Exploratory Bivariate and Multivariate Geovisualizations of a Social Vulnerability Index

  • Georgianna Strode Florida State University
  • Victor Mesev Florida State Universiy
  • Susanne Bleisch FHNW University of Applied Sciences and Arts Northwestern Switzerland
  • Kathryn Ziewitz Florida Agricultural and Mechanical University
  • Fennis Reed
  • John Derek Morgan University of West Florida


In the United States, the Centers for Disease Control and Prevention (CDC) is the national agency that conducts and supports public health research and practice. Among the CDC’s many achievements is the development of a social vulnerability index (SVI) to aid planners and emergency responders when identifying vulnerable segments of the population, especially during natural hazard events. The index includes an overall social vulnerability ranking as well as four individual themes: socioeconomic, household composition & disability, ethnicity & language, and housing & transportation. This makes the SVI dataset multivariate, but it is typically viewed via maps that show one theme at a time. This paper explores a suite of cartographic techniques that can represent the SVI beyond the univariate view. Specifically, we recommend three techniques: (1) bivariate mapping to illustrate overall vulnerability and population density, (2) multivariate mapping using cartographic glyphs to disaggregate levels of the four vulnerability themes, and (3) visual analytics using Euler diagrams to depict overlap between the vulnerability themes. The CDC’s SVI, and by extension, vulnerability indices in other countries, can be viewed in a variety of cartographic forms that illustrate the location of vulnerable groups of society. Viewing data from various perspectives can facilitate the understanding and analysis of the growing amount and complexity of data.

Author Biography

Georgianna Strode, Florida State University
Georgianna is an application developer/programmer at the Florida Resources and Environmental Analysis Center (FREAC) of the Florida State University. Her interests include dasymetric population estimation techniques, geovisualization (especially bivariate mapping), and exploring the potential of using the US National Grid (USNG) in a more prominent role within GIS.
How to Cite
Strode, G., Mesev, V., Bleisch, S., Ziewitz, K., Reed, F., & Morgan, J. D. (2020). Exploratory Bivariate and Multivariate Geovisualizations of a Social Vulnerability Index. Cartographic Perspectives, (95), 5-23. https://doi.org/10.14714/CP95.1569
Peer-Reviewed Articles