research-article

CartoDraw: A Fast Algorithm for Generating Contiguous Cartograms

Authors:

Daniel A. Keim,

Stephen C. North,

Christian PanseAuthors Info & Claims

IEEE Transactions on Visualization and Computer Graphics, Volume 10, Issue 1

Pages 95 - 110

https://doi.org/10.1109/TVCG.2004.1260761

Published: 01 January 2004 Publication History

Abstract

Abstract- Cartograms are a well-known technique for showing geography-related statistical information, such as population demographics and epidemiological data. The basic idea is to distort a map by resizing its regions according to a statistical parameter, but in a way that keeps the map recognizable. In this study, we formally define a family of cartogram drawing problems. We show that even simple variants are unsolvable in the general case. Because the feasible variants are NP-complete, heuristics are needed to solve the problem. Previously proposed solutions suffer from problems with the quality of the generated drawings. For a cartogram to be recognizable, it is important to preserve the global shape or outline of the input map, a requirement that has been overlooked in the past. To address this, our objective function for cartogram drawing includes both global and local shape preservation. To measure the degree of shape preservation, we propose a shape similarity function, which is based on a Fourier transformation of the polygons' curvatures. Also, our application is visualization of dynamic data, for which we need an algorithm that recalculates a cartogram in a few seconds. None of the previous algorithms provides adequate performance with an acceptable level of quality for this application. In this paper, we therefore propose an efficient iterative scanline algorithm to reposition edges while preserving local and global shapes. Scanlines may be generated automatically or entered interactively to guide the optimization process more closely. We apply our algorithm to several example data sets and provide a detailed comparison of the two variants of our algorithm and previous approaches.

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Cited By

Nickel SSondag MMeulemans WKobourov SPeltonen JNöllenburg M(2022)Multicriteria Optimization for Dynamic Demers CartogramsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.315122728:6(2376-2387)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1109/TVCG.2022.3151227
Hasan MMondal DTasnim JSchneider K(2021)Putting Table Cartograms into PracticeAdvances in Visual Computing10.1007/978-3-030-90439-5_8(91-102)Online publication date: 4-Oct-2021
https://dl.acm.org/doi/10.1007/978-3-030-90439-5_8
Chen JWang CLi C(2020)Resizing geovisualization with density map via a map collageJournal of Visualization10.1007/s12650-019-00610-423:1(125-139)Online publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1007/s12650-019-00610-4
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cover image IEEE Transactions on Visualization and Computer Graphics

IEEE Transactions on Visualization and Computer Graphics Volume 10, Issue 1

January 2004

113 pages

ISSN:1077-2626

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Copyright © Copyright © 2004 IEEE. All Rights Reserved.

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IEEE Educational Activities Department

United States

Publication History

Published: 01 January 2004

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Cited By

Nickel SSondag MMeulemans WKobourov SPeltonen JNöllenburg M(2022)Multicriteria Optimization for Dynamic Demers CartogramsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.315122728:6(2376-2387)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1109/TVCG.2022.3151227
Hasan MMondal DTasnim JSchneider K(2021)Putting Table Cartograms into PracticeAdvances in Visual Computing10.1007/978-3-030-90439-5_8(91-102)Online publication date: 4-Oct-2021
https://dl.acm.org/doi/10.1007/978-3-030-90439-5_8
Chen JWang CLi C(2020)Resizing geovisualization with density map via a map collageJournal of Visualization10.1007/s12650-019-00610-423:1(125-139)Online publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1007/s12650-019-00610-4
Nickel SSondag MMeulemans WChimani MKobourov SPeltonen JNöllenburg M(2019)Computing Stable Demers CartogramsGraph Drawing and Network Visualization10.1007/978-3-030-35802-0_4(46-60)Online publication date: 17-Sep-2019
https://dl.acm.org/doi/10.1007/978-3-030-35802-0_4
Tong CMcNabb LLaramee RLaramee RTam GVidal F(2018)Cartograms with topological featuresProceedings of the Conference on Computer Graphics & Visual Computing10.2312/cgvc.20181217(127-134)Online publication date: 13-Sep-2018
https://dl.acm.org/doi/10.2312/cgvc.20181217
Hong SYoo MChinh BHan ABattersby SKim JMandryk RHancock MPerry MCox A(2018)To Distort or Not to DistortProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3174202(1-12)Online publication date: 21-Apr-2018
https://dl.acm.org/doi/10.1145/3173574.3174202
Nusrat SAlam MScheidegger CKobourov S(2018)Cartogram Visualization for Bivariate Geo-Statistical DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2017.276533024:10(2675-2688)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1109/TVCG.2017.2765330
Evans WFelsner SKaufmann MKobourov SMondal DNishat RVerbeek K(2018)Table cartogramComputational Geometry: Theory and Applications10.1016/j.comgeo.2017.06.01068:C(174-185)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1016/j.comgeo.2017.06.010
Tong CRoberts RLaramee RBerridge DThayer DWan TVidal F(2017)Cartographic treemaps for visualization of public healthcare dataProceedings of the Conference on Computer Graphics & Visual Computing10.2312/cgvc.20171276(29-42)Online publication date: 14-Sep-2017
https://dl.acm.org/doi/10.2312/cgvc.20171276
Tong CMcNabb LLaramee RLyons JWalters ABerridge DThayer DWan TVidal F(2017)Time-oriented cartographic treemaps for visualization of public healthcare dataProceedings of the Conference on Computer Graphics & Visual Computing10.2312/cgvc.20171273(1-18)Online publication date: 14-Sep-2017
https://dl.acm.org/doi/10.2312/cgvc.20171273
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