Gridded dot map technique for tackling visual clutter in discrete geographic data.
This is a rudimentary implementation of BinSq in processing-java for release alongside our publication. Processing (see http://www.processing.org) is required to compile this version. Files with .java extension will be part of a larger geotools package to be released in the near future.
The key components of the technique are illustrated in the image above. Steps 1 to 4 depict the transformation from a geographically accurate but cluttered representation, to a visual outcome optimal for comparing categorical and density differences.
Steps:
1. Data visualised with geographically accurate dot map.
2. Data is binned to a density approximating grid.
3. Data is equalised.
4. The resulting gridded map.
Please read our paper for complete description of the algorithm. A copy maybe obtained at http://www.tandfonline.com/doi/full/10.1080/15230406.2016.1174623. Do get in touch if you are interested in our work but do not have access to the journal.
Do cite the paper if you find it useful.
// Bibtex
@article{chua2016binsq,
title={BinSq: visualizing geographic dot density patterns with gridded maps},
author={Chua, Alvin and Vande Moere, Andrew},
journal={Cartography and Geographic Information Science},
pages={1--20},
year={2016},
publisher={Taylor \& Francis}
}