Scaling of Geographic Space as a Universal Rule for Map Generalization

Bin Jiang, Xintao Liu, Tao Jia

Research output: Journal article publicationJournal articleAcademic researchpeer-review

31 Citations (Scopus)

Abstract

Map generalization is a process of producing maps at different levels of detail by retaining essential properties of the underlying geographic space. In this article, we explore how the map generalization process can be guided by the underlying scaling of geographic space. The scaling of geographic space refers to the fact that in a geographic space, small things are far more common than large ones. In the corresponding rank-size distribution, this scaling property is characterized by a heavy-tailed plot such as a power law, lognormal, or exponential function. In essence, any heavy-tailed distribution consists of the head of the distribution (with a low percentage of vital or large things) and the tail of the distribution (with a high percentage of trivial or small things). Importantly, the low and high percentages constitute an imbalanced contrast, e.g., 20 versus 80. We suggest that the purpose of map generalization is to retain the objects in the head and to eliminate or aggregate those in the tail. We applied this selection rule to three generalization experiments and found that the scaling of geographic space indeed underlies map generalization. We further relate the universal rule to Töpfer's radical law (or trained cartographers' decision making in general) and illustrate several advantages of the universal rule.
Original languageEnglish
Pages (from-to)844-855
Number of pages12
JournalAnnals of the Association of American Geographers
Volume103
Issue number4
DOIs
Publication statusPublished - 4 Jul 2013
Externally publishedYes

Keywords

  • head/tail breaks
  • head/tail division rule
  • heavy-tailed distributions
  • power law
  • principles of selection

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth-Surface Processes

Cite this