Abstract
The visual attributes such as shape, color, size have been considered as the most basic form of information encoded in geographic information visualization interface; however, the optimal multi-visual coding forms and reasonable quantity are not well defined, nor has it been determined whether the advantage of one-attribute coding is maintained across different multi-visual coding. In this study, we choose four typical visual attributes (text, shape, color, size) in geographic information visualization and argue that the effects of multi-visual coding are affected by the coding forms and the levels of quantity. Our experiment used a within-subjects design, with independent variables of four visual attributes (text, shape, size, color) and the number (1, 2, 3, 4) of visual attributes in multi-visual coding forms. The results support the effects of multi-visual coding in geographic information visualization are modulated not only by the coding characteristics of each visual attribute, but also by the forms and the number of visual attributes in the coding forms.
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Acknowledgments
This paper was supported by the National Nature Science Foundation of China Grant (No. 72201128), the China Postdoctoral Science Foundation (No. 2023M730483) and the Collaborative Education Program of the Chinese Education Ministry (No. 202102298009).
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Zhang, J., Di, X., Zhao, L., Li, X., Xu, W. (2024). Research on the Effects of Multi-visual Coding in Geographic Information Visualization. In: Mori, H., Asahi, Y. (eds) Human Interface and the Management of Information. HCII 2024. Lecture Notes in Computer Science, vol 14690. Springer, Cham. https://doi.org/10.1007/978-3-031-60114-9_13
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DOI: https://doi.org/10.1007/978-3-031-60114-9_13
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