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Fast flow-based algorithm for creating density-equalizing map projections.

Michael T Gastner1, Vivien Seguy2, Pratyush More3

  • 1Division of Science, Yale-NUS College, Singapore 138527; michael.gastner@yale-nus.edu.sg.

Proceedings of the National Academy of Sciences of the United States of America
|February 22, 2018
PubMed
Summary
This summary is machine-generated.

A new flow-based algorithm rapidly generates accurate cartograms, which are maps resized by data. This computational cartography method significantly speeds up the creation of data-driven visualizations for spatial analysis.

Keywords:
cartographycomputer graphicsdata visualizationstatistical analysis

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Area of Science:

  • Computational cartography
  • Geographic Information Systems (GIS)
  • Data visualization

Background:

  • Cartograms rescale geographic regions based on quantitative data, offering advantages over traditional charts for spatial analysis.
  • Existing computational methods for cartogram generation, often physics-inspired, face challenges in speed and accuracy.
  • Developing algorithms for rapid and accurate coordinate transformation in cartograms remains a significant challenge.

Purpose of the Study:

  • To introduce a novel flow-based algorithm for generating cartograms.
  • To improve the computational efficiency and accuracy of cartogram creation.
  • To enable faster spatial statistical analysis through enhanced data visualization.

Main Methods:

  • Development of a flow-based algorithm utilizing physics-inspired equations of motion.
  • Numerical methods designed for easier equation solving and straightforward parallelization.
  • Transformation of all map coordinates, including non-border points, to create accurate projections.

Main Results:

  • The proposed algorithm achieves significantly faster computation times, reducing generation to seconds.
  • Maintains comparable quantitative measures of shape distortion to previous methods.
  • Ensures accurate area scaling, correct region fitting, and generates a map projection for every point.

Conclusions:

  • The new flow-based algorithm offers a substantial speedup for cartogram generation without compromising accuracy.
  • This method facilitates more efficient spatial statistical analysis and data-driven map creation.
  • Demonstrated applications include election results, economic data, and public health mapping.