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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2508.07529 |
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Table des matières:
- Chorematic diagrams are highly reduced schematic maps of geospatial data and processes. They can visually summarize complex situations using only a few simple shapes (choremes) placed upon a simplified base map. Due to the extreme reduction of data in chorematic diagrams, they tend to be produced manually; few automated solutions exist. In this paper we consider the algorithmic problem of summarizing classed region maps, such as choropleth or land use maps, using a chorematic diagram with a single disk choreme. It is infeasible to solve this problem exactly for large maps. Hence, we propose several point sampling strategies and use algorithms for classed point sets to efficiently find the best disk that represents one of the classes. We implemented our algorithm and experimentally compared sampling strategies and densities. The results show that with the right sampling strategy, high-quality results can be obtained already with moderately sized point sets and within seconds of computation time.