How does your viewing perspective matter for decision-making with flood risk maps?*

References

• Abbott, E. A. (1884/1992). Flatland: A romance of many dimensions. (Dover Thrift ed.). Dover Publications Inc.
   Google Scholar
• Amirebrahimi, S., Rajabifard, A., Mendis, P., & Ngo, T. (2016, May 2–6). A planning decision support tool for assessment and 3D visualisation of flood risk to buildings. In International Federation of Surveyors (FIG) Working Week 2016: Recover from Disaster, Proceedings, Christchurch, New Zealand. International Federation of Surveyors (FIG).
   Google Scholar
• Bertin, J. (1967). Sémiologie graphique. Les diagrammes, les réseaux, les cartes. La Haye, Mouton, Gauthier-Villars.
   Google Scholar
• Charrière, M. K. M., Junier, S. J., Mostert, E., & Bogaard, T. A. (2012, November 20–22). Flood risk communication—Visualization tools and evaluation of effectiveness. In Comprehensive Flood Risk Management: Research for Policy and Practice, Proceedings, Comprehensive Flood Risk Management FLOODrisk 2012: The 2nd European conference on FLOODrisk management science, policy and practice: Closing the gap (pp. 367–368). CRC Press.
   Google Scholar
• Cope, M. (2016). Organizing and analyzing qualitative data. In I. Hay (Ed.), Qualitative research methods in human geography (pp. 373–392). Oxford University Press.
   Google Scholar
• De Moel, H., van Alphen, J., & Aerts, J. C. J. H. (2009). Flood maps in Europe – methods, availability and use. Natural Hazards and Earth System Sciences, 9(2), 289–301. https://doi.org/10.5194/nhess-9-289-2009
   Web of Science ®Google Scholar
• Duebel, S., Roehlig, M., Schumann, H., & Trapp, M. (2014). 2D and 3D presentation of spatial data: A systematic review. In 2014 IEEE VIS International Workshop on, (3DVis), (pp. 11–18). IEEE. https://doi.org/10.1109/3DVis.2014.7160094
   Google Scholar
• Evans, S. Y., Todd, M., Baines, I., Hunt, T., & Morrison, G. (2014). Communicating flood risk through three-dimensional visualisation. Proceedings of the Institution of Civil Engineers - Civil Engineering, 167(5), 48–55. https://doi.org/10.1680/cien.13.00020
   Web of Science ®Google Scholar
• Fabrikant, S. I., Maggi, S., & Montello, D. R. (2014). 3D network spatialization: Does it add depth to 2D representations of semantic proximity? LNISA, 8728, 34–47. https://doi.org/10.1007/978-3-319-11593-1_3
   Google Scholar
• Franz, M., Scholz, M., & Hinz, O. (2015). 2D versus 3D visualizations in decision support – The impact of decision makers’ perceptions. In International Conference on Information Systems 2015. Association for Information Systems (AIS).
   Google Scholar
• Friendly, M. (2008). A brief history of data visualization. In Handbook of data visualization (pp. 15–56). Springer. https://doi.org/10.1007/978-3-540-33037-0_2
   Google Scholar
• Hagemeier-Klose, M., & Wagner, K. (2009). Evaluation of flood hazard maps in print and web mapping services as information tools in flood risk communication. Natural Hazards and Earth System Sciences, 9(2), 563–574. https://doi.org/10.5194/nhess-9-563-2009
   Web of Science ®Google Scholar
• Haynes, K., Barclay, J., & Pidgeon, N. (2007). Volcanic hazard communication using maps: An evaluation of their effectiveness. Bulletin of Volcanology, 70(2), 123–138. https://doi.org/10.1007/s00445-007-0124-7
   Web of Science ®Google Scholar
• Hegarty, M., Smallman, H. S., Stull, A. T., & Canham, M. S. (2009). Naïve cartography: How intuitions about display configuration can hurt performance. Cartographica: The International Journal for Geographic Information and Geovisualization, 44(3), 171–186. https://doi.org/10.3138/carto.44.3.171
   Google Scholar
• Holt, C. A., & Laury, S. K. (2002). Risk aversion and incentive effects. American Economic Review, 92(5), 1644–1655. https://doi.org/10.1257/000282802762024700
   Web of Science ®Google Scholar
• Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society, 47(2), 263–291. https://doi.org/10.2307/1914185
   Web of Science ®Google Scholar
• Kellens, W., Zaalberg, R., Neutens, T., Vanneuville, W., & De Maeyer, P. (2011). An analysis of the public perception of flood risk on the Belgian coast. Risk Analysis, 31(7), 1055–1068. https://doi.org/10.1111/j.1539-6924.2010.01571.x
   PubMed Web of Science ®Google Scholar
• Kemec, S., Zlatanova, S., & Duzgun, H. S. (2010). A framework for defining a 3D model in support of risk management. Geographic Information and Cartography for Risk and Crisis Management, 199539, 69–82. https://doi.org/10.1007/978-3-642-03442-8_5
   Google Scholar
• Korporaal, M., Ruginski, I. T., & Fabrikant, S. I. (2020). Effects of uncertainty visualization on map-based decision making under time pressure. Frontiers in Computer Science, 2. https://doi.org/10.3389/fcomp.2020.00032
   PubMed Web of Science ®Google Scholar
• Kübler, I., Richter, K.-F., & Fabrikant, S. I. (2019). Against all odds: Multicriteria decision making with hazard prediction maps depicting uncertainty. Annals of the American Association of Geographers, 110(3), 661–683. https://doi.org/10.1080/24694452.2019.1644992
   Web of Science ®Google Scholar
• Lejuez, C. W., Richards, J. B., Read, J. P., Kahler, C. W., Ramsey, S. E., Stuart, G. L., Strong, D. R., & Brown, R. A. (2002). Evaluation of a behavioral measure of risk taking: The balloon analogue risk task (BART). Journal of Experimental Psychology: Applied, 8(2), 75–84. https://doi.org/10.1037/1076-898X.8.2.75
   PubMed Web of Science ®Google Scholar
• Leskens, J. G., Kehl, C., Tutenel, T., Kol, T., de Haan, G., Stelling, G., & Eisemann, E. (2017). An interactive simulation and visualization tool for flood analysis usable for practitioners. Mitigation and Adaptation Strategies for Global Change, 22(2), 307–324. https://doi.org/10.1007/s11027-015-9651-2
   PubMed Web of Science ®Google Scholar
• Lieske, D. J., Wade, T., & Roness, L. A. (2014). Climate change awareness and strategies for communicating the risk of coastal flooding: A Canadian maritime case example. Estuarine, Coastal and Shelf Science, 140, 83–94. https://doi.org/10.1016/j.ecss.2013.04.017
   Web of Science ®Google Scholar
• Macchione, F., Costabile, P., Costanzo, C., & De Santis, R. (2019). Moving to 3-D flood hazard maps for enhancing risk communication. Environmental Modelling and Software, 111, 510–522. https://doi.org/10.1016/j.envsoft.2018.11.005
   Web of Science ®Google Scholar
• Nahm, F. S. (2016). Nonparametric statistical tests for the continuous data: The basic concept and the practical use. Korean Journal of Anesthesiology, 69(1), 8–14. https://doi.org/10.4097/kjae.2016.69.1.8
   PubMed Web of Science ®Google Scholar
• Oberg, A. L., & Mahoney, D. W. (2007). Linear mixed effects models. In W. T. Ambrosius (Ed.), Topics in biostatistics. Methods in molecular biology (pp. 213–234). https://doi.org/10.1007/978-1-59745-530-5_11
   Google Scholar
• Oliva, A. (2005). Gist of the scene (chapter 41). In L. Itti, G. Rees, & J. K. Tsotsos (Eds.), Neurobiology of attention (pp. 251–256). Academic Press. https://doi.org/10.1016/B978-012375731-9/50045-8
   Google Scholar
• Popelka, S., & Brychtova, A. (2013). Eye-tracking study on different perception of 2D and 3D terrain visualisation. The Cartographic Journal, 50(3), 240–246. https://doi.org/10.1179/1743277413Y.0000000058
   Web of Science ®Google Scholar
• Robinson, A. H. (1952). The look of maps. An examination of cartographic design. University of Wisconsin Press.
   Google Scholar
• Rollason, E., Bracken, L. J., Hardy, R. J., & Large, A. R. G. (2018). Rethinking flood risk communication. Natural Hazards, 92(3), 1665–1686. https://doi.org/10.1007/s11069-018-3273-4
   Web of Science ®Google Scholar
• Roth, R. E. (2009). The impact of user expertise on geographic risk assessment under uncertain conditions. Cartography and Geographic Information Science, 36(1), 29–43. https://doi.org/10.1559/152304009787340160
   Web of Science ®Google Scholar
• Roth, R. E., Quinn, C., & Hart, D. (2015). The competitive analysis method for evaluating water level visualization tools. In J. Brus, A. Vondrakova, & V. Vozenilek (Eds.), Modern trends in cartography. Lecture notes in geoinformation and cartography. Springer. https://doi.org/10.1007/978-3-319-07926-4_19
   Google Scholar
• Ruginski, I., Creem-Regehr, S. H., Stefanucci, J. K., & Cashdan, E. (2019). GPS use negatively affects environmental learning through spatial transformation abilities. Journal of Environmental Psychology, 64, 12–20. https://doi.org/10.1016/j.jenvp.2019.05.001
   Web of Science ®Google Scholar
• Savage, D. M., Wiebe, E. N., & Devine, H. A. (2004). Performance of 2D versus 3D topographic representations for different task types. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 48(16), 1793–1797. https://doi.org/10.1177/154193120404801601
   Google Scholar
• Schobesberger, D., & Patterson, T. (2008, February 11–15). Evaluating the effectiveness of 2D vs. 3D trailhead maps a map user study conducted at Zion National Park, United States. In Proceedings of the 6th ICA Mountain Cartography Workshop (pp. 201–205). International Cartographic Association (ICA).
   Google Scholar
• Seipel, S., & Lim, N. J. (2017). Color map design for visualization in flood risk assessment. International Journal of Geographical Information Science, 31(11), 2286–2309. https://doi.org/10.1080/13658816.2017.1349318
   Web of Science ®Google Scholar
• Shepherd, I. D. H. (2008). Travails in the third dimension: A critical evaluation of 3D geographical visualization. In M. Dodge, M. McDerby, & M. Turner (Eds.), Geographic visualization: Concepts, tools and applications (pp. 199–222). Wiley.
   Google Scholar
• Shneiderman, B. (1996). The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings IEEE Symposium on Visual Languages (pp. 336–343). https://doi.org/10.1109/VL.1996.545307
   Google Scholar
• Simpson, M., Padilla, L., Keller, K., & Klippel, A. (2022). Immersive storm surge flooding: Scale and risk perception in virtual reality. Journal of Environmental Psychology, 80, 101764. https://doi.org/10.1016/j.jenvp.2022.101764
   Web of Science ®Google Scholar
• St. John, M., Cowen, M. B., Smallman, H. S., & Oonk, H. M. (2001). The use of 2D and 3D displays for shape-understanding versus relative-position tasks. Human Factors, 43(1), 79–98. https://doi.org/10.1518/001872001775992534
   PubMed Web of Science ®Google Scholar
• St. John, M., Smallman, H. S., & Cowen, M. B. (2000). Designing for the task: Sometimes 2-D is just plane better. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 44(21), 3-407–3–410. https://doi.org/10.1177/154193120004402108
   Google Scholar
• Tversky, B., Morrison, J. B., & Betrancourt, M. (2002). Animation: Can it facilitate? International Journal of Human-Computer Studies, 57(4), 247–262. https://doi.org/10.1006/ijhc.2002.1017
   Web of Science ®Google Scholar
• van Ackere, S., Glas, H., Beullens, J., Deruyter, G., De Wulf, A., & De Maeyer, P. (2016). Development of a 3D dynamic flood WEB GIS visualisation tool. International Journal of Safety and Security Engineering, 6(3), 560–569. https://doi.org/10.2495/SAFE-V6-N3-560-569
   Google Scholar
• Ware, C. (2022). Visual thinking for information design (2nd ed.). Elsevier.
   Google Scholar
• Ware, C., & Plumlee, M. (2005). 3D geovisualization and the structure of visual space (chapter 29). In J. Dykes, A. M. MacEachren, & M.-J. Kraak (Eds.), International cartographic association, exploring geovisualization (pp. 567–576). Elsevier. https://doi.org/10.1016/B978-008044531-1/50447-4
   Google Scholar
• Wilkening, J., & Fabrikant, S. I. (2011). How do decision time and realism affect map-based decision making? In M. Egenhofer, N. Giudice, R. Moratz, & M. Worboys (Eds.), Spatial information theory. COSIT 2011. Lecture notes in computer science (Vol. 6899, pp. 1–19). Springer. https://doi.org/10.1007/978-3-642-23196-4_1
   Google Scholar
• Wilkening, J., & Fabrikant, S. I. (2013). How users interact with a 3D geo-browser under time pressure. Cartography and Geographic Information Science, 40(1), 40–52. https://doi.org/10.1080/15230406.2013.762140
   Web of Science ®Google Scholar
• Zhang, N., Yasunari, T., & Ohta, T. (2011). Dynamics of the larch taiga–permafrost coupled system in Siberia under climate change. Environmental Research Letters, 6(2), 024003. https://doi.org/10.1088/1748-9326/6/2/024003
   Web of Science ®Google Scholar