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

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

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LIPIcs.GISCIENCE.2018.37.pdf
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Author Details

Irene M. Johannsen
  • Department of Geography, University of Bonn, Meckenheimer Allee 172, D-53115 Bonn, Germany
Sara Irina Fabrikant
  • Department of Geography, University of Zurich, Winterthurerstr. 180, CH-8057 Zurich, Switzerland
Mariele Evers
  • Department of Geography, University of Bonn, Meckenheimer Allee 166, D-53115 Bonn, Germany

Funding

This work is based on the unpublished MSc thesis by the first author advised by the subsequent authors. It was partially supported by the Canton of Zurich, Switzerland.

Cite As Get BibTex

Irene M. Johannsen, Sara Irina Fabrikant, and Mariele Evers. How Do Texture and Color Communicate Uncertainty in Climate Change Map Displays? (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 37:1-37:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/LIPIcs.GISCIENCE.2018.37

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.

Subject Classification

ACM Subject Classification
  • Information systems → Geographic information systems
  • Human-centered computing → User centered design
  • Human-centered computing → Contextual design
  • Human-centered computing → Empirical studies in visualization
  • Human-centered computing → Visualization design and evaluation methods
Keywords
  • uncertainty visualization
  • empirical study
  • visual variables
  • climate change

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