Evaluation of Methods for Classifying Epidemiological Data on Choropleth Maps in Series

By Cynthia A. Brewer, Linda Pickle. 2002

436 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/422a8c493bdb8c7ae195d7e7130fb4dc80068180

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Martijn Tennekes
2. Bin Jiang
3. Alan M. MacEachren
4. Denis White
5. Daniel B. Carr
6. Daniel R. Montello

In Statistics and Probability

1. Bin Jiang
2. Alan M. MacEachren
3. Martijn Tennekes
4. Denis White
5. Daniel B. Carr

Citations in the corpus

• Head/Tail Breaks: A New Classification Scheme for Data with a Heavy-Tailed Distribution (2012, background): “Data classification is a fundamental issue in statistical mapping, and it is well known that different classification methods can lead to very different visual patterns, sometimes in a distorted or biased manner (e.g., MacEachren 1994; Monmonier 1996; Brewer and Pickle 2002).”
• Conditioned Choropleth Maps and Hypothesis Generation (2005, methodology): “Brewer and Pickle (2002) provided research indicating the merits of using quantiles (equal percent categories) and favored the use of five classes.”
• tmap: Thematic Maps in R (2018, background): “A good starting point is to use five or seven classes based on natural breaks (MacEachren 1994) or quantiles (Brewer and Pickle 2002).”