The developed Python package, named VASA, will be accessible at https://github.com/move-ucsb/VASA. To demonstrate the applicability of the designed visualizations, the variability in spatiotemporal structure of human mobility patterns during the COVID-19 pandemic in the United States is assessed. VASA offers three novel multivariate visualizations: A stacked recency and consistency map, a line-path scatter plot, and a categorical strip (dot) plot. All three techniques use LISA as the base and utilize local Moran’s I and permuted p-values. The techniques are best suited for analysis of areal data at two levels of analysis: the object-level and the summary-level. The object-level of analysis receives the data at the finest available scale (e.g. county, census blocks, etc.), whereas the summary-level (e.g. state) refers to the less granular spatial units that contain object-level units. The stacked recency and consistency map allows to ascertain the spatiotemporal structure of data at both object- and summary-level. The categorical strip plot allows for comparison of trends at the summary-level. The line-path visualization is better suited for a fine-detail analysis of individual object-level trajectories within a specified summary-level.

The VASA package includes four classes:

• VASA: A class that deals with aggregations and missing values.

And 3 classes for corresponding types of charts:

• StackedChoropleth
• Scatter
• Strip

This StackedChoropleth shows the number of times a CBG was classified as a hot or cold spot over the time period.

This StackedChoropleth shows the last week a CBG was classified as a hot or cold spot over the time period.

This StackedChoropleth shows both the total number of times a county was classified as a hotspot or coldspot and the last week of that classification.

The following choropleth plot shows both the total number of times a CBG was classified as a hotspot or coldspot and the last week of that classification, by binning values and using the 2D color scheme listed.

Scatter plots provide an alternative view to the choropleths, allowing the option to highlight geometries grouped together at a higher level.

In this example of a Stripplot, the percentages of counties that were classified as hotspots or coldspots is shown for each state.

Update: adding interactive line scatter and choropleth plots

National Science Foundation BCS Awards 2043202 and 1853681.