Spatial text visualization using automatic typographic maps

Shehzad Afzal, Ross Maciejewski, Yun Jang, Niklas Elmqvist, David S. Ebert

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

We present a method for automatically building typographic maps that merge text and spatial data into a visual representation where text alone forms the graphical features. We further show how to use this approach to visualize spatial data such as traffic density, crime rate, or demographic data. The technique accepts a vector representation of a geographic map and spatializes the textual labels in the space onto polylines and polygons based on user-defined visual attributes and constraints. Our sample implementation runs as a Web service, spatializing shape files from the OpenStreetMap project into typographic maps for any region.

Original languageEnglish (US)
Article number6327261
Pages (from-to)2056-2564
Number of pages509
JournalIEEE Transactions on Visualization and Computer Graphics
Volume18
Issue number12
DOIs
StatePublished - 2012

Keywords

  • Geovisualization
  • label placement
  • spatial data
  • text visualization

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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