The State of the Art in Cartograms

TL;DR

This paper surveys the history, algorithms, and evaluation methods of cartograms, highlighting their diverse types and the trade-offs among accuracy dimensions to guide future research and design.

Contribution

It provides a comprehensive overview of cartogram types, algorithms, evaluation techniques, and identifies key challenges and guidelines for future development.

Findings

Different cartogram types balance accuracy dimensions differently.

Evaluation methods help compare cartogram effectiveness.

Design guidelines emerge from analysis of existing techniques.

Abstract

Cartograms combine statistical and geographical information in thematic maps, where areas of geographical regions (e.g., countries, states) are scaled in proportion to some statistic (e.g., population, income). Cartograms make it possible to gain insight into patterns and trends in the world around us and have been very popular visualizations for geo-referenced data for over a century. This work surveys cartogram research in visualization, cartography and geometry, covering a broad spectrum of different cartogram types: from the traditional rectangular and table cartograms, to Dorling and diffusion cartograms. A particular focus is the study of the major cartogram dimensions: statistical accuracy, geographical accuracy, and topological accuracy. We review the history of cartograms, describe the algorithms for generating them, and consider task taxonomies. We also review quantitative and qualitative evaluations, and we use these to arrive at design guidelines and research challenges.