Evaluating User Interaction with Cartographic Visualizations on Mobile and Desktop Platforms
Do people read interactive maps differently on a phone than on a computer? In a lab study, 41 cartography students solved the same nine map tasks on both devices while every click, zoom and pan was logged. They were just as accurate on the phone, but needed many more interactions: on phones they kept moving the map, on desktops they clicked straight to the information they needed.
- Year
- 2026
- Type
- Journal article
- Original language
- EN
- Journal
- International Journal of Human–Computer Interaction
- Authors
- S. Popelka, O. Ruzicka, T. Vanicek, K. Facevicova, M. Beitlova, M. Vojtechovska, P. Cybulski, Z. Stachon
Contribution
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Directly compares identical cartographic tasks on desktop and smartphone in a counterbalanced within-subject design (41 participants, nine tasks on choropleth and point symbol maps, two equivalent task variants), rather than studying one device in isolation as most prior work does.
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Introduces MishPink, a responsive web platform built on Leaflet that runs the tasks and logs map interactions (pan, zoom, pop-ups, layer and legend actions) together with task events, buffering them locally so no data is lost on mobile devices.
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Shows that the device barely affects outcomes: accuracy did not differ, and completion time differed significantly in only two of nine tasks (both faster on desktop), whereas smartphones required significantly more interactions in every task.
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Goes beyond counts by analysing interaction types as proportions (compositional profiles, ternary diagrams): even after normalisation, smartphone use is dominated by continuous panning, while desktop use relies more on targeted pop-up queries—a difference in strategy, not just in effort.
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Finds that the device effect depends on the map type—clear for choropleth maps, weak for point symbol maps—and that expertise mainly changes which elements people use (more legend and layer use among advanced students), not how much they interact.
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Uses eye-tracking on both devices as qualitative context for the logs rather than as a quantitative measure, and states openly why: dynamic, participant-specific map views made standard AOI analysis infeasible, and the recordings were inspected by a single researcher.
Abstract
Questions addressed
Are people less accurate when reading interactive maps on a smartphone than on a desktop?
Not in this study. Across nine tasks, the median accuracy difference between desktop and smartphone was zero, and no task showed a significant difference after correction for multiple comparisons. Errors were driven mainly by task difficulty and by participants misunderstanding what to compare, not by the device. The caveat is that the map application was responsive and the tasks clearly defined, and participants were cartography students.
Why do people need more interactions on a phone, and does that make them slower?
On a small screen people lose the overview, so they compensate with many short pan and zoom steps and repeated "inspect–adjust–inspect" cycles around pop-up windows. Smartphones required significantly more actions in every task (median differences of roughly 7–33 actions per task). Yet completion time was mostly comparable: these extra actions are short and cheap, so interaction count and time measure different things.
Do smartphone and desktop users follow different strategies, or do phone users just do more of the same?
Different strategies. When each participant’s actions were converted to proportions, so that the higher totals on phones no longer mattered, phone profiles were still dominated by panning (often over half of all actions), while desktop profiles on choropleth maps leaned towards pop-up queries. The same participants shifted their mix when they switched devices, and the order in which they used the devices did not explain it.
Does the device matter equally for all kinds of maps?
No. For choropleth maps, where values had to be read from pop-ups or compared across layers, desktop and smartphone strategies separated clearly. For point symbol maps, both devices converged on scanning the map by panning, with only subtle differences. Task and map type therefore shape interaction at least as much as the device.
How does map expertise change the way people use interactive map controls?
More experienced students used the legend and layer controls more purposefully, while beginners often skipped the legend after training and relied on clicking features for pop-up values. Expertise changed which tools were used rather than how often people interacted. Strategies still varied a lot within every group: some advanced students never opened the legend in point symbol tasks.
What does this mean for designing mobile-first web maps?
Because phone users reach the same answers through many more navigation steps, mobile map interfaces should cut unnecessary interactions: keep the legend visible or one tap away without covering the map, simplify layer management, reduce the steps needed to retrieve attribute values, and make pop-ups compact and touch-friendly.
What are the main limitations of the study?
It was a controlled lab study with cartography students from one university, so it may not reflect everyday map use or less experienced users. Eye-tracking on the two devices used different hardware and could not be analysed quantitatively; it was inspected by one researcher without independent coding. Despite counterbalancing, some learning transfer between devices cannot be fully excluded.
Citation
Popelka, S., Ruzicka, O., Vanicek, T., Facevicova, K., Beitlova, M., Vojtechovska, M., Cybulski, P., & Stachon, Z. (2026). Evaluating user interaction with cartographic visualizations on mobile and desktop platforms. International Journal of Human–Computer Interaction. https://doi.org/10.1080/10447318.2026.2718631
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