geographic Visualization: Concepts, Tools and Applications, (pp. 49–65). Chichester, UK: Wiley.
  • Imhof, E. (1965). Kartographische gelndedarstellung. Berlin: Walter De Gruyter.
  • Jenny, B., Liem, J., Avri, B., & Putman, W. M. (2016). Interactive video maps: A year in the life of earth’s CO2. Journal of Maps, 12(sup1), 36–42. doi:10.1080/17445647.2016.1157323
  • Jobard, B., Ray, N., & Sokolov, D. (2012). Visualizing 2D flows with animated arrow plots. arXiv preprint arXiv:1205.5204.
  • Keim, D., Andrienko, G., Fekete, J.-D., Görg, C., Kohlhammer, J., & Melançon, G. (2008). Visual analytics: Definition, process, and challenges. In A. Kerren, J. T. Stasko, J.-D. Fekete, & C. North (Eds.), Information visualization: Human-centered issues and perspectives (pp. 154–175). Berlin: Springer. doi:10.1007/978-3-540-70956-5_7
  • Koussoulakou, A., & Kraak, M. (1992). Spatia-temporal maps and cartographic communication. Cartographic Journal, 29(2), 101–108. doi:10.1179/000870492787859745
  • Lowe, R. K. (2003). Animation and learning: Selective processing of information in dynamic graphics. Learning and Instruction, 13(2), 157–176. doi:10.1016/S0959-4752(02)00018-X
  • Lowe, R. K. (2004). Interrogation of a dynamic visualization during learning. Learning and Instruction, 14(3), 257–274. doi:10.1016/j.learninstruc.2004.06.003
  • MacEachren, A. M. (1995). How maps work. representation, visualization, and design. New York: Guilford Press.
  • Maciejewski, R., Rudolph, S., Hafen, R., Abusalah, A., Yakout, M., Ouzzani, M., … Ebert, D. S. (2010). A visual analytics approach to understanding spatiotemporal hotspots. IEEE Transactions on Visualization and Computer Graphics, 16(2), 205–220. doi:10.1109/TVCG.2009.100
  • Maggi, S., Fabrikant, S. I., Imbert, J.-P., & Hurter, C. (2016). How do display design and user characteristics matter in animations? An empirical study with air traffic control displays. Cartographica: the International Journal for Geographic Information and Geovisualization, 51(1), 25–37. doi:10.3138/cart.51.1.3176
  • Mayer, A. R., Dorflinger, J. M., Rao, S. M., & Seidenberg, M. (2004). Neural networks underlying endogenous and exogenous visualspatial orienting. NeuroImage, 23(2), 534–541. doi:10.1016/j.neuroimage.2004.06.027
  • Mayer, R. E. (2002). Multimedia learning. Psychology of Learning and Motivation, 41, 85–139.
  • Nossum, A. S. (2014). Exploring eye movement patterns on cartographic animations using projections of a space-time-cube. Cartographic Journal, 51(3), 249–256. doi:10.1179/1743277412Y.0000000031
  • Peterson, M. P. (1996). Between reality and abstraction: Non-temporal applications of cartographic animation. Retrieved from http://maps.unomaha.edu/AnimArt/article.html
  • Pyysalo, U., & Oksanen, J. (2013). Outlier highlighting for spatio-temporal data visualization. Cartography and Geographic Information Science, 40(3), 165–171. doi:10.1080/15230406.2013.803706
  • QGIS Development Team. (2018). QGIS geographic information system. Open source geospatial foundation project. Retrieved from http://qgis.osgeo.org
  • R Core Team. (2018). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Retrieved from http://www.r-project.org
  • Resch, B., Hillen, F., Reimer, A., & Spitzer, W. (2013). Towards 4D cartography: Four-dimensional dynamic maps for understanding spatio-temporal correlations in lightning events. Cartographic Journal, 50(3), 266–275. doi:10.1179/1743277413Y.0000000062
  • Saint-Marc, C., Villanova-Oliver, M., Davoine, P.-A., Capoccioni, C. P., & Chenier, D. (2017). User testing of dynamic geovisualizations: Lessons learned and possible improvements for cartographic experiments. International Journal of Cartography, 3(1), 88–101. doi:10.1080/23729333.2017.1301347
  • Shipley, T. F., Fabrikant, S. I., & Lautenschütz, A.-K. (2013). Creating perceptually salient animated displays of spatiotemporal coordination in events. In M. Raubal, D. M. Mark, & A. U. Frank (Eds.), Cognitive and linguistic aspects of geographic space: New perspectives on geographic information research (pp. 259–270). Berlin: Springer. doi:10.1007/978-3-642-34359-9_14
  • Slocum, T., Sluter, R., Kessler, F., & Yoder, S. (2004). A qualitative evaluation of maptime, a program for exploring spatiotemporal point data. Cartographica: the International Journal for Geographic Information and Geovisualization, 39(3), 43–68. doi:10.3138/92T3-T928-8105-88X7
  • Teufert, J. F. (2004). Development and implementation of a NATO-wide state-of-the-art interim geospatial intelligence support tool. In E. M. Carabezza, (Ed.) Sensors, and command, control, communications, and intelligence (C3I) technologies for homeland security and homeland defense III (Vol 5403, pp. 734–746). Bellingham, WA: SPIE. doi: 10.1117/12.542311
  • Thomas, J. J., & Cook, K. A. (2006). A visual analytics agenda. Computer Graphics and Applications, IEEE, 26(1), 10–13. doi:10.1109/MCG.2006.5
  • Viégas, F., & Wattenberg, M. (2012). Wind map. Retrieved from http://hint.fm/projects/wind/
  • von Bastian, C. C., Locher, A., & Ruflin, M. (2013). Tatool: A Java-based open-source programming framework for psychological studies. Behavior Research Methods, 45(1), 108–115. doi:10.3758/s13428-012-0224-y
  • Ware, C., Bolan, D., Miller, R., Rogers, D. H., & Ahrens, J. P. (2016). Animated versus static views of steady flow patterns. In E. Jain & S. Joerg (Eds.), Proceedings of the ACM Symposium on Applied Perception SAP ’16 (pp. 77–84). New York: ACM. doi:10.1145/2931002.2931012
  • Willems, N., Van de Wetering, H., & Van Wijk, J. J. (2009). Visualization of vessel movements. Computer Graphics Forum, 28(3), 959–966. doi:10.1111/cgf.2009.28.issue-3