Spatial text visualization using automatic typographic maps

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

Research output: Contribution to journalArticle

25 Citations (Scopus)

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)2556-2564
Number of pages9
JournalIEEE Transactions on Visualization and Computer Graphics
Volume18
Issue number12
DOIs
StatePublished - 2012

Fingerprint

Visualization
Crime
Web services
Labels

Keywords

  • Geovisualization
  • label placement
  • spatial data
  • text visualization

ASJC Scopus subject areas

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

Cite this

Spatial text visualization using automatic typographic maps. / Afzal, Shehzad; Maciejewski, Ross; Jang, Yun; Elmqvist, Niklas; Ebert, David S.

In: IEEE Transactions on Visualization and Computer Graphics, Vol. 18, No. 12, 6327261, 2012, p. 2556-2564.

Research output: Contribution to journalArticle

Afzal, Shehzad ; Maciejewski, Ross ; Jang, Yun ; Elmqvist, Niklas ; Ebert, David S. / Spatial text visualization using automatic typographic maps. In: IEEE Transactions on Visualization and Computer Graphics. 2012 ; Vol. 18, No. 12. pp. 2556-2564.
@article{fa854cfb8da040bdbac318836ff432e6,
title = "Spatial text visualization using automatic typographic maps",
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.",
keywords = "Geovisualization, label placement, spatial data, text visualization",
author = "Shehzad Afzal and Ross Maciejewski and Yun Jang and Niklas Elmqvist and Ebert, {David S.}",
year = "2012",
doi = "10.1109/TVCG.2012.264",
language = "English (US)",
volume = "18",
pages = "2556--2564",
journal = "IEEE Transactions on Visualization and Computer Graphics",
issn = "1077-2626",
publisher = "IEEE Computer Society",
number = "12",

}

TY - JOUR

T1 - Spatial text visualization using automatic typographic maps

AU - Afzal, Shehzad

AU - Maciejewski, Ross

AU - Jang, Yun

AU - Elmqvist, Niklas

AU - Ebert, David S.

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

KW - Geovisualization

KW - label placement

KW - spatial data

KW - text visualization

UR - http://www.scopus.com/inward/record.url?scp=84867649130&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84867649130&partnerID=8YFLogxK

U2 - 10.1109/TVCG.2012.264

DO - 10.1109/TVCG.2012.264

M3 - Article

VL - 18

SP - 2556

EP - 2564

JO - IEEE Transactions on Visualization and Computer Graphics

JF - IEEE Transactions on Visualization and Computer Graphics

SN - 1077-2626

IS - 12

M1 - 6327261

ER -