Matzen, Laura E.Howell, Breannan C.Tuft, MarieDivis, Kristin M.Aigner, WolfgangArchambault, DanielBujack, Roxana2024-05-212024-05-2120241467-8659https://doi.org/10.1111/cgf.15094https://diglib.eg.org/handle/10.1111/cgf15094People frequently make decisions based on uncertain information. Prior research has shown that visualizations of uncertainty can help to support better decision making. However, research has also shown that different representations of the same information can lead to different patterns of decision making. It is crucial for researchers to develop a better scientific understanding of when, why and how different representations of uncertainty lead viewers to make different decisions. This paper seeks to address this need by comparing geospatial visualizations of wildfire risk to verbal descriptions of the same risk. In three experiments, we manipulated the specificity of the uncertain information as well as the visual cues used to encode risk in the visualizations. All three experiments found that participants were more likely to evacuate in response to a hypothetical wildfire if the risk information was presented verbally. When the risk was presented visually, participants were less likely to evacuate, particularly when transparency was used to encode the risk information. Experiment 1 showed that evacuation rates were lower for transparency maps than for other types of visualizations. Experiments 2 and 3 sought to replicate this effect and to test how it related to other factors. Experiment 2 varied the hue used for the transparency maps and Experiment 3 manipulated the salience of the borders between the different risk levels. These experiments showed lower evacuation rates in response to transparency maps regardless of hue. The effect was partially, but not entirely, mitigated by adding salient borders to the transparency maps. Taken together, these experiments show that using transparency to encode information about risk can lead to very different patterns of decision making than other encodings of the same information.CCS Concepts: Human-centered computing → Empirical studies in visualizationHuman centered computing → Empirical studies in visualization10.1111/cgf.1509412 pages