Evaluating the Impact of Shape and Metric Selection on Human Perception in Geospatial Data Visualizations

Visualizations such as bar charts, scatter plots, and objects on geographical maps often convey critical information, including exact and relative numeric values, using shapes. The choice of shape and method of encoding information is often selected arbitrarily, or decided based on convention or common practice. However, past studies have shown that the human eye can be fooled by visual representations. The Ebbinghaus illusion demonstrates that the perceived relative sizes of shapes depends on their configuration, which in turn can affect judgements, especially in visualizations like proportional symbol maps. In this study we evaluate the effects of varying the type of shapes and metrics for encoding geospatial data in visual representations on a spatio-temporal map interface. We find that some combinations of shape and metric are more conducive to accurate human judgements than others, and we provide recommendations for applying these findings in future spatial visualization designs.