Spatial text visualization using automatic typographic maps

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

doi:10.1109/TVCG.2012.264

Spatial text visualization using automatic typographic maps

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

Research output: Contribution to journal › Article › peer-review

35 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 language	English (US)
Article number	6327261
Pages (from-to)	2056-2564
Number of pages	509
Journal	IEEE Transactions on Visualization and Computer Graphics
Volume	18
Issue number	12
DOIs	https://doi.org/10.1109/TVCG.2012.264
State	Published - 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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10.1109/TVCG.2012.264

Cite this

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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.}",

note = "Funding Information: We thank Axis Maps for generously giving us the permission to use their Typographic Maps in this article as well as for providing details on how these maps are currently constructed. This work was supported in part by the U.S. Department of Homeland Security{\textquoteright}s VACCINE Center under award no. 2009-ST-061-CI0002 and the Defense Threat Reduction Agency under award no. HDTRA1-10-1-0083.",

year = "2012",

doi = "10.1109/TVCG.2012.264",

language = "English (US)",

volume = "18",

pages = "2056--2564",

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publisher = "IEEE Computer Society",

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AU - Afzal, Shehzad

AU - Maciejewski, Ross

AU - Jang, Yun

AU - Elmqvist, Niklas

AU - Ebert, David S.

N1 - Funding Information: We thank Axis Maps for generously giving us the permission to use their Typographic Maps in this article as well as for providing details on how these maps are currently constructed. This work was supported in part by the U.S. Department of Homeland Security’s VACCINE Center under award no. 2009-ST-061-CI0002 and the Defense Threat Reduction Agency under award no. HDTRA1-10-1-0083.

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

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Spatial text visualization using automatic typographic maps

Abstract

Keywords

ASJC Scopus subject areas

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