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Evaluating the perceived visual complexity of multidirectional hill-shading

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Języki publikacji
EN
Abstrakty
EN
Eye tracking recordings could reveal the visual behavior for different cartographic visualization techniques, such as hill-shading, while at the same time eye tracking metrics (ETMs) can summarize the associated complexity levels in a concise and quantitative manner. In the present study, three different hill-shading methods, including:(i) the standard method based on ideal diffuse reflection, (ii) the Multidirectional ObliqueWeighted method – MDOW and (iii) the combination of a MDOW’s variation with standard hill-shading, are evaluated and ranked in terms of their perceived visual complexity. The performed examination is based on both eye tracking techniques and expert judgement procedures. A weighted combination of basic ETMs has been used, implemented by the Landscape Rating Index – LRI. The weights resulted from an experts’ judgement process where the opinions of experts in geoinformatics, cartography, geovisualization, experimental psychology, cognitive science, neuroscience and eye tracking were analyzed. Fifteen (15) individuals participated in an eye tracking experiment with hill-shading images produced by the three methods under evaluation, while 41 experts participated in an online questionnaire in order to collect all the analysis data. The final evaluation was based on the computation of three LRI models. The outcomes indicate that implementing hill-shading with more than one light sources results in similar perceptual behaviors, allowing for a seamless exploitation of the advantages of using multidirectional illumination.
Rocznik
Strony
161--172
Opis fizyczny
Bibliogr. 22 poz., rys., tab., wykr.
Twórcy
  • National Technical University of Athens, School of Rural and Surveying Engineering, Athens, Greece
  • National Technical University of Athens, School of Rural and Surveying Engineering, Athens, Greece
  • KTH Royal Institute of Technology, School of Architecture and Built Environment, Stocholm, Sweden
  • University of West Attica, Department of Surveying and Geoinformatics Engineering, Athens, Greece
  • National Technical University of Athens, School of Rural and Surveying Engineering, Athens, Greece
  • University of West Attica, Department of Surveying and Geoinformatics Engineering, Athens, Greece
autor
  • National Technical University of Athens, School of Rural and Surveying Engineering, Athens, Greece
Bibliografia
  • [1] Bezdek, J.C. (1981). Pattern Recognition with Fuzzy Objective Function Algoritms. New York, USA: Plenum Press.
  • [2] Castner, H.W. and Eastman, R.J. (1984). Eye-movement parameters and perceived map complexity – I. The American Cartographer, 11(2), 107–117. DOI: 10.1559/152304084783914768.
  • [3] Farmakis-Serebryakova, M. and Hurni, L. (2020). Comparison of Relief Shading Techniques Applied to Landforms. ISPRS Int. J. Geo-Inf., 9(3), 253. DOI: 10.3390/ijgi9040253.
  • [4] Horn, B.K.P. (1981). Hill-shading and the reflectance map. Proc. IEEE, 69(1), 14–47. DOI: 10.1109/PROC.1981.11918.
  • [5] Imhof, E. (1982). Cartographic Relief Presentation. Berlin, Germany: Walter de Gruyter.
  • [6] Kaplan, R. and Kaplan, S. (1989). The experience of nature: A psychological perspective. Cambridge, UK: Cambridge University Press.
  • [7] Kennelly, P.J. and Stewart, A.J. (2006). A uniform sky illumination model to enhance shading of terrain and urban areas. CaGIS, 33, 21–36. DOI: 10.1559/152304006777323118.
  • [8] Kennelly, P.J. and Stewart, A.J. (2014). General sky models for illuminating terrains. Int. J. Geogr. Inf. Sci., 28, 383–406. DOI: 10.1080/13658816.2013.848985.
  • [9] Kiefer, P., Giannopoulos, I., Raubal, M. and Duchowski, A. (2017). Eye tracking for spatial research: Cognition, computation, challenges. Spat. Cogn. Comput., 17(1–2), 1–19. DOI: 10.1080/13875868.2016.1254634.
  • [10] Krassanakis, V. and Cybulski, P. (2019). A review on eye movement analysis in map reading process: The status of the last decade. Geodesy Cartogr., 68(1), 191–209. DOI: 10.24425/gac.2019.126088.
  • [11] Krassanakis, V., Filippakopoulou, V. and Nakos, B. (2014). EyeMMV toolbox: An eye movement post-analysis tool based on a two-step spatial dispersion threshold for fixation identification. J. Eye Mov.Res., 7(1). DOI: 10.16910/jemr.7.1.1.
  • [12] Krassanakis, V., Filippakopoulou, V. and Nakos, B. (2016). Detection of moving point symbols on cartographic backgrounds. J. Eye Mov. Res., 7(1). DOI: 10.16910/jemr.9.2.2.
  • [13] Krassanakis, V., Misthos, L.M. and Menegaki, M. (2018). LandRate toolbox: An adaptable tool for eye movement analysis and landscape rating. In Eye Tracking for Spatial Research: 3rd International Workshop, 14 January 2018 (pp. 40–45). Zurich, Switzerland: ETH Zurich Research Collection.
  • [14] Kuper, R. (2017). Evaluations of landscape preference, complexity, and coherence for designed digital landscape models. Landsc. Urban Plan., 157, 407–421. DOI: 10.1016/j.landurbplan.2016.09.002.
  • [15] Loissios, D., Tzelepis, N. and Nakos, B. (2007). A methodology for creating analytical hill-shading by combining different lighting directions. In Proceedings of 23rd International Cartographic Conference, 4-10 August 2007. Moscow, Russia: International Cartographic Association.
  • [16] Machado, P., Romero, J., Nadal, M., Santos, A., Correia, J. and Carballal, A. (2015). Computerized measures of visual complexity. Acta Psychol., 160, 43–57. DOI: 10.1016/j.actpsy.2015.06.005.
  • [17] Mark, R. (1992). Multidirectional, oblique-weighted, shaded-relief image of the Island of Hawaii. U.S.Geological Survey. (OF-92-422).
  • [18] Meyer, M.A. and Booker, J.M. (2001). Eliciting and analyzing expert judgment: a practical guide.Philadephia, USA: Society for Industrial and Applied Mathematics.
  • [19] Misthos, L.M., Messaris, G., Damigos, D. and Menegaki, M. (2017). Exploring the perceived intrusion of mining into the landscape using the fuzzy cognitive mapping approach. Ecol. Eng., 101, 60–74.DOI: 10.1016/j.ecoleng.2017.01.015.
  • [20] Patel, V.L., Arocha, J.F. and Kaufman, D.R. (1999). Expertise and Tacit Knowledge in Medicine. In R.J. Sternberg and J.A. Horvath (Eds.), Tacit Knowledge. in Professional Practice: Research and Practitioner Perspectives (pp. 75–99). New Jersey, USA: Lawrence Erlbaum Associates Publishers.
  • [21] Pieters, R., Wedel, M. and Batra, R. (2010). The stopping power of advertising: Measures and effects of visual complexity. J. Mark., 74(5), 48–60. DOI: 10.1509/jmkg.74.5.048.
  • [22] Veronesi, F. and Hurni, L. (2015). A GIS tool to increase the visual quality of relief shading by automatically changing the light direction. Comput. Geosci., 74, 121–127. DOI: 10.1016/j.cageo.2014.10.015.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f08f1237-b6f5-4a8a-bedb-1f159326edd5
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