Scale-Aware Cartographic Displacement Based on Constrained Optimization

Ken Maruyama, Shigeo Takahashi, Hsiang-Yun Wu, Kazuo Misue, Masatoshi Arikawa
Scale-Aware Cartographic Displacement Based on Constrained Optimization
In Proceedings of the 23th International Conference on Information Visualisation (iV2019), pages 74-80. July 2019.

Information

  • Publication Type: Conference Paper
  • Workgroup(s)/Project(s):
  • Date: July 2019
  • Booktitle: Proceedings of the 23th International Conference on Information Visualisation (iV2019)
  • Call for Papers: Call for Paper
  • DOI: https://dx.doi.org/10.1109/IV.2019.00022
  • Event: The 23th International Conference on Information Visualisation
  • Lecturer: Shigeo Takahashi
  • Pages (from): 74
  • Pages (to): 80
  • Keywords: Cartographic generalization, displacement, constrained optimization, scale-aware mapping

Abstract

Abstract—The consistent arrangement of map features in accordance with the map scale has recently been technically important in digital cartographic generalization. This is primarily due to the recent demand for informative mapping systems, especially for use in smartphones and tablets. However, such sophisticated generalization has usually been conducted manually by expert cartographers and thus results in a time-consuming and error-prone process. In this paper, we focus on the displacement process within cartographic generalization and formulate them as a constrained optimization problem to provide an associated algorithm implementation and its effective solution. We first identify the underlying spatial relationships among map features, such as points and lines, on each map scale as constraints and optimize the cost function that penalizes excessive displacement of the map features in terms of the map scale. Several examples are also provided to demonstrate that the proposed approach allows us to maintain consistent mapping regardless of changes to the map scale.

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BibTeX

@inproceedings{maruyama-2019-iv,
  title =      "Scale-Aware Cartographic Displacement Based on Constrained
               Optimization",
  author =     "Ken Maruyama and Shigeo Takahashi and Hsiang-Yun Wu and
               Kazuo Misue and Masatoshi  Arikawa",
  year =       "2019",
  abstract =   "Abstract—The consistent arrangement of map features in
               accordance with the map scale has recently been technically
               important in digital cartographic generalization. This is
               primarily due to the recent demand for informative mapping
               systems, especially for use in smartphones and tablets.
               However, such sophisticated generalization has usually been
               conducted manually by expert cartographers and thus results
               in a time-consuming and error-prone process. In this paper,
               we focus on the displacement process within cartographic
               generalization and formulate them as a constrained
               optimization problem to provide an associated algorithm
               implementation and its effective solution. We first identify
               the underlying spatial relationships among map features,
               such as points and lines, on each map scale as constraints
               and optimize the cost function that penalizes excessive
               displacement of the map features in terms of the map scale.
               Several examples are also provided to demonstrate that the
               proposed approach allows us to maintain consistent mapping
               regardless of changes to the map scale.",
  month =      jul,
  booktitle =  "Proceedings of the 23th International Conference on
               Information Visualisation (iV2019)",
  doi =        "https://dx.doi.org/10.1109/IV.2019.00022",
  event =      " The 23th International Conference on Information
               Visualisation ",
  pages =      "74--80",
  keywords =   "Cartographic generalization, displacement, constrained
               optimization, scale-aware mapping",
  URL =        "/research/publications/2019/maruyama-2019-iv/",
}