Generating grid maps via the snake model
<|reference_start|>Generating grid maps via the snake model: The grid map, often referred to as the tile map, stands as a vital tool in geospatial visualization, possessing unique attributes that differentiate it from more commonly known techniques such as choropleths and cartograms. It transforms geographic regions into grids, which requires the displacement of both region centroids and boundary nodes to establish a coherent grid arrangement. However, existing approaches typically displace region centroids and boundary nodes separately, potentially resulting in self-intersected boundaries and compromised relative orientation relations between regions. In this paper, we introduce a novel approach that leverages the Snake displacement algorithm from cartographic generalization to concurrently displace region centroids and boundary nodes. The revised Constrained Delaunay triangulation (CDT) is employed to represent the relations between regions and serves as a structural foundation for the Snake algorithm. Forces for displacing the region centroids into a grid-like pattern are then computed. These forces are iteratively applied within the Snake model until a satisfactory new boundary is achieved. Subsequently, the grid map is created by aligning the grids with the newly generated boundary, utilizing a one-to-one match algorithm to assign each region to a specific grid. Experimental results demonstrate that the proposed approach excels in maintaining the relative orientation and global shape of regions, albeit with a potential increase in local location deviations. We also present two strategies aligned with existing approaches to generate diverse grid maps for user preferences. Further details and resources are available on our project website: https://github.com/TrentonWei/DorlingMap.git.<|reference_end|>
@article{wei2024generating,
    title={Generating grid maps via the snake model},
    author={Zhiwei Wei, Nai Yang, Wenjia Xu, Su Ding},
    journal={Transactions in GIS, 2024, 1-19},
    year={2024},
    doi={10.1111/tgis.13174},
    archivePrefix={arXiv},
    eprint={2406.18573},
    primaryClass={cs.CV cs.CY cs.GR}
}