What can cartographers learn from artistic paintings when stylizing maps? A preliminary synthesis from the perspective of visual neuroscience

ABSTRACT

Creating a map style from scratch is challenging. Cartographers may find inspirations from artistic paintings and transfer their style to maps. However, the reference painting and the extracted style elements may not fit well with the content and function of maps, resulting in undesirable or even frustrating map stylization. The question of how to choose appropriate paintings as inspirations and utilize their essential visual elements to stylize maps remains unanswered. As neuroscience has developed, an increasing number of neural mechanisms underlying visual perception have been discovered, deepening our understanding of artistic styles and their adaptation to maps. In this paper, we draw connections between visual neurons and style elements of both artistic paintings and maps by examining seven neural mechanisms (i.e. central-peripheral vision, color-to-contour adhesion, double-opponent effects, visual filling-in, orientation selectivity, latency variation, and what-where separation) that are typical of artistic paintings. We also demonstrate that these mechanisms are transferable to maps. We then create a cartographic style syntactics to generally indicate how and to what degree these mechanisms can be reflected in four cartographic stylistic criteria (i.e. identification, expressiveness, aesthetic appeal and emotional impact). Our work contributes to the integration of principles from neuroscience with cartographic design to deepen our understanding of map perception and to facilitate map style transfer.

KEYWORDS:

• Cartographic style
• neurosciences
• visual perception
• visual mechanism
• map style transfer

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data are available upon request from the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [under Grants 42371443, 41971417].