Adaptive Choropleth mapper (ACM)

Documentation for Adaptive Choropleth Mapper (ACM)

( The Web Application URL: )

Developers: Su Han, Sergio Rey, Elijah Knaap, Wei Kang, Levi Wolf

Adaptive Choropleth Mapper (ACM) is an open-source mapping tool for the visualization of multiple choropleth maps, which provides the following functions.

  1. An automatic way to compute and set the same class intervals across different choropleth maps
  2. A paired visualization of choropleth maps, with both global and local classifications
  3. Linking and brushing across multiple choropleth maps in terms of map extents and class intervals
  4. A stacked chart representing the temporal change of each class in choropleth maps over time

  * Adaptive Choropleth Mapper(ACM) works best in FireFox. It has not been tested in IE.


  1. ACM creates both the same and individually different classification intervals for multiple choropleth maps.
  2. ACM provides several classification methods which are equal intervals, quantiles, standard deviation, arithmetic progression, geometric progression, and natural breaks classification methods.
  3. For each classification method, the ACM provides users an option to see maps either with global classification or with local classification
  4. ACM automatically synchronizes choropleth maps in terms of map extents and class intervals. The synchronization of ACM has two types: continuous synchronization and one-time synchronization. The continuous synchronization is appropriate for the relatively small data size of polygons or users who have state-of-the-art computers. The one-time synchronization function is appropriate with big data sets involving a large number of polygons or any users who do not have enough computing power in their computers.  
  5. ACM provides a stacked chart representing the temporal change of each class of choropleth maps over time. The stacked chart shows the change in the number of polygons belonging to each class interval. The chart appears only when the map extent and the class intervals of all maps are the same. To make all maps have the same map extent and class intervals, enable "Link All" or click "Link" on each of the maps.

Demo Videos

      1. Spatiotemporal Visualization at Multi-Scales

      2. Comparing Variables at Multi-Spatial Scales.


User's Guideline


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           <script src="data/LA_ex/GEO_JSON_SD.js"></script>

           <script src="data/LA_ex/GEO_VARIABLES_SD.js"></script>

Example Visualizations using Adaptive Choropleth Mapper

Link to Longitudinal Neighborhood Explorer (LNE) where ACM is embedded and which visualizes spatiotemporal census data.

Having errors in choropleth visualization?  Check your input data and make sure that your input data do not contain non-numeric data. The null value must be represented in -9999. You might have #DIV/0! in your data when you preprocess your data in Excel.

Copyright (c) 2018 Su Han, Sergio Rey, Elijah Knaap, Wei Kang, Levi Wolf

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.