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Adaptive Choropleth Mapper: A Web-based Tool for Synchronous Exploration of Multiple Variables at Multiple Spatial Scales

Su Yeon Han, Sergio Rey, Elijah Knaap, Wei Kang, Levi Wolf

Abstract


Choropleth mapping is an essential visualization technique for exploratory spatial data analysis. Most conventional choropleth mapping tools assign observations a specific color corresponding to their position in the distribution of values over the entire map. This practice is often an issue for user experience since the classification is not responsive to the map view. The fixed full-map classification scheme cannot emphasize the local differences if the map’s spatial focus is changed. Another issue is that the choropleth mapping tools in popular GIS packages do not provide an automatic way to set the same class interval for multiple choropleth maps representing each different variable. Thus, it is hard to reveal the difference in the distributional patterns across time or in multiple maps representing each different variable. To overcome this limitation with conventional choropleth mapping tools, we developed a highly interactive and user-friendly Web-based choropleth mapping tool called Adaptive Choropleth Mapper (ACM) which provides all of the following functions. First, it provides an automatic way to set the same class interval to multiple choropleth maps. Second, the class intervals are automatically recalculated to focus on areas within the current view of the map. Third, other maps’ views are automatically updated to have the same extent, and their class intervals are recomputed as well. Fourth, the ACM provides a stacked chart representing the temporal change of each class of choropleth maps within the map extent. These four functions of ACM enable more meaningful interactive investigations of multiple choropleth maps in space and time.

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This work is licensed under a Creative Commons Attribution 3.0 License.