License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GISCIENCE.2018.37
URN: urn:nbn:de:0030-drops-93655
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9365/
Go to the corresponding LIPIcs Volume Portal

Johannsen, Irene M. ; Fabrikant, Sara Irina ; Evers, Mariele

How Do Texture and Color Communicate Uncertainty in Climate Change Map Displays? (Short Paper)

pdf-format:
LIPIcs-GISCIENCE-2018-37.pdf (0.4 MB)

Abstract

We report on an empirical study with over hundred online participants where we investigated how texture and color value, two popular visual variables used to convey uncertainty in maps, are understood by non-domain-experts. Participants intuit denser dot textures to mean greater attribute certainty; irrespective of whether the dot pattern is labeled certain or uncertain. With this additional empirical evidence, we hope to further improve our understanding of how non-domain experts interpret uncertainty information depicted in map displays. This in turn will allow us to more clearly and legibly communicate uncertainty information in climate change maps, so that these displays can be unmistakably understood by decision-makers and the general public.

BibTeX - Entry

@InProceedings{johannsen_et_al:LIPIcs:2018:9365,
  author =	{Irene M. Johannsen and Sara Irina Fabrikant and Mariele Evers},
  title =	{{How Do Texture and Color Communicate Uncertainty in Climate Change Map Displaysl (Short Paper)}},
  booktitle =	{10th International Conference on Geographic Information  Science (GIScience 2018)},
  pages =	{37:1--37:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Stephan Winter and Amy Griffin and Monika Sester},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9365},
  URN =		{urn:nbn:de:0030-drops-93655},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.37},
  annote =	{Keywords: uncertainty visualization, empirical study, visual variables, climate change}
}

Keywords: uncertainty visualization, empirical study, visual variables, climate change
Collection: 10th International Conference on Geographic Information Science (GIScience 2018)
Issue Date: 2018
Date of publication: 02.08.2018

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI