13.1 Choropleth maps and cartograms

Choropleth maps and cartograms are powerful tools for visualizing spatial data. They use color and shape to show patterns across geographic areas, making complex info easy to grasp at a glance.

These techniques have pros and cons. Choropleths can mislead if data isn't normalized. Cartograms distort familiar shapes. But when used right, they reveal hidden trends and challenge assumptions about geographic importance.

Choropleth Maps and Cartograms

Purpose and Use Cases

Top images from around the web for Purpose and Use Cases

• 

  Visualization — Courses View original

  Is this image relevant?

• 

  ggplot2 - Cartogram + choropleth map in R - Stack Overflow View original

  Is this image relevant?

• 

  Visualization — Courses View original

  Is this image relevant?

• 

  ggplot2 - Cartogram + choropleth map in R - Stack Overflow View original

  Is this image relevant?

1 of 2

Top images from around the web for Purpose and Use Cases

• 

  Visualization — Courses View original

  Is this image relevant?

• 

  ggplot2 - Cartogram + choropleth map in R - Stack Overflow View original

  Is this image relevant?

• 

  Visualization — Courses View original

  Is this image relevant?

• 

  ggplot2 - Cartogram + choropleth map in R - Stack Overflow View original

  Is this image relevant?

1 of 2

• Choropleth maps use color or shading to represent the intensity or quantity of a variable within defined geographic areas, allowing for the visualization of spatial patterns and distributions
• Effective for displaying data that is standardized to a comparable scale, such as rates, ratios, or densities, rather than raw counts or totals
• Commonly used to visualize demographic data (population density, income levels), election results, disease prevalence, or environmental data across different regions
• Cartograms distort the size of geographic areas proportionally to the value of a chosen variable, emphasizing the relative importance or magnitude of the variable rather than the actual physical area
• Useful for highlighting disparities or inequalities in the distribution of a variable, such as population, wealth, or resource consumption, across different regions
• Can effectively challenge preconceived notions about the relative importance of different geographic areas based on their physical size alone

Limitations and Considerations

• Choropleth maps are subject to the modifiable areal unit problem (MAUP), where the choice of geographic boundaries can influence the perceived spatial patterns
• Ecological fallacy can occur when conclusions about individuals are incorrectly drawn from aggregate data in choropleth maps
• Cartograms may be difficult to read and interpret, particularly for audiences unfamiliar with the technique, and may require additional context or explanations to aid understanding
• Potential for misinterpretation or misuse of choropleth maps and cartograms exists, especially when the visualizations may be used to support particular arguments or agendas

Creating Choropleth Maps

Color Schemes and Data Classification

• Select a color scheme that effectively represents the nature of the data, such as sequential colors for ordered data (low to high values) or diverging colors for data with a meaningful middle point (above and below average)
• Ensure the chosen color scheme is colorblind-friendly and can be easily distinguished by viewers with color vision deficiencies
• Normalize the data to account for differences in the size or population of the geographic areas being compared, such as using rates or densities instead of raw counts
• Choose an appropriate data classification method to group the data into discrete categories or intervals, such as equal intervals, quantiles, or natural breaks (Jenks)
• Consider using 4-7 data classes for optimal comprehension, balancing the need for detail with the readability of the map

Legend and Labeling

• Include a clear and informative legend that explains the color scale and data classification method used, as well as the units of measurement for the variable being mapped
• Use appropriate labeling to identify the geographic areas being mapped, such as country or state names, ensuring that labels are legible and do not obscure important map features
• Consider adding additional labels or annotations to highlight specific data points or regions of interest, such as the highest or lowest values in the dataset

Designing Cartograms

Cartogram Techniques

• Select a cartogram technique that suits the nature of the data and the desired visual effect, such as:
  • Contiguous area cartograms, which maintain the adjacency of geographic areas while distorting their sizes
  • Non-contiguous area cartograms, which allow geographic areas to be separated from each other to better represent the data values
  • Dorling cartograms, which represent geographic areas with proportionally sized circles
• Ensure that the distortion of the geographic areas is proportional to the chosen variable, maintaining the relative magnitudes of the data values

Preserving Spatial Context

• Preserve the topology and relative positions of the geographic areas as much as possible to maintain recognizability and spatial context
• Use appropriate color schemes and labeling to enhance the readability and interpretation of the cartogram, especially when the distortion significantly alters the shape of familiar geographic areas
• Consider providing additional visual cues, such as reference lines or background maps, to help orient the viewer and provide spatial context

Evaluating Visualization Effectiveness

Assessing Choropleth Maps

• Assess whether the chosen color scheme and data classification method effectively highlight the spatial patterns and distributions of the mapped variable, without creating false impressions or obscuring important details
• Consider the potential limitations of choropleth maps, such as the modifiable areal unit problem (MAUP) and the ecological fallacy, and how they may impact the interpretation of the visualization
• Gather feedback from the target audience to gauge the effectiveness of the choropleth map in communicating the intended message and facilitating data-driven decision-making

Evaluating Cartograms

• Evaluate the readability and interpretability of cartograms, particularly for audiences unfamiliar with the technique, and consider providing additional context or explanations to aid understanding
• Assess the potential for misinterpretation or misuse of cartograms, especially when the visualizations may be used to support particular arguments or agendas
• Compare the effectiveness of cartograms to other methods of visualizing spatial data, such as choropleth maps or proportional symbol maps, in conveying the specific patterns and relationships of interest