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Conference paper
Exploring the visual correlation of choropleth maps using an evolutionary algorithm
Auto-Carto Research Symposium, 2005 (Las Vegas, Nevada)
2005
DOI: 10.17077/vhby-49mr
Abstract
Multivariate choropleth maps are often used to compare patterns of different spatial variables. This approach can be implemented by simultaneously drawing a series of choropleth maps, with each representing a particular variable. In this paper, we develop an evolutionary algorithm that can be used to generate a set of classifications that allow a user to explore the spatial patterns of multiple choropleth maps in terms of their visual correlation. Synthetic and census data are used to demonstrate the effectiveness of our approach. We also discuss the role of our approach in an interactive mapping environment and its implication for spatial data mining.
Details
- Title: Subtitle
- Exploring the visual correlation of choropleth maps using an evolutionary algorithm
- Creators
- Ningchuan Xiao - The Ohio State UniversityMarc P Armstrong - University of Iowa
- Resource Type
- Conference paper
- Conference
- Auto-Carto Research Symposium, 2005 (Las Vegas, Nevada)
- DOI
- 10.17077/vhby-49mr
- Number of pages
- 11 pages
- Copyright
- Copyright © 2005 Ningchuan Xiao and Marc P. Armstrong
- Comment
Subsequently published as "Supporting the Comparison of Choropleth Maps Using an Evolutionary Algorithm." Cartography and Geographic Information Science, Volume 32, 2005 - Issue 4, pages 347-358 https://doi.org/10.1559/152304005775194755
- Language
- English
- Date copyrighted
- 2005
- Date presented
- 2005
- Academic Unit
- Geographical and Sustainability Sciences
- Record Identifier
- 9983557444402771
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